Medizinische Hochschule

Medizinische Hochschule Hannover

Klinik für Strahlentherapie und Spezielle Onkologie

Arbeitsgruppe Experimentelle Radioonkologie

Impact of the DNA damage response

in clinical and cellular

radiosensitivity of cancer patients

INAUGURALDISSERTATION

zur Erlangung des Grades einer Doktorin der Naturwissenschaften

– Doctor rerum naturalium –

(Dr. rer. nat.)

vorgelegt von

Katharina Neuhäuser

geboren in Braunschweig

Hannover 2017

2

Angenommen durch den Senat: 12.04.2018

Präsident: Prof. Dr. med. Christopher Baum

Wissenschaftliche Betreuung: Prof. Dr. med. Hans Christiansen

Wissenschaftliche Zweitbetreuung: Prof.‘in Dr. med. vet. Teruko Tamura-Niemann

1. Referent: Prof. Dr. med. Hans Christiansen

2. Referent: Prof.‘in Dr. med. vet. Teruko Tamura-Niemann

3. Referent: Prof. Dr. rer. nat. Ulrich Lehmann-Mühlenhoff

Tag der mündlichen Prüfung: 12.04.2018

Prüfungsausschuss

Vorsitz: Prof. Dr. rer. nat. Immo Prinz

1. Prüfer: Prof. Dr. med. Hans Christiansen

2. Prüfer: Prof.‘in Dr. med. vet. Teruko Tamura-Niemann

3. Prüfer: Prof. Dr. rer. nat. Ulrich Lehmann-Mühlenhoff

3

Diese Arbeit ist meiner Familie und dem Anderen gewidmet

4

Table of contents Index of Figures and Tables ....................................................................................................... 8

Figures ........................................................................................................................................ 8

Tables ......................................................................................................................................... 9

Supplementary figures .............................................................................................................. 9

List of abbreviations ................................................................................................................. 12

Publications and contributions ................................................................................................ 15

Summary .................................................................................................................................. 16

Zusammenfassung .................................................................................................................... 18

1 Introduction part 1: The DNA damage response .............................................................. 20

1.1 Forms of DNA lesions and repair pathways .............................................................. 20

1.1.1 DNA single-strand break repair of replication-associated DNA damage ........... 22

1.1.2 DNA double-strand break repair ........................................................................ 24

1.2 The cell cycle and checkpoint control ....................................................................... 26

1.3 Apical kinases of the DNA damage response ............................................................ 28

1.3.1 ATR in DNA repair and checkpoint control ........................................................ 29

1.3.2 ATM in DNA repair and checkpoint control ....................................................... 29

1.3.3 Crosstalk of ATR and ATM in DNA repair and checkpoint control ..................... 33

1.4 The Fanconi anemia (FA) pathway ............................................................................ 34

1.4.1 Genetic heterogeneity of Fanconi anemia ......................................................... 34

1.4.2 The FA pathway in crosslink repair .................................................................... 34

1.4.3 Bridging of the FA pathway with other DNA repair mechanisms ...................... 35

1.5 The translationally controlled tumor protein as new player in DNA repair .............. 36

2 Introduction part 2: Individual radiosensitivity in cancer treatment ............................... 37

2.1 Cancer ........................................................................................................................ 37

2.2 Breast cancer ............................................................................................................. 38

2.2.1 Genetic predisposition and familial breast cancer ............................................ 38

2.2.2 Breast cancer subtypes and triple negative breast cancer ................................ 39

2.3 The relationship between cancer and radiosensitivity ............................................. 40

2.3.1 Benefits and drawbacks of irradiation treatment .............................................. 40

2.3.2 Molecular basis of radiation therapy ................................................................. 41

2.3.3 Adverse effects on healthy tissues ..................................................................... 41

2.3.4 Chemoradiosensitivity ........................................................................................ 43

2.3.5 Known radiosensitivity syndromes and inflicted genes ..................................... 44

2.3.6 Different forms of cell death following irradiation ............................................ 47

5

2.4 Related work on characterization of individual radiosensitivity ............................... 48

2.5 Previous and related work on TPT1 in breast cancer and ATM signaling ................. 52

2.5.1 TPT1 as a candidate BC susceptibility gene ....................................................... 52

2.5.2 The proposed role of TPT1 in ATM signaling ..................................................... 52

2.6 Hypothesis and aims of this project .......................................................................... 53

3 Material and methods ...................................................................................................... 56

3.1 Material ..................................................................................................................... 56

3.1.1 Cell lines .............................................................................................................. 56

3.1.2 Antibodies .......................................................................................................... 58

3.1.3 Plasmids and kits ................................................................................................ 59

3.1.4 Chemicals ........................................................................................................... 60

3.1.5 Enzymes and siRNAs ........................................................................................... 62

3.1.6 Medium and other materials ............................................................................. 62

3.1.7 Buffers and solutions .......................................................................................... 63

3.1.8 Devices and disposables ..................................................................................... 65

3.1.9 Software ............................................................................................................. 68

3.1.10 Gene Nomenclature ........................................................................................... 68

3.2 Cell culture methods.................................................................................................. 68

3.2.1 Culture, counting and cryopreservation of cells ................................................ 68

3.2.2 Telomerase reverse transcriptase immortalization ........................................... 70

3.2.3 Mycoplasm treatment ........................................................................................ 71

3.2.4 Reverse transfection and siRNA silencing .......................................................... 72

3.2.5 ATM inhibition .................................................................................................... 72

3.2.6 Irradiation ........................................................................................................... 72

3.2.7 Lysate preparation and immunoblotting ........................................................... 72

3.2.8 Sodium dodecyl sulfate polyacrylamide gel electrophoresis and western blot 73

3.2.9 Immunocytochemistry and pre-extraction ........................................................ 75

3.2.10 Image processing and foci analyses ................................................................... 76

3.2.11 Colony survival assay .......................................................................................... 77

3.2.12 Senescence assay ............................................................................................... 77

3.3 Other methods .......................................................................................................... 78

3.3.1 Statistics ............................................................................................................. 78

3.3.2 Patients ............................................................................................................... 79

3.3.3 DNA extraction ................................................................................................... 79

3.3.4 Exome sequencing .............................................................................................. 80

3.3.5 Primer design and polymerase chain reaction ................................................... 81

6

3.3.6 Agarose gel electrophoresis ............................................................................... 82

3.3.7 Sanger sequencing ............................................................................................. 82

3.3.8 Bioinformatics .................................................................................................... 83

4 Results ............................................................................................................................... 85

4.1 Assessment of TPT1 as candidate radiosensitivity marker in ATM signaling ............ 85

4.1.1 TPT1 does not affect early ATM signaling after irradiation ............................... 85

4.1.2 Intracellular distribution of TPT1 does not change after irradiation ................. 86

4.1.3 Limited colocalization of TPT1 with γH2AX foci after irradiation ...................... 87

4.1.4 Knockdown of TPT1 does not impair formation of γH2AX foci after irradiation 88

4.2 Assessment of the functional relationship between clinical and cellular radiosensitivity...................................................................................................................... 90

4.2.1 The genetic signature of radiosensitivity ........................................................... 90

4.2.2 Annotation of exome sequencing data by GeneCards ...................................... 90

4.2.3 Ingenuity Pathway Analysis ................................................................................ 92

4.2.4 Reactome Pathway Analysis and comparison of annotation tools ................. 102

4.2.5 Validation of exome sequencing data .............................................................. 104

4.3 Generation of cell cultures and functional assays ................................................... 105

4.3.1 Immortalization of primary skin fibroblasts from RS BC patients .................... 105

4.4 Functional studies in TERT immortalized cells of RS BC patients ............................ 107

4.4.1 ATM signaling after irradiation ........................................................................ 107

4.4.2 Kinetics of DNA damage recognition and repair in TERT immortalized cells of RS BC patients ...................................................................................................................... 108

4.4.3 Previous studies on RAD51 foci formation in primary RS cells and comparison to results obtained with TERT RS cells ............................................................................ 110

4.4.4 Colony survival after irradiation as functional endpoint ................................. 111

4.4.5 Irradiation-associated senescence as functional endpoint.............................. 114

5 Discussion ........................................................................................................................ 117

5.1 TPT1 as candidate marker for individual radiosensitivity ....................................... 117

5.1.1 No evidence for a role of TPT1 in early ATM signaling .................................... 117

5.1.2 No evidence for nuclear translocation or chromatin binding of TPT1 upon irradiation ........................................................................................................................ 118

5.1.3 No evidence for an effect of TPT1 on foci formation and resolution after irradiation ........................................................................................................................ 119

5.1.4 No evidence for elevation of TPT1 levels in breast cancer cell lines ............... 120

5.1.5 The effect of TPT1 on DNA damage sensing and repair might depend on cell type 121

5.2 Exome sequencing as tool to identify the genetic background of RS ..................... 122

7

5.2.1 Annotation by GeneCards reveals strong inter-individual variability in RS patients 123

5.2.2 Mutations in Cancer and DNA repair genes correlate with individual RS ....... 124

5.2.3 Association of cancer and DNA damage response genes in RS patients by IPA 126

5.2.4 Cancer and DNA damage response genes associate to clinical RS and not solely to cancer malady ............................................................................................................. 127

5.3 Functional studies in cells from radiosensitive patients ......................................... 132

5.3.1 Early ATM signaling is functional in TERT immortalized fibroblasts of RS BC patients 133

5.3.2 Repair up to 48 h after IR is efficient in TERT immortalized fibroblasts of RS BC patients 135

5.3.3 Mutational background of MC3 and MC7 correlates with RAD51 foci formation defects 136

5.3.4 Cellular RS is associated with clinical RS according to colony survival ............ 138

5.3.5 RS may manifest downstream of DSB recognition through cellular senescence

140

5.4 Impact of the DNA damage response on clinical and cellular RS ............................ 145

6 Conclusions and perspectives ......................................................................................... 147

7 References ...................................................................................................................... 152

8 Supplementary information ............................................................................................ 200

9 Acknowledgement .......................................................................................................... 259

10 Curriculum Vitae .......................................................................................................... 260

Electronic appendix ................................................................................................................ 263

8

Index of Figures and Tables

Figures

Figure 1 Overview showing forms of DNA lesions and the corresponding DNA damage

responses.................................................................................................................................. 21

Figure 2 Cell cycle phases and checkpoints ............................................................................. 28

Figure 3 ATM signaling after ionizing radiation shown as intracellular pathway by Ingenuity

Pathway Analysis ...................................................................................................................... 32

Figure 4 Distinct roles for ATR and ATM in checkpoint control ............................................... 33

Figure 5 Estimated new cancer cases and deaths in the USA in 2017, adapted from Siegel et

al.288 .......................................................................................................................................... 38

Figure 6 The relationship between cancer and radiosensitivity .............................................. 40

Figure 7 The toxicity of radiotherapy ....................................................................................... 43

Figure 8 Forms of cell death in cancer or healthy cells triggered by irradiation ..................... 48

Figure 9 TPT1 in DNA repair modified from Zhang et al, 2012264 and elevated levels in A-T

LCLs ........................................................................................................................................... 53

Figure 10 Cellular mechanisms following irradiation-induced DNA damage .......................... 54

Figure 11 Structure of this project ........................................................................................... 55

Figure 12 P-value of overlap calculation in Ingenuity Pathway Analysis by Fisher’s Exact Test .................................................................................................................................................. 79

Figure 13 Knockdown of TPT1 does not influence ATM signaling by means of KAP1 (Ser824)

phosphorylation ....................................................................................................................... 85

Figure 14 No evidence for colocalization of TPT1 and γH2AX in ADP and MCF10A cells ........ 87

Figure 15 γH2AX foci numbers in TPT1 knockdown cells after irradiation .............................. 89

Figure 16 Workflow for characterization of individual radiosensitivity using patient material

.................................................................................................................................................. 90

Figure 17 GeneCards annotation of genes with truncating mutations in RS patients ............ 91

Figure 18 Comparative IPA analyses between RS cancer patients .......................................... 92

Figure 19 IPA upstream analysis results of RS patients ........................................................... 93

Figure 20 Overlapping genes of datasets for comparison between cancer patients .............. 95

Figure 21 Comparative IPA analyses between cancer patients ............................................... 96

Figure 22 Pathways of interest in comparison analyses of RS BC, BC and Fam BC patient

groups in IPA ............................................................................................................................. 97

Figure 23 Subcelluar view of genes associated with DNA repair sub-pathways by comparative

IPA analyses .............................................................................................................................. 98

Figure 24 Canonical pathways in comparative analyses of RS BC, BC and Fam BC groups ... 100

Figure 25 Comparative IPA analyses with single patients in RS BC, BC and Fam BC groups . 102

Figure 26 Comparison of annotation methods: DNA repair pathway ................................... 103

Figure 27 Comparison of annotation tools for DNA repair, cancer and immune system genes

................................................................................................................................................ 104

Figure 28 Immortalization of MC1, MC3 and MC7 primary fibroblasts with TERT................ 106

Figure 29 Mutations in DNA repair genes in RS BC patients MC1, MC3 and MC7 ................ 106

Figure 30 ATM targets CHEK2 and KAP1 after irradiation in RS BC TERT cells ...................... 108

Figure 31 γH2AX and 53BP1 foci kinetics in TERT immortalized RS BC cells after irradiation

................................................................................................................................................ 109

Figure 32 Colony survival of TERT immortalized MC1, MC3 and MC7 cells after irradiation

compared to BJ5TA ................................................................................................................ 111

9

Figure 33 Time course of colony formation assay in TERT immortalized MC1, MC3 and MC7

cells ......................................................................................................................................... 113

Figure 34 Pilot experiment to determine senescence after irradiation in TERT immortalized

RS BC cell lines ........................................................................................................................ 114

Figure 35 Irradiation-associated senescence in MC3 TERT cells compared to BJ5TA ........... 115

Figure 36 Network for genes that were identified or further characterized in this breast

cancer study ........................................................................................................................... 129

Figure 37 Proposed model of RS as consequence of DNA repair defects and senescence ... 142

Figure 38 Possible impact of HERC2, RAD51C and ABL1 mutations on RS related to ATM

signaling .................................................................................................................................. 144

Figure 39 Possible mechanism of DNA repair defects leading to radiosensitivity ................ 148

Figure 40 Early and late forms of cell death leading to failure of clonogenic survival after

irradiation ............................................................................................................................... 149

Figure 41 Conclusions and suggestions on follow-up studies ................................................ 151

Tables

Table 1 Examples of cancers treated with radiation therapy (modified from Baskar et al.275)

.................................................................................................................................................. 41

Table 2 Chromosome breakage and radiosensitivity syndroms .............................................. 44

Table 3 Cell lines used in this project as described in this thesis ............................................. 56

Table 4 Cell lines used in this project as previously published ................................................ 57

Table 5 Primary antibodies ....................................................................................................... 58

Table 6 Secondary antibodies .................................................................................................. 59

Table 7 Plasmids and kits ......................................................................................................... 59

Table 8 Chemicals ..................................................................................................................... 60

Table 9 Enzymes and siRNAs .................................................................................................... 62

Table 10 Medium and other materials used in this work ........................................................ 62

Table 11 Buffers and solutions prepared and used in this project .......................................... 63

Table 12 Devices and disposables ............................................................................................ 65

Table 13 Software used in this project ..................................................................................... 68

Table 14 Culture and cryopreservation conditions of cell cultures ......................................... 70

Table 15 Composition of western blot gels .............................................................................. 74

Table 16 Fluorescence microscopy devices and parameters ................................................... 76

Table 17 Microscope settings used for foci images ................................................................. 76

Table 18 PCR protocol for primer optimization and validation sequencing ............................ 82

Table 19 Cycling conditions for sequencing reaction .............................................................. 83

Table 20 P-values of senescence analysis in radiosensitive cell cultures after irradiation

compared to BJ5TA ................................................................................................................ 115

Table 21 P-values of senescence analysis in MC3 TERT cells compared to BJ5TA control .... 116

Table 22 Clinical data on RS BC patients showing variability of side-effect manifestation ... 124

Supplementary figures

Supplementary figure S-1 No alterations in TPT1 levels after IR in different cell systems and

no effect of TPT1 knockdown on p-CHEK2 Ser19 levels after IR ........................................... 201

Supplementary figure S-2 No changes in TPT1 levels after ATM inhibition and no chromatin

binding after IR ....................................................................................................................... 202

10

Supplementary figure S-3 No evidence for colocalization of TPT1 and γH2AX or decreased

γH2AX foci numbers after TPT1 knockdown .......................................................................... 203

Supplementary figure S-4 No evidence for nuclear translocation of TPT1 in ADP or

colocalization with γH2AX after IR in HCC1937 cells ............................................................. 204

Supplementary figure S-5 Immunostainings of TPT1 and RAD51 in BJ5TA and MC3 TERT cells

after irradiation ...................................................................................................................... 205

Supplementary figure S-6 Secondary antibody controls for immunostainings ..................... 206

Supplementary figure S-7 No changes in 53BP1 foci numbers after IR in TPT1 knockdown

cells compared to controls ..................................................................................................... 211

Supplementary figure S-8 Complete IPA core analysis results of all RS patients .................. 230

Supplementary figure S-9 Complete IPA core analysis results of RS BC patients .................. 231

Supplementary figure S-10 Complete IPA core analysis results of RS patients with other

cancers .................................................................................................................................... 232

Supplementary figure S-11 Complete IPA core analysis results of all Chemo RS patients .... 233

Supplementary figure S-12 Mechanistic networks found in RS patients by Ingenuity Pathway

Analysis ................................................................................................................................... 234

Supplementary figure S-13 Complete IPA core analysis results of BC patients ..................... 235

Supplementary figure S-14 Complete IPA core analysis results of Fam BC patients ............. 236

Supplementary figure S-15 IPA heatmaps of “Cancer” and “Organismal Injury and

Abnormalities” in RS patients ................................................................................................ 237

Supplementary figure S-16 “Neurological disease”, “Reproductive system disease” and “Dermatological diseases and conditions” IPA hits in RS patients ........................................ 238


Abnormalities” in RS BC patients ........................................................................................... 239


Abnormalities” in BC patients ................................................................................................ 240


Abnormalities” in Fam BC patients ........................................................................................ 241

Supplementary figure S-20 IPA heatmaps of “Reproductive system disease” and “Neurological Disease” in RS BC patients............................................................................... 242

Supplementary figure S-21 IPA heatmap of “Hereditary Disorder” in Fam BC patients ....... 242

Supplementary figure S-22 IPA comparison analyses between groups with unique genes .. 244

Supplementary figure S-23 Canonical pathways in comparative analyses of unique genes

from RS BC, BC and Fam BC groups........................................................................................ 245

Supplementary figure S-24 Predicted effects of the mutations in ABL1 and FANCL of patient

MC7 on protein sequence ...................................................................................................... 252

Supplementary figure S-25 Predicted effects of the mutations in RAD51C and RBBP6 of

patient MC3 on protein sequence or intronic ....................................................................... 253

Supplementary figure S-26 Predicted effects of the mutations in HERC2 of patient MC1 and

NPAT of patient MC7 on protein sequence or splice site ...................................................... 253

Supplementary figure S-27 RAD51 foci analysis in primary and immortalized RS cells ........ 254

Supplementary figure S-28 CSA in 6well plates with different coating ................................. 255

Supplementary figure S-29 No colony growth in 6-well plates and change of morphology of

MC3 TERT cells ....................................................................................................................... 256

Supplementary figure S-30 Senescence assay results analyzed by Mann-Whitney test and

fitted for exponential decay ................................................................................................... 257

Supplementary figure S-31 Comparison of aging genes with exome sequencing results of

cancer patients ....................................................................................................................... 258

11

Supplementary tables

Supplementary table S-1 Clinical data of radiosensitive patients and two matched pairs ... 200

Supplementary table S-2 Raw data of γH2AX foci after TPT1 knockdown and irradiation ... 207

Supplementary table S-3 Raw data of 53BP1 foci countings in ADP and MCF10A after TPT1

knockdown ............................................................................................................................. 211

Supplementary table S-4 Mutations that occurred in the same genes in more than one

patient .................................................................................................................................... 212

Supplementary table S-5 Identical mutations that occurred in at least two patients .......... 213

Supplementary table S-6 Mutations identified by exome sequencing and subjected to

validation sequencing............................................................................................................. 214

Supplementary table S-7 Mutations identified by exome sequencing that failed validation 221

Supplementary table S-8 Mutations identified by exome sequencing that were not subjected

to validation sequencing ........................................................................................................ 223

Supplementary table S-9 Genes identified in DNA replication, recombination and repair by

IPA........................................................................................................................................... 243

Supplementary table S-10 IPA definitions of DNA repair subpathways and underlying

references ............................................................................................................................... 243

Supplementary table S-11 Canonical pathway p-values of comparative IPA analysis .......... 246

Supplementary table S-12 Canonical pathway p-values of comparative IPA analysis after DNA

repair filtering ......................................................................................................................... 246

Supplementary table S-13 First 40 Hits of Diseases and Biofunctions p-values of comparative

IPA analyses after DNA repair filtering ................................................................................... 247

Supplementary table S-14 Comparison of annotation methods: cancer .............................. 248

Supplementary table S-15 Comparison of annotation methods: immune system ............... 249

Supplementary table S-16 P-values of densitometric analyses performed for results

discussed in 4.4.1 ................................................................................................................... 249

Supplementary table S-17 P-values of γH2AX foci corresponding to Figure 31 .................... 251

Supplementary table S-18 P-values of 53BP1 foci corresponding to Figure 31 .................... 252

Supplementary table S-19 Raw data pilot experiment senescence after irradiation ............ 256

Supplementary table S-20 Raw data senescence after irradiation in BJ5TA and MC3 TERT

cells ......................................................................................................................................... 256

12

List of abbreviations

Abbreviation Explanation

10H 10 µg/ml hygromycin B

5FU 5 Fluorouracil

9-1-1 Heterotrimeric complex

composed of RAD1, RAD9

and HUS1

A Adenine

AP Apurinic-apyrimidinic

ATCC American Type Culture

Collection

ATLD Ataxia-telangiectasia-like

disorder

ATM Ataxia Telangiectasia

Mutated

BC Breast cancer

BER Base excision repair

bp Base pair

BSA Bovine serum albumine

C Cytosine

CB Cajal body

CDK(s) Cyclin-dependent

kinase(s)

CFS Common fragile sites

cGy Centigray

cm² Square centimeter

CML Chronic myeloid

leukemia

CS Cockayne syndrome

CSA Colony survival assay

CT Computed tomography

CTCAE v3.0 Common Terminology

Criteria for Adverse

Effects version 3.0

DAPI Diamidino-2-

phenylindole

ddH2O Double-distilled water

ddNTP di-desoxyribonucleoside

triphosphates

DDR DNA damage response

DMEM Dulbecco's modified

Eagle‘s medium DMSO Dimethyl sulfoxide

DNA Deoxyribonucleic acid

dNTP desoxyribonucleoside

triphosphates

DSB Double-strand break


dsDNA Double-stranded DNA

DTT Dithiothreitol

e.g. exempli gratia

EBV Epstein–Barr virus

ECL Enhanced

chemiluminescence

EDTA Ethylenediaminetetraace

tate

EGTA Ethyleneglycoltetraacetat

e

FA Fanconi anemia

Fam Familial

Fam BC Familial breast cancer

FCS Fetal calf serum

FITC Fluorescein

isothiocyanate

g Gram

G Guanine

G1 Gap1

G2 Gap2

GFP Green fluorescent

protein

GGR Global genome repair

Gln L-glutamine

GWAS Genome-wide

association study

gy Gray

h Hour/hours

HCl Hydrochloric acid

HeLa (cells) Henrietta Lacks

HLA Human leukocyte antigen

(cluster)

HPLC High-performance liquid

chromatography

A-T Ataxia-telangiectasia

HR Homologous

recombination

ICC Immunocytochemistry

ICL Inter-strand crosslinks

IgG Immunoglobulin G

IPA Ingenuity Pathway

Analysis

IR Irradiation

KCl Potassium chloride

kDa Kilodalton

13


kg Kilogram

l Liter

LCL Lymphoblastoid cell line

LENT SOMA Late Effects Normal

Tissues: Subjective,

Objective, Management

and Analytic

M Mole

M (cell cycle) Mitosis

M1 Mortality stage 1

M2 Mortality stage 2

MAF Minor allele frequency

MC Mamma carcinoma

MEGM Mammary Epithelial Cell

Growth Medium

mg Milligram

mGy Milligray

min Minute/minutes

ml Milliliter

mm Millimeter

mM Millimole

MMC Mitomycin C

MMS Methyl-methane

sulfonate

MR Mismatch repair

MRN MRE11A-RAD50-NBN

MU Monitor unit

(radiotherapy)

MVX Energy of X-radiation

N Number of experiments

Na Sodium

NaCl Sodium chloride

NaF Sodium fluoride

NBS Nijmegen breakage

syndrome

NCI National Cancer Institute

NER Nucleotide excision

repair

NGS Normal goat serum

NHEJ Non-homologous end

joining

nm Nanometer

OMICS Biological studies ending

in omics, e.g. proteomics

OR Human olfactory cluster

P Phosphor

PAGE Polyacrylamide gel


electrophoresis

PBS Phosphate-buffered

saline

PCR Polymerase chain

reaction

PEG Polyethylene glycol

pen Penicillin

pH pondus Hydrogenii

(potential of hydrogen)

pmol Picomole

PMSF Phenylmethansulphanylfl

uoride

RAPADILINO Radial ray defect, both

patellae hypoplasia or

aplasia and cleft or highly

arched palate, diarrhea

and dislocated joints,

little size and limb

malformations, long,

slender nose and normal

intelligence

RIDDLE Radiosensitivity,

immunodeficiency,

dysmorphic features and

learning difficulties

RNA Ribonucleic acid

ROS Reactive oxygen species

rpm Rounds per minute

RPMI Roswell Park Memorial

Institute

RS Radiosensitivity/radiosen

sitive/radiation

sensitivity

RS BC Radiosensitivity, breast

cancer

Rs-number Reference SNP ID

number

RT Radiotherapy

RTOG Radiation Therapy

Oncology Group

S (phase) Synthesis (phase)

SASP Senescence-associated

secretory phenotype

SCC Squamous cell carcinoma

Scr Scrambled

SD Standard deviation

SDS Sodium dodecylsulfate

14


Ser serine

SIFT Sorting Intolerant From

Tolerant

siRNA Short interfering RNA

SNP Single-nucleotide

polymorphism

SSB Single-strand break

ssDNA Single-stranded DNA

Strep Streptomycin

SV40 Simian virus 40

T Thymine

TBE Tris/Borate/EDTA

TCR Transcription-coupled

repair

TDD Trichothiodystrophy

(group A)

TE Tris/EDTA

TEMED Tetramethylethylenedia

mine

TERT Telomerase Reverse

Transcriptase


Thr Threonine

TNBC (cell

lines)

Triple negative breast

cancer

TTD Trichothiodystrophy

U Units

U/ml Units per milliliter

UV Ultraviolet

V(D)J

(recombinatio

n)

variable (V), diversity (D)

joining (J), gene

segments.

v/v Volume per volume

w/v Weight per volume

WB Western blot

WT Wildtype

Xg Multiple of gravitational

acceleration

XP Xeroderma pigmentosum

β-Gal β-Galactosidase

γ IR Gamma irradiation

λ Wavelength (Lamda)

15

Publications and contributions

Journal article:

Pfeifer K, Schürmann P, Bogdanova N, Neuhäuser K, Kostovska IM, Plaseska-Karanfilska D, Park-Simon TW, Schindler D, Dörk T Frameshift variant FANCL*c.1096_1099dupATTA is not

associated with high breast cancer risk. Clinical Genetics 2016:n/a-n/a. doi:

10.1111/cge.12837.

Conference paper and oral presentation:

Neuhäuser K, Bogdanova N, Bhuju S, Geffers R, Christiansen H, Dörk T, Rave-Fränk M

Mutation in FANCO/RAD51C, but not FANCL, is Associated with Clinical and Chromosomal

Radiosensitivity. Experimentelle Strahlentherapie und Klinische Strahlenbiologie, 2016:31-37.

Conference paper and poster presentation:

Neuhäuser K, Bogdanova N, Borgmann K, Dahm-Daphi J, Schindler D, Christiansen H, Dörk T

Evidence for elevated basal levels of TPT1, but no induction after irradiation, in

lymphoblastoid cells from individuals with increased clinical radiosensitivity.

Experimentelle Strahlentherapie und Klinische Strahlenbiologie, 2017:24-30.

Bogdanova N, Jguburia N, Neuhäuser K, Wieland B, Stamm G, Wacker F, Christiansen H,

Dörk T Chromosomal radiosensitivity of breast epithelial cells and lymphocytes in repeated

diagnostic CT scans. International Wolfsberg Meeting on Molecular Radiation

Biology/Oncology, Ermatingen, Switzerland, 2017:36.

Manuscripts:

Neuhäuser K, Küper L, Bogdanova N, Willers M, Wieland B, Christiansen H, Dörk T.

Assessment of the role of TPT1 in ATM signaling and breast cancer susceptibility. Radiation

research (accepted with major revision requirements)


Dörk T. Chromosomal radiosensitivity of breast epithelial cells and lymphocytes in

repeated diagnostic CT scans. International Journal of Radiation Oncology* Biology* Physics

(in review)

16

Summary


Impact of the DNA damage response in clinical and cellular radiosensitivity of cancer patients

Adverse effects of radiotherapy occur in 5–10 % of cancer patients ranging from acute

effects like skin burns and inflammation to late effects of vascular tissue damage or

infertility. These reactions are not predictable at present which limits effective treatment of

non-responders due to uniform application of insufficiently low doses. The aim of this thesis

was to investigate genetic and cellular mechanisms underlying normal tissue toxicity. Three

different objectives were followed in order to identify biomarkers of radiation sensitivity

(RS), which all focused on the role of the DNA damage response.

Firstly, the impact of the translationally controlled tumor protein 1 (TPT1), a new player in

DNA repair, on Ataxia-Telangiectasia mutated (ATM) signaling was investigated in breast

epithelial cells (MCF10A) and SV40 immortalized human fibroblasts (ADP). Silencing of TPT1

had no significant effect on early ATM signaling 30 min after irradiation (IR) by

phosphorylation of CHEK2 (Ser19) and KAP1 (Ser824) as investigated by western blot (WB).

Consistently, no nuclear translocation of TPT1 or foci formation of TPT1 after IR was

observed in several cell lines by immunocytochemistry (ICC) or cellular fractionization.

Moreover, ATM inhibition prior to IR neither affected the TPT1 level nor the intracellular

distribution of TPT1 and no significant colocalization of TPT1 with γH2AX foci or chromatin

binding after IR was observed. The formation and resolution of γH2AX and 53BP1 foci after

IR revealed little differences after TPT1 silencing, although ADP, but not MCF10A, cells

showed a marginally significant effect of TPT1 on residual γH2AX foci numbers at 24 h after

IR. Altogether, TPT1 does not play an essential role in the recognition and repair of radiation-

induced chromosome breaks and therefore was not further considered as RS biomarker

candidate in the context of the DNA damage response.

Secondly, unraveling the genetic fingerprint of RS cancer patients was addressed by exome

sequencing. 19 patients with adverse reactions, a majority graded 3 by RTOG (Radiation

Therapy Oncology Group) classification, and two BC control patients were analyzed and

results filtered for genes with truncating mutations. 587 genes were identified and subjected

to annotation by GeneCards, Ingenuity Pathway Analysis (IPA) and Reactome browser.

Remarkable inter-individual variability regarding assignment to functional categories was

detected. Findings included enrichment of DNA repair, cancer and immune system-related

genes. Prioritization of candidates for validation sequencing was performed on the basis of

classification to either of these pathways and with regard to genes involved in cell cycle, cell

death and skin diseases. 223 out of 315 mutations could be validated and 70 constituted

false positives. After removal of the latter genes from the dataset, comparative IPA analyses

were performed between truncating mutations in 11 RS BC, 11 BC and 11 Fam (familial) BC

patients. Strikingly, the RS BC group was strongly associated with cancer and with DNA

damage response pathways, closely followed by Fam BC patients. This pointed to an

enrichment of germline DNA repair gene mutations in radiosensitive BC patients.

The third part of this project comprised generation of four TERT immortalized cell lines from

primary skin fibroblasts of RS BC patients and two matched non-RS pairs. Establishment of

immortalized cell lines was successful for RS BC patients MC (mamma carcinoma) 1, MC3

and MC7, who all suffered from severe side-effects affecting different parts of the body

(RTOG 3). Heterozygosity for mutations in either HERC2 in MC1, RAD51C in MC3 or FANCL

17

and ABL1 in MC7 could be confirmed by sanger sequencing in these cells. Functional

consequences on ATM signaling were analyzed by p-CHEK2 (Ser19) and p-KAP1 (Ser824)

formation by immunoblotting, and γH2AX, 53BP1 and RAD51 (RAD51 Recombinase) foci

formation by ICC. By WB, ABL1 levels were shown to be reduced by approximately 50 % in

MC7 cells compared to the wildtype TERT immortalized control BJ5TA. Early ATM signaling

as assessed by p-CHEK2 (Ser19) and p-KAP1 (Ser824) 30 min after 1.5 and 6 Gy IR was

functional in all cultures despite subtle differences. Consistently, repair kinetics as assessed

by γH2AX and 53BP1 foci formation 1 h, 6 h, 24 h and 48 h were clearly detectable in all

cultures. MC1 TERT showed a delay in resolution of foci between 6 h and 24 h, which may be

attributed to impaired HERC2 function. MC3 and MC7 cells showed strong reduction of foci

levels already after 24 h- and almost no residual foci after 48 h. Prominent impair of RAD51

foci formation was observed only in primary (MC3) and immortalized (MC7) cells and not in

MC1 TERT cells, indicating differential effects of the mutational background of these cells on

DNA repair through homologous recombination. To address the cellular survival capacity in

the TERT immortalized RS BC patient cells, the colony survival assay (CSA, or clonogenic

assay) was performed after IR ranging from 2– 8 Gy. Results after 4 Gy are presented here

and indicate strong impairment of clonogenic survival after IR in all RS cultures compared to

the control, however, especially in MC3 and MC7 cells. In the latter cell lines, hardly any

colony formation could be observed. Microscopic inspection of these cells indicated

development of a senescence phenotype after IR. In order to determine IR-associated

senescence, cells were counted according to senescence-associated β-galactosidase staining

after 4 Gy of IR. Senescence without and after IR was detected in all cultures including the

control but normalization to background levels in unirradiated cells revealed significant

differences at 7 d after IR only in MC3 TERT and MC7 TERT compared to the control,

respectively. As MC3 TERT showed the steepest decline in non-senescent cells already at

24 h after IR, this cell line was chosen for further experiments. Comparison between MC3

TERT and BJ5TA showed significant development of IR-associated senescence in the RAD51C

carrier. These results suggest a possible mechanism of induction of RS involving defective

DNA repair that leads to accumulation of lesions in cells followed by initiation of senescence,

which finally may account for immunological implications in RS cancer patients.

18

Zusammenfassung


Impact of the DNA damage response in clinical and cellular radiosensitivity of cancer patients

Bei 5-10 % der Krebspatienten treten bei der Strahlentherapie Nebenwirkungen auf, die

akute Effekte wie Hautverbrennungen und Entzündungen und/oder Spätfolgen wie

beispielsweise Gefäßgewebeschäden oder Unfruchtbarkeit verursachen. Diese Reaktionen

sind derzeit nicht vorhersehbar, was die wirksame Behandlung der übrigen nicht betroffenen

Patienten aufgrund generalisierter Anwendung unzureichender Dosen limitiert. Das Ziel

dieser Arbeit war die Untersuchung von genetischen und zellulären Mechanismen der

Normalgewebstoxizität strahlensensitiver Krebspatienten. Drei Ansätze wurden verfolgt, um

die Rolle der DNA-Reparatur in der Strahlentoxizität im Hinblick auf mögliche Biomarker zu

erforschen.

Zunächst wurde der Einfluss des neuen DNA-Reparatur Kandidaten TPT1 auf das ATM-

Signaling in Brustepithelzellen (MCF10A) und SV40-immortalisierten humanen Fibroblasten

(ADP) untersucht. Das Silencing von TPT1 hatte keinen signifikanten Effekt auf die frühe ATM

Signaltransduktion 30 Minuten nach der Bestrahlung, was durch Western Blot

Untersuchungen der Phosphorylierung von CHEK2 (Ser19) und KAP1 (Ser824) bestätigt

wurde. Zudem wurde nach Bestrahlung mehrerer Zelllinien weder eine nukleäre

Translokation von TPT1, noch eine Foci-Bildung durch Immunzytochemie (ICC) oder zelluläre

Fraktionierung beobachtet. Darüber hinaus beeinflusste eine ATM-Inhibition vor der

Bestrahlung weder das TPT1-Level, noch die intrazelluläre Verteilung von TPT1. Weiterhin

wurde keine signifikante Kolokalisation von TPT1 mit γH2AX-Foci oder Chromatinbindung

nach Bestrahlung beobachtet. Das TPT1-Silencing zeigte kaum Auswirkungen auf die Bildung

und Auflösung von γH2AX- und 53BP1-Foci nach Bestrahlung, es wurde jedoch ein

marginaler Effekt auf γH2AX 24 h nach Bestrahlung in ADP Zellen beobachtet. Insgesamt

scheint TPT1 keine wesentliche Rolle bei der Erkennung und Reparatur von

strahlungsinduzierten Chromosomenbrüchen zu spielen und wurde daher im

Zusammenhang mit der DNA-Schadensreaktion nicht als Biomarker-Kandidat für

Stahlensensibilität betrachtet.

Ein zweites Ziel der Arbeit war die Analyse von möglichen Mutationen, welche die

Stahlensensibilität verursachen könnten, durch Exom-Sequenzierung. 19 Patienten mit

Nebenwirkungen, die zum großen Teil als RTOG (Radiation Therapy Oncology Group) Grad 3

klassifiziert wurden, sowie zwei Brustkrebs-Kontrollpatienten wurden analysiert. Es wurde

nach proteinverkürzenden Mutationen gefiltert, was zu 587 identifizierten Genen führte, die

durch GeneCards, Ingenuity Pathway Analysis (IPA) und den Reactome Browser annotiert

wurden. Es wurde eine große Variabilität zwischen individuellen Exomen bezüglich der

Zuordnung der Gene zu funktionalen Kategorien festgestellt. Die Ergebnisse zeigten eine

Anreicherung von Genen, die bekanntermaßen eine Rolle in der DNA-Reparatur und/oder

der Krebsentstehung aufweisen oder in Zusammenhang mit dem Immunsystem stehen. Die

Priorisierung von Kandidaten für die Validierungssequenzierung wurde auf der Grundlage

der Zuordnung zu einem dieser Pathways und im Hinblick auf Gene durchgeführt, die an

Zellzyklus, Zelltod, oder Hauterkrankungen beteiligt sind. 223 von 315 Mutationen konnten

bestätigt werden, für 22 Mutationen gelang kein adäquates Primerdesign und 70

Mutationen stellten sich als falsch-positive Treffer heraus. Nach der Entfernung der letzteren

Gene aus dem Datensatz wurden vergleichende IPA-Analysen zwischen trunkierenden

19

Mutationen von 11 RS-Brustkrebs (breast cancer, BC), 11 BC und 11 Fam (familiärer) BC-

Patienten durchgeführt. Auffallend war, dass die RS BC-Gruppe besonders stark mit Krebs-

und DNA-Schadensreaktionswegen assoziiert war, dicht gefolgt von Fam BC-Patienten.

Der dritte Teil dieses Projekts umfasste die Erzeugung von vier TERT immortalisierten

Zelllinien aus primären Hautfibroblasten von RS-BC-Patienten und zwei in Krankheitsbild und

Alter vergleichbaren Brustkrebspatienten. Die Etablierung von immortalisierten Zelllinien

war erfolgreich für die RS-BC-Patienten MC (Mamma Carcinom) 1, MC3 und MC7, die alle an

schweren Nebenwirkungen in verschiedenen Körperregionen litten (RTOG 3). Heterozygotie

für Mutationen in entweder HERC2 in MC1, RAD51C in MC3 oder FANCL sowie ABL1 in MC7

konnte durch Sanger-Sequenzierung bestätigt werden. Funktionelle Auswirkungen auf den

ATM-Signalweg wurden durch Bildung von p-CHEK2 (Ser19) und p-KAP1 (Ser824) über

Immunoblots und Bildung von RAD51, γH2AX und 53BP1 Foci mittels Immunzytochemie analysiert. Durch Western Blot wurde gezeigt, dass das ABL1-Proteinniveau in den

heterozygoten MC7-Zellen im Vergleich mit den Wildtyp-TERT immortalisierten

Kontrollzellen BJ5TA um etwa 50 % reduziert vorlag. Die frühe ATM-Signaltransduktion, die

durch p-CHEK2 (Ser19) und p-KAP1 (Ser824) 30 min nach Bestrahlung mit 1.5 und 6 Gy

bestimmt wurde, war trotz subtiler Unterschiede in allen Kulturen funktional. Entsprechend

war die Reparaturkinetik, wie sie durch γH2AX- und 53BP1-Foci-Bildung nach 1 h, 6 h, 24 h

und 48 h bestimmt wurde, in allen Kulturen eindeutig nachweisbar. MC1 TERT zeigte eine

verzögerte Foci-Auflösung zwischen 6 und 24 h, was auf eine beeinträchtigte HERC2-

Funktion zurückgeführt werden könnte. MC3- und MC7-Zellen zeigten bereits nach 24 h eine

starke Reduktion der Foci-Werte, und wiesen nach 48 h kaum noch nachweisbare Foci auf.

Eine ausgeprägte Beeinträchtigung der RAD51-Foci-Bildung wurde nur in primären MC3 und

immortalisierten MC7 Zellen, nicht aber in MC1-TERT-Zellen, beobachtet, was auf

unterschiedliche Effekte des Mutationshintergrunds dieser Zellen auf die DNA-Reparatur

hindeutet. Um die zelluläre Überlebensfähigkeit in den TERT immortalisierten RS-BC-

Patientenzellen zu untersuchen, wurde der Colony Survival Assay (CSA, clonogenic assay)

nach einer Bestrahlung mit 2–8 Gy durchgeführt. Die Ergebnisse der Bestrahlung mit 4 Gy

werden hier präsentiert. Sie weisen eine starke Beeinträchtigung des klonogenen

Überlebens nach Bestrahlung in allen RS-Kulturen im Vergleich zur Kontrolle auf.

Insbesondere die MC7 TERT Fibroblasten stachen hierbei hervor, da sie nach Bestrahlung

keinerlei Koloniebildung aufwiesen. Sehr ähnliche Beeinträchtigung zeigte auch die MC3

TERT. Durch mikroskopische Untersuchung der Zellen zeigte sich ein hoher Anteil von sehr

großen Zellen, die starke Granulierung aufwiesen und Ähnlichkeiten zu seneszenten Zellen

zeigten. Um die strahlenassoziierte Seneszenz zu bestimmen, wurden die Zellen gemäß der

mit Seneszenz assoziierten β-Galactosidase-Färbung nach Bestrahlung mit 4 Gy ausgezählt.

Seneszenz wurde in allen Kulturen mit und ohne Bestrahlung, einschließlich der Kontrolle,

nachgewiesen. Nach Normalisierung auf Hintergrundwerte in unbestrahlten Zellen zeigten

sich 7 Tage nach Bestrahlung signifikante Unterschiede in den MC3-TERT- und MC7-TERT

Zellen im Vergleich zur Kontrolle. Da MC3-TERT bereits 24 Stunden nach Bestrahlung den

stärksten Abfall in nicht-seneszenten Zellen zeigte, wurde diese Zelllinie für weitere

Experimente ausgewählt. Ein Vergleich zwischen MC3-TERT und BJ5TA zeigte eine

signifikante Entwicklung von IR-assoziierter Seneszenz in den Zellen der RAD51C-

Mutationsträgerin. Diese Ergebnisse lassen einen möglichen Mechanismus der Induktion von

Strahlensensibilität mittels defekter DNA-Reparatur vermuten, die zur Akkumulation von

Läsionen in Zellen führen könnte, gefolgt von Seneszenz, die letztendlich immunologische

Implikationen bei strahlensensiblen Krebspatienten auslösen könnte.

20

1 Introduction part 1: The DNA damage response

1.1 Forms of DNA lesions and repair pathways

The survival of organisms is dependent on the correct transmission of intact genetic material

from one cell to its offspring. Lesions of the genome by DNA damage can occur at various

points of the life cycles of cells in the body, and organisms have developed several defense

mechanisms to ensure the integrity of the genetic information, collectively termed the DNA

damage response (DDR). An interactive network of repair pathways, which share several

components, has evolved, and is initiated upon DNA damage by various exogenous and

endogenous sources. Such can be physiological stress, failure of enzymatic reactions,

replication errors and free radical species as by-product of metabolism or ionizing radiation,

chemical compounds, cigarette smoke, alcohol consumption, UV light and several more1-4.

Estimations have been made that every cell can undergo 105 spontaneous DNA lesions in

one day5. Upon sensing of the damage, the decision needs to be made whether the repair

machinery is capable of managing the insult, or else, cell death must be initiated to ensure

protection of the surrounding cells and the lineage by elimination of the damaged cell. If this

fails and damaged cells manage to escape the repair processes, various disorders and tumor

development can be the consequence2 6. Defects in surveillance and repair of the genome

can contribute to progression, appearance as well as heterogeneity of cancer7.

The DDR is also involved in several other processes like DNA replication, chromatin folding

and packing, regulation of the epigenetic environment, gene expression, protein synthesis

and immune system2 8. As several cancers are associated with defects in the DDR, they are

dependent on the remaining repair functions for survival and provide a well established

target in cancer therapy9. It is crucial that proper interaction of the DDR components with

the cell-cycle-checkpoint and chromosome-segregation machinery is guaranteed, to allow

DNA repair prior to mitosis in order to prevent the spreading of the damaged genetic

material to the daughter cells10. As the DNA damage response is a very complex mechanism

that involves hundreds of proteins, an overview of different forms of DNA lesions, the

subsequently initiated repair mechanisms and some of the major proteins involved in these

processes is given in Figure 1. Gene products that will be of further interest in this project

are shown in crosstalk with other components of the DDR and will be introduced in this

chapter.

22

homologous end joining (NHEJ) and homologous recombination (HR) will be discussed in this

section.

Base-excision repair (BER) belongs to the frequently utilized pathways, which are specialized

for dealing with smaller lesions arising from endogenous stress, while nucleotide excision

repair (NER) corrects helix-distorting damage that can arise from environmental mutagens14

15. Reactive cellular catabolites can endogenously create miscoding alkylation lesions, which

can be rapidly and efficiently removed by methyltransferases in a direct reversal action16-19.

If the cell faces a DNA lesion that blocks the replication machinery, a bypass through

specialized DNA polymerases can be initiated in an emergency situation15. Intra-strand

crosslinks can successfully be bypassed during replication, while inter-strand crosslinks (ICLs)

present a greater threat to the integrity of the genome as they prevent DNA strand

separation during transcription and replication and need to be corrected by homologous

recombination (HR) repair and the Fanconi Anemia (FA) pathway20 (section 1.4). ICLs can

form during endogenous release of metabolic by-products or arise from exogenous agents

like UV irradiation (IR) or cancer drugs like cisplatin and mitomycin C21. Convergence of

replication forks at the localization of ICLs initiates repair that operates during replication in

the S (synthesis) phase of the cell cycle22. Stalled replication forks are temporarily arrested

but can resume replication (termed replication fork restart) once the repair has been

successfully executed, for example by RAD51-dependent homologous recombination

repair23 (subsection 1.1.2). A collapsed replication fork, however, is inactivated in the course

of dissociation of the replication machinery and can account for genome rearrangements if it

cannot be stabilized or persists over a longer time period3.

1.1.1 DNA single-strand break repair of replication-associated DNA damage

DNA is particularly vulnerable during replication and transcription processes, especially

through attack by reactive oxygen species (ROS). These can be endogenously created during

immunological responses, as byproducts of metabolism especially in the course of cellular

respiration or by exogenous agents such as chemicals or IR. ROS can cause oxidized bases,

abasic or apurinic-apyrimidinic (AP) sites and single-strand breaks. It is estimated that over

105 base lesions are caused by endogenous ROS in an aerobic cell genome per day3.

Unwinding of the duplex genome to create transient single-stranded DNA renders it

particularly sensitive to the formation of oxidized bases, which could lead to mispairings and

subsequently to cancer-causing mutations if replication proceeds. Furthermore, bulky

adducts, which stall replicative polymerases, can lead either to repair or fork collapse24. It is

vital that replication is restarted each time after it encounters an impairment of replication

fork progression, to ensure physiological cell functions and complete reproduction.

Different options to repair replication-associated DNA damage have evolved, either in the

template strand or in a post-replication repair mechanism in the progeny strand. The

majority of mutagenic base lesions are repaired in a pre-replicative manner through base-

excision repair-initiating enzymes.

1.1.1.1 Base excision repair and mismatch repair pathways

Loss of a whole base due to cleavage of the N-glycosidic bond between the phosphate-sugar-

backbone and the nucleotide creates an AP site which initiates the base excision repair

pathway (BER)25. This repair mechanism removes toxic and non-bulky base lesions and

strand breaks from genomic and mitochondrial DNA14 and is basically mediated by an

23

enzyme complex containing DNA polymerase β (POLB) and DNA ligase I (LIG1)25. BER is

triggered by DNA glycosylases and AP lyases, that hydrolytically cleave the base-deoxyribose

glycosyl bond of the affected nucleotide, for example Endonuclease VIII-like 1 (NEIL1) or

Thymine DNA Glycosylase (TDG). NEIL1 is involved in replication-associated repair of

oxidized bases during the S-phase (synthesis) of the cell cycle, has a preference for oxidized

pyrimidines, and removes the altered bases through its AP lyase activity26. It binds to the

single-stranded DNA to mediate fork regression and acts as hub protein by interacting with

distal repair proteins presumably to enhance efficiency of damaged-base recognition and

repair24. These encompass DNA ligases or the heterotrimeric 9-1-1 complex composed of

RAD1, RAD9 and HUS1.

An important post-replication DNA repair mechanism that is implicated in several cancers is

mismatch repair (MR), which operates to compensate dNTP-misincorporations. These can

result from escaping the proofreading machinery during DNA replication and will eventually

be interpreted as DNA lesions10 27. Furthermore, “insertion and deletion” loops, which might

form during replication and recombination of DNA, are corrected by MR10 27. This form of DNA

repair mechanism is capable of initiating cell cycle arrest as well as apoptosis in case of

intensive damage and has been proposed as general DNA damage sensor due to its broad

recognition and repair capacity of diverse base pair anomalies, including conventional

mismatches28-30. Key players are MutL homolog 1 (MLH1) and MutS homolog 2 (MSH2)

which are involved in the recognition of the mismatch together with several other proteins

including MutS Homolog 6 (MSH6), followed by nicking to enable the removal of the

mispaired nucleotide. Excision of the nicked strand by exonucleases, resynthesis and ligation

of the corrected stretch of DNA are subsequently performed to complete repair31.

Given that excision could start either at the 5’ or 3’ terminus, depending on the localization

of the base that needs to be exchanged, exonucleases with different polarities were

identified. One of the major exonucleases in mammalian cells is the MSH2 interactor EXO1

(Exonuclease 1), which possesses 5'→3' dsDNA exonuclease activity as well as an RNase H

activity32 33. MRE11A has been described as 3′→5′ direction exonuclease34, whereas the

ssDNA-specific exonuclease EXO5 (Exonuclease 5) is bidirectional with a strong preference

for 5’-ends. Its directionality is enforced by the hub protein complex RPA (Replication protein

A), which binds and stabilizes ssDNA intermediates and is important for nucleotide excision

and double-strand break repair (subsection 1.1.2) in addition to BER35 36. EXO5 has been

associated with resolution of stalled DNA replication forks and defects in this gene result in

increase of DNA damage in the form of ICLs, spontaneous and damage-induced chromosome

abnormalities36.

MR and BER share some components, for example NEIL1 and TDG. In addition to BER, NEIL1

functions in MR by correcting mismatched uracil and thymine pairings and, in contrast to

TDG, exhibits a broad substrate specificity24. TDG can correct G-T mispairings which can be

generated by deamination of 5-methylcysteine37, and initiates BER through removing

thymine from guanine-thymine mispairs. This results in an AP site that can subsequently be

targeted by AP endonucleases, and refilled by DNA polymerases and ligases to restore the

original guanine-cytosine interaction according to Watson-Crick base pairing10 38 39. Through

its interplay with Tet-(ten eleven translocation) proteins, TDG also functions in active DNA

demethylation of cytosine residues, an important form of epigenetic regulation by

transcriptional activation of silenced genes40-43. Moreover, TDG lacks glycosylase activity

24

towards the prevalent cytosine modification 5-methylcytosine44 45, which is oxidized by Tet-

proteins like the tumor suppressor TET2. This results in formation of 5-carboxylcytosine,

which can be used as substrate by TDG leading to BER42 46.

1.1.1.2 Nucleotide-excision repair

Helix-distorting DNA lesions such as pyrimidine dimers and photoproducts caused by UV

light, demand repair by removing the whole nucleotide, not only the base, and are

recognized by the nucleotide excision repair pathway (NER). It consists of several elements,

including the Xeroderma pigmentosum (XP) family proteins A-G and V, which are associated

with severe cutaneous implications including a dramatically increased risk of skin cancer, the

Cockayne syndrome (CS) proteins A and B as well as trichothiodystrophy (TTD) group A47.

NER can be divided into two sub-pathways and is initiated at stalled replication forks, but

can also be coupled to transcription and proceed genome-wide, resolving a wide spectrum

of damage48 49. The NER sub-pathways global genome repair (GGR) and transcription-

coupled repair (TCR) are initiated by unique damage recognition systems but share some

common core factors of NER49. XPC (Xeroderma pigmentosum, Complementation Group C) is

important in the early steps of GGR and damage sensing, binds to the undamaged

complementary strand and mediates repair complex formation50-53.

Moreover, XPC is able to stimulate the activity of TDG, providing a connection with BER

initiation54 and is associated with MMS19 via the core-TFIIH basal transcription factor

complex55 56 that has been shown to be implicated in chemotherapy response57. The core

reaction of both NER sub-pathways involves excision of the fragment containing the

photoproduct exclusively on the damaged strand and using the intact sister strand as

template for resynthesis by the DNA polymerase and ligase network. While GGR covers the

damage in the entire genome, TCR proceeds much faster as only the actively transcribed

regions of the genome are repaired58-60. It has been shown that this form of DNA repair is

subject to regulation by the COP9 signalosome (CSN) complex which plays a key role in

degradation of its components by ubiquitination60. Furthermore, several regulatory proteins

have been identified that serve as scaffolds or are involved in maturation of repair key

components. MMS19, for example, provides iron-sulfur cluster insertion into apoproteins via

the cytosolic iron-sulfur protein assembly (CIA) machinery61.

BER, MR and NER all rely on the same repair protocol, in which the damage is sensed by poly

(ADP-ribose) polymerases (PARP) 1 and 2 that associate to single-strand lesions62-64.

Subsequently, a signal transduction cascade that hydrolytically removes the affected base or

nucleotide is initiated. Afterwards, the complementary sequence is restored via the single-

strand template and DNA ends are ligated together65. More challenging and unusual forms

of DNA damage such as distortions of the sugar-phosphate backbone can only be repaired

by a complex network of proteins, involving cell cycle control and a strong signal

transduction and amplification capability.

1.1.2 DNA double-strand break repair

While all forms of DNA lesions can be a potential threat to the cell, DNA double-strand

breaks are considered the most harmful, as only one DSB is sufficient to result in persistent

growth arrest by senescence or even cell death if left unrepaired10. Further consequences

can be chromosomal aberrations in the form of translocations and deletions, which can

trigger loss of heterozygozity and promote carcinogenesis through genomic instability66. It is

25

believed that the ratio in which double- and single-strand breaks are created, for example by

free radical species, determines the cell fate67 68. The molecular mechanisms of dealing with

the highly toxic DSBs are homologous recombination69 (HR) and non-homologous end joining

(NHEJ).

1.1.2.1 Non-homologous end joining repair

NHEJ presumably is the most important form of DSB repair in humans, as it operates

throughout the cell cycle and does not rely on a template to restore the original base-

pairing10 70 71. It simply religates the ends of a DSB in a “quick-and-dirty” manner, which is

highly flexible and can readily safe the cell from consequences of the DSB on the one hand,

but can lead to mutations itself on the other hand10. Defects in NHEJ render cells sensitive to

ionizing radiation (IR) and result in immunological defects, as this pathway also operates at

physiological DSBs resulting from V(D)J recombination and immunoglobulin class switch

recombination in the context of antigen diversity promotion4 70.

Furthermore, failures of nuclear enzymes of lymphoid cells are associated with about half of

the chromosomal translocations that account for human lymphomas4. NHEJ has a

remarkable variety of substrates that it can accept to produce joined products. The Ku-

Proteins, which constitute the DNA-binding subunit of the DNA-Dependent Protein Kinase

(DNA-PK), directly bind the two DNA ends at the DSB and provide a scaffold for nucleases,

polymerases and ligases that can be recruited in a flexible order4. One of the interactors of

the DNA-PK complex is the NIMA (Never In Mitosis Gene A)-Related Kinase 4 (NEK4), which

plays a role in recruitment of the complex to DNA DSBs, in activation of TP53 (Tumor Protein

P53), cell cycle arrest and phosphorylation of H2AX (Histone H2AX)72. Although H2AX is

phosphorylated at S139 by several kinases, including ATM (ATM Serine/Threonine Kinase)

and ATR (ATR Serine/Threonine Kinase), see section 1.3, DNA-PK has been shown to be the

major kinase in charge of activation of H2AX in the DNA DSB repair and cell cycle context73.

The Artemis DNA-PKcs complex is the enzymatic core of DNA-PK, has a range of nuclease

activities, and is capable of cutting a variety of DNA overhangs. The polymerase lambda

(POLλ) is more flexible than replicative polymerases4. DNA ligase IV also inhabits outstanding

flexibility by the ability to ligate ssDNA and proceed across gaps and incompatible DNA ends.

This demonstrates the versatility of several components involved in the NHEJ response to

DSBs.

1.1.2.2 Homologous recombination repair

In contrast to the error-prone NHEJ, which is activated by DNA-PK, HR is a high fidelity

mechanism with low mutation rate. It mainly operates during the S and G2 (Gap2) phases of

the cell cycle as it requires the presence of a DNA template to restore the DNA in its original

base sequence11. HR is utilized in repair of DNA as well as collapsed replication forks and

mainly triggered by the apical kinases ATM (ATM Serine/Threonine Kinase) and ATR (ATR

Serine/Threonine Kinase). However, crosstalk between DNA-PK, ATR and ATM has been

reported to facilitate HR74 75. Upon DSB induction, the MRN complex assembles CTBP-

interacting protein (CtIP) and BRCA1/PALB2/BRCA2 to initiate HR. In parallel, it serves as

origin of downstream signaling events and recruits ATM76.

HR is conceptually divided into three stages known as presynapsis, followed by synapsis and

postsynapsis77. ATM triggers resection of the nucleotides adjacent to the break by

stimulating the nucleolytic activity of exonucleases like CtIP, MRE11A or EXD278, which

26

generate 3′-ssDNA overhangs, that are extended by nucleases in cooperation with the

Bloom's syndrome helicase BLM (Bloom Syndrome RecQ Like Helicase)77 79. The Werner

syndrome protein WRN (Werner Syndrome RecQ Like Helicase) is a homologue of BLM and is

associated with ATM, MRE11A, RAD50, EXO1 and the DNA-PK subunits KU70/80. It

possesses helicase as well as 3'5' DNA exonuclease activity and is believed to repair stalled

or collapsed replication forks80-88. Resection is terminated by the translocase activity of DNA

Helicase B (HELB) which inhibits the activity of exonucleases upon S-phase entry and

stimulates RAD51-mediated heteroduplex extension in 5'-3' direction75 89. During the

presynapsis phase, the ssDNA-binding protein RPA coats the DNA strand and is subsequently

exchanged by RAD51, which forms nucleoprotein filaments. It is believed that BRCA2 is

involved is mediating this step together with other proteins90. The RAD51 nucleofilaments

are essential for homology search and strand exchange, which are subsequently performed

during synapsis91 and RAD51 association with ssDNA likely reflects nuclear RAD51 foci76.

RAD51 dissociates in the course of postsynapsis, and the homologous sister chromatid is

used as reference for insertion of the missing nucleotides into the break and completion of

repair77 92 93. The RAD51-binding protein fidgetin-like 1 (FIGNL1) also interacts with the

RAD51 recombinase and plays an important role in HR, as evidence that it can associate to

DNA lesions independently of BRCA2 or the RAD51 paralogs like RAD51C, has been

reported76.

The severity of DNA lesions in the form of DSBs requires the collective action of proteins

which sense the damage, initiate cell cycle arrest and finally repair the DNA. HR is initiated

upon degradation of the 5’-DNA strand of the DSB and a complex interplay of DNA damage

sensors like the MRE11A-RAD50-NBN (MRN) complex, the 9-1-1 complex and apical kinases

like ATM and ATR follows. Subsequently, several downstream mediators like 53BP1, γH2AX

and BRCA1, kinases like CHEK2 and CHEK1, and effectors like TP53 or CDC25 that can

determine cell fate like apoptosis, checkpoint arrest or DNA repair, are activated94. The

complex interplay of these factors will be further discussed in the following subsections.

1.2 The cell cycle and checkpoint control

As described in the previous subsections, cells are under continuous threat by endogenous

and exogenous agents that cause DNA damage. In order to be able to fully replicate, a cell

needs to sophistically undergo cell cycle progression. In order to allow completion of the cell

cycle, a series of surveillance pathways have evolved, which are called cell cycle

checkpoints95 and allow suspension of the whole process until the prerequisites for reaching

the next phase are fully given. Major players in checkpoint control, cell cycle progression and

cell death are the inhibitors and activators of cyclin-dependent kinases (CDKs), the E2F-

family of transcription factors and the retinoblastoma tumor suppressor (RB). RB prevents

unscheduled cell cycle entry and is implicated in several sporadic cancers96. It is suggested

that a majority of human cancer cells miss the proliferation-associated regulatory functions

of RB, have lost G1 (Gap 1) checkpoint control and show differential response to wide-

ranging therapeutic agents, making this protein an important factor in cancer treatment96-98.

Stimulation by mitogens activates CDK-cyclin complexes that attenuate the suspending

effects of RB by phosphorylation98. It can be reactivated by phosphatases until completion of

mitosis or in response to cellular stress like DNA lesions that induce cell cycle arrest99,100. The

normal cell cycle progress includes 4 cell cycle phases and at least 3 cell cycle checkpoints, as

schematically depicted in Figure 2. The G1 phase is characterized by bridging the time

between nuclear division and DNA synthesis101, during which the cell prepares for DNA

27

duplication in the next cell cycle phase. If the DNA is intact and the environment is

favourable, as determined by the G1/S checkpoint, the cell can enter S phase. During S

phase, the synthesis of DNA is accomplished102, followed by preparation for mitosis in the

subsequent G2 phase. Entry into mitosis is prevented by the G2/M checkpoint if DNA

replication has not been properly performed. Mitosis can only be completed if chromosomes

are correctly attached to the mitotic spindle, which is supervised by the metaphase

checkpoint103. Progression through G1 and G2 phases is only possible if the DNA has not

been damaged; otherwise the cell cycle checkpoint executers need to coordinate cell cycle

progression with DNA repair95. ATM and ATR are two of the major checkpoint kinases in

mammalian cells and manage a series of signal transduction events. Whether ATM or ATR

are activated in the course of cell cycle control depends on the nature of the DNA damage,

however, signal transduction pathways converge in TP53 induction and catalytic inhibition of

CDC25 phosphatase95. The precise functions of ATM and ATR in checkpoint signaling will be

discussed in section 1.3.

The tumor suppressor BRCA1 is targeted by ATM and CHEK2 after ionizing radiation and

phosphorylated by ATR during genotoxic stress arising from UV damage104. Upon activation,

BRCA1 induces cell cycle arrest in G1, which has been shown to depend on RB function105.

Several interactors of RB are known, among them RBBP6 (RB Binding Protein 6, Ubiquitin

Ligase), which is part of a protein network that enables genome-wide DNA replication and

chromosomal stability106. Replication abnormalities are often found within common fragile

sites (CFSs), which have been associated with a variety of oncogenes and tumor

suppressors107-109. The RBBP6/ZBTB38 (Zinc Finger And BTB Domain Containing 38)/MCM10

(Minichromosome Maintenance 10 Replication Initiation Factor) axis, with RBBP6 as

upstream member, has been shown to counteract CFS rearrangement and replication stress.

The multifunctional protein RBBP6 is implicated in several cancers, associated with DNA

repair through interaction with Y-box binding protein 1 and probably exerts its checkpoint

control via interaction with RB (G2/M phase) and TP53 (control of G1/S)110 111. TP53, the

most intensively studied tumor suppressor up to date, is both targeted by ATR and ATM

through CHEK1 and CHEK2 and acts as a transcription factor to alter gene expression and

promote senescence or apoptosis in response to intensive damage of DNA112. It is suggested

that the guarding functions of TP53 might be activated by DNA damage in early-stage

tumors, stressing its potential role in bridging the DNA damage response and

tumorigenesis112.

Several interactors of TP53 are related to cell cycle control and/or apoptosis. One example is

pituitary tumor-transforming gene 2 (PTTG2), a member of the securin family of proteins,

which has been shown to be responsible for cell adhesion and apoptosis in a TP53-, and

CDKN1A (TP21)-dependent manner113. TP53 is reversibly modified by a range of different

post-translational modifications, which regulate its stability as well as its tumor-suppressive

functions114. Numerous modifications occur upon stressors like DNA lesions after IR. One of

the many enzymes that target TP53, apart from ATM and ATR, is the protein kinase CK2

(Casein Kinase 2). It phosphorylates TP53 at Ser392 that is related to the IR response and

tumorigenesis functions of TP53114. It has been demonstrated that UV-induced TP53 levels,

site-specific DNA binding, and transcription regulation of hundreds of TP53-target genes can

be influenced via this mechanism114-117. CK2 is furthermore associated with the COP9-

signalosome complex of proteins that mediates ubiquitination and proteasomal degradation

28

of TP53 and is activated in response to DNA damage in the context of GGR, TCR and cell

cycle control60,118-120. Figure 2 summarizes checkpoint control functions in the cell cycle.

Figure 2 Cell cycle phases and checkpoints Schematic representation of the cell cycle phases comprising interphase (G1= Gap1, S= synthesis, G2= Gap2) and

M= mitosis. The possibility of cells to enter G0 phase is visualized by the arrow and functions of different cell cycle

checkpoints are summarized. Figure modified from Alberts et al.103.

1.3 Apical kinases of the DNA damage response

Successful repair of DNA lesions requires a nucleo-cytoplasmic cascade of events that needs

to be tightly regulated and coordinated. As described above, a complex signaling cascade is

activated following DNA damage, which depends on the nature of the damage and the cell

cycle phase in which the damage occurs. The consecutive steps of the signaling network are

attributed to sensors, mediators, transducers and effector proteins. The two main damage

sensor complexes are the MRN-complex that detects DSBs and the RPA/9-1-1 complex,

which senses exposed regions of ssDNA. Apical kinases in the DNA damage response are

crucial nodes of signal transduction and amplification and initiate the phosphorylation and

thus activation of hundreds of downstream targets. The phosphatidylinositol 3-kinase-

related kinase (PIKK) family includes enzymes that share catalytic activity through

serine/threonine kinase function121. While DNA-PK mainly triggers NHEJ in the course of

DSB-repair as described in section 1.1.2, the ATR and ATM kinases are activated in the

course of DNA replication defects and HR, respectively. ATR phosphorylates BRCA1, CHEK1,

MCM2, RAD17, RPA2, H2AX, TP53 and several more downstream targets that inhibit DNA

replication and mitosis and/or promote DNA repair, recombination, apoptosis or

senescence. It furthermore couples the FA pathway of crosslink repair to DNA repair

functions through FANCD2 monoubiquitination122-124. ATM may function as tumor

29

suppressor and phosphorylates and activates CHEK2, FANCD2, BRCA1, HERC2, EXO1, NBN,

TERF1, RAD9, H2AX, 53BP1, TP53 and many more downstream targets. These include the

kinase ABL1 that is activated in the course of checkpoint signaling upon DSB repair,

apoptosis induction and genotoxic stress management125 126. Furthermore, association

between ATM and NPAT (Nuclear Protein, Coactivator Of Histone Transcription) is known,

which is essential for cell cycle progression127, is implicated in S-phase entry promotion128,

and links cell cycle control to replication-dependent histone gene transcription129.

Although they share a certain number of components and downstream functions, the nature

of the DNA damage that triggers activation of these latter two kinases is distinct130. There is

strong evidence that the ATM/CHEK2 module primarily responds to DSBs, whereas the

ATR/CHEK1 pathway is activated by SSBs and bulky lesions. However, both pathways

converge on CDC25, thereby regulating cell cycle progression131 (subsection 1.3.3.).

1.3.1 ATR in DNA repair and checkpoint control

ATR is indispensable for cellular survival and controls responses to a broad spectrum of DNA

lesions. These include damage arising from malfunctional DNA replication that leads to an

excess of ssDNA122. RPA encloses the single-stranded DNA and interacts with a separately

formed heterodimer of ATR and the ATR interacting protein (ATRIP), which subsequently

attaches to the SSB122 132-134. Sensors of DNA damage and mediators of ATR signaling are the

RAD family checkpoint proteins, for example the checkpoint DNA exonuclease RAD1 that

interacts with RAD9 and HUS1 in the heterotrimeric 9-1-1 complex, which is recruited to the

DNA after damage together with DNA polymerases135. It has been suggested that the 9-1-1

complex has a positive impact on DNA polymerase beta (POLB) affinity to its template as

well as on its activity, thereby connecting checkpoint control with the early steps in DNA

repair135. ATR activation is supported by the action of the two adaptor proteins

Topoisomerase II Binding Protein 1 (TOPBP1) and claspin (CLSPN). The interaction of claspin

with phosphorylated RAD17 (a component of the 9-1-1 clamp loader) initiates and maintains

the phosphorylation of CHEK1 by ATR122 136. Following activation, CHEK1 dissociates from the

DNA damage site and fulfills its role as major downstream kinase through phosphorylating

and activating its many substrates, including proteins involved in cell cycle checkpoint

control137.

1.3.2 ATM in DNA repair and checkpoint control

The apical kinase ATM plays a crucial role in DNA DSB repair and was initially described in

the context of the genetic disorder and chromosome breakage syndrome Ataxia-

Telangiectasia (A-T), in which both ATM genes were found to be inactivated or missing,

hence named ataxia-telangiectasia mutated138-140 (subsection 2.3.5). It can be targeted

through the DSB-sensing MRN-complex141, direct interaction with the DSB142, or

conformational changes of chromatin143. Furthermore, there is evidence that ssDNA oligos,

which are generated by the MRN-complex and signal ongoing repair, also stimulate ATM

function144. The MRN-complex consists of proteins that are associated with genome-

instability syndromes, see section 2.3.5, and is one of the first DNA-binding platforms

localizing to the site of the DSB145. It unwinds DNA ends, activates inactive ATM dimers and

serves as scaffold for ATM and large macromolecular complexes, which are known as

“foci”145-146. Upon monomerization, ATM molecules are able to undergo

autophosphorylation, which extends their signaling capacity to hundreds of substrates147,148.

Several studies have pointed out that there is strong association between the proteins

30

involved in DSB repair and checkpoint control, one of them being the RAD50 interactor

RINT1 (RAD50 Interactor 1), which binds RAD50 only during late S and G2/M phases and may

be needed for the integrity of the radiation-induced G2/M checkpoint149.

Furthermore, RINT1 has been reported to be implicated in telomere length control via

interaction with RB family members independent from telomerase action150. Telomere

regulation and checkpoint control are tightly associated and oncogenic transformation is

often related to loss of telomere regulation by alteration of telomerase activity. Telomere

regulation is important in extending the replicative life span of cells and protection of

chromosome ends from degradation151. The 3’ single-stranded overhang of nucleotides at

the end of each telomere provides a similar target for ATM and ATR action as a DNA lesion,

which amplifies the function of the DDR in telomere integrity152,153. In mammalian germline

cells and the majority of cancers, telomere length is preserved by the ribonucleoprotein

telomerase154-155. It is recruited to telomeres by assistance of ATM and ATR156. Human

telomerase consists of TERC (telomerase RNA), TERT (catalytic subunit), dyskerin and TCAB1

(telomerase cajal body protein 1), also known as WRAP53157. WRAP53 (WD repeat

containing antisense to TP53) is an essential component of the telomerase holoenzyme

complex and also regulates TP53 expression and its induction after DNA damage158,159. It is

responsible for the association of the TERC subunit with cajal bodies (CB), where it can

interact with the catalytic subunit TERT158. Furthermore, TERC-containing CBs associate with

telomeres depending on the cell cycle phase160 161, which links WRAP53 to cell cycle

regulation.

In order to gain access to DNA breaks within tightly packed chromatin, core histones are the

initial targets of DNA-PK and ATM162. One of the primary targets of ATM is the histone H2AX,

an isotype of histone H2A, which is part of the histone octamere structure of nucleosomes

forming chromatin163 164. ATM phosphorylates H2AX on serine 139, which is then termed

γH2AX, within minutes after ionizing radiation and triggers γH2AX spreading along a

megabase of chromatin away from the lesion, further amplifying the signal165 166. γH2AX

mediates association of 53BP1 (p53-binding protein 1), NBN (Nibrin) and MDC1 (mediator of

DNA damage checkpoint protein 1)167-169, is associated with formation of RAD50, RAD51, and

BRCA1 foci formation during the damage recovery phase170 and can be targeted by ATR in

response to replication stress171. Although it greatly enhances localization of several repair

proteins in the vicinity of DNA lesions, it has been proposed that it is actually expendable for

their initial recognition169. H2AX phosphorylation by ATM is further intensified through

positive feedback by the damage sensor protein MDC1 until RNF8 (ring finger protein 8)-

mediated ubiquitination (in crosstalk with other proteins) terminates the initial signaling

cascade of γH2AX172 173. This results in chromatin relaxation, rendering it accessible for the

repair machinery and promotes local accumulation of 53BP1 and BRCA1 and their

localization at DSBs174-176. The timing of γH2AX and 53BP1 foci formation is regulated by the

RNF20–RNF40 heterodimer, which itself is another ATM target177.

The DNA repair protein 53BP1 was initially described as an interactor of the tumor

suppressor TP53178 and functions as mediator as well as effector of DSB repair. Similar to

γH2AX, it serves as landing platform for several other DSB repair proteins and amplifies ATM

signaling179. It enhances ATM phosphorylation of TP53, CHEK2 and BRCA1 and promotes

checkpoint control while loss or malfunction of 53BP1 results in G2/M-checkpoint defects

and increased genomic instability179-183. Furthermore, 53BP1 triggers DSB repair through

31

NHEJ by protection against DNA end-resection, which is crucial for pathway choice179,184. As

already mentioned for γH2AX, the activation and localization of 53BP1 to DSBs is mediated

by a series of chromatin ubiquitination steps, which involves the E3 ubiquitin ligase HERC2

(HECT domain and RCC1-like domain-containing 2)185 among others.

The tumor suppressor proteins BRCA1 and BRCA2 are DNA damage mediators and important

players in HR186 (see also sections 1.1.2 and 2.2). BRCA1 is recruited to sites of DNA lesions

after phosphorylation by ATM and ATR104,187-189, associates with RAD51190 and mediates-S-

phase and G2/M cell cycle checkpoints through the serine-threonine checkpoint kinase

CHEK1191-193. The major downstream kinase of ATM is CHEK2, which itself has a vast number

of substrates, amplifies the DDR signal to TP53 and forwards it to CDC25 phosphatases

crucial for the regulation of cell cycle progression126. It plays a major role in promoting HR

over NHEJ through targeting BRCA1 and BRCA2194. Not only TP53, BRCA2 and KAP1 (KRAB

[Kruppel-associated box domain]-associated protein 1), but also BRCA1 is mediated by both

ATM and CHEK2, which is likewise involved in cell cycle arrest to enable progression of DNA

DSB repair121,194. CHEK2 phosphorylation of BRCA1 furthermore promotes RAD51

recruitment, leading to strand invasion and exchange in the course of HR2 (section 1.1.2.).

Activation of CHEK2 by ATM and ATR includes several phosphorylation steps and involves

the phosphorylation sites Ser19, Thr26, Ser28, Ser33, Ser35, Ser50, and Thr68, as well as

autophosphorylation of CHEK2 itself in the course of signal amplification131,195,196.

Phosphorylation at the Thr68 residue is believed to be the initial activation step197-199, which

is followed by autophosphorylation of CHEK2 on residues Thr383 and Thr387 and

oligomerization to increase kinase acitivity197,200,201. Active monomers of CHEK2 can

translocate into the nucleus and target several substrates including cell cycle checkpoint

kinases to prevent cell cycle progression, and BRCA1 and BRCA2 to mediate HR194. After

completion of DNA damage repair, CHEK2 returns to an inactive state by protein

modification and degradation194.

Another major substrate of ATM is KAP1, which functions as transcriptional repressor and is

an important component of condensed heterochromatin202,203. As heterochromatin is

transcriptionally silent and tightly packed, repair of DNA requires more time in this part of

the genome and also differential regulation of repair compared to euchromatin-related

repair204,205. KAP1 is phosphorylated by ATM at the highly conserved residue Ser824 within

30 min after DNA damage206,205. Furthermore, it has been shown that DNA-PK and ATR,

besides ATM, can also activate KAP1206. Upon activation by phosphorylation, pKAP1

translocates into the nucleus, associates with damaged sites in chromatin, and has been

shown to colocalize with the damage foci of 53BP1, γH2AX and BRCA1206. It furthermore

serves as marker of sustained ATM activity at unrepaired sites within heterochromatin as its

phosphorylation is maintained by the hyperaccumulation of the MRN complex, dependent

on 53BP1, which mediates retention of ATM205.

The role of ATM in DNA repair, cell cycle control and survival pathways has been intensely

studied, however, there is also growing evidence that ATM mediates apoptosis through the

tyrosine kinase ABL1 (ABL Proto-Oncogene 1, Non-Receptor Tyrosine Kinase)207. ABL1 is

implicated in the hematological malignancy chronic myeloid leukemia (CML), in which ABL1

is fused to BCR after translocation, resulting in the BCR-ABL oncogene208. Following DNA

damage, ABL1 mediates cell fate determination in the context of cell cycle arrest in G1 or

induction of apoptosis by interaction with the tumor suppressor proteins TP53 or RB and the

33

1.3.3 Crosstalk of ATR and ATM in DNA repair and checkpoint control

In the previous subsections the mechanistic functions of ATR and ATM have been addressed.

Although there are several variations by means of events that trigger activation of the

kinases as well as differences in their targets, the interplay of these two major kinases is

essential for proper DNA repair and checkpoint control. While most DNA repair proteins can

be phosphorylated by both ATR and ATM, singularity seems to exist in the context of the two

checkpoint kinases CHEK1 and CHEK2122. Crosstalk is likely due to signaling intersections

between different DNA lesions, as end resection in the course of HR produces ssDNA, which

is targeted by ATR, and nucleases can cleave ssDNA resulting in generation of DSBs that

initiate ATM activation. As described above, checkpoint signaling demands action of both

ATR and ATM, but this is again dependent on environmental factors. Figure 4 illustrates how

ATR and CHEK1 interact to promote damage repair in G1/S phase of the cell cycle while ATM

triggers HR and cell cycle arrest via CHEK2 in G2 phase cells. Both signaling pathways

ultimately lead to inhibition of the CDC25 phosphatase in order to prevent the transition

from G2 into mitosis. Three isoforms of the dual specificity phosphatase CDC25 are known in

mammals (CDC25A, B and C) and in its active form, CDC25C activates the mitotic Cyclin B-

Cyclin Dependent Kinase 1 complex to promote cell cycle progression95. This is prevented by

phosphorylation through CHEK1 or CHEK2 which induces catalytic inhibition or cytoplasmic

sequestration of CDC25C.

Figure 4 Distinct roles for ATR and ATM in checkpoint control Role of ATR Serine/Threonine Kinase (left-hand side) and ATM Serine/Threonine Kinase (right-hand side) in radiation-

initiated checkpoint control. DNA lesions by irradiation (IR), UV light, or replication errors in G1/S phase of the cell cycle

lead to activation of ATR which targets CHEK1 (Checkpoint Kinase 1), leading to inhibition of CDC25 (Cell Division Cycle

25/CDC25C) phosphatase, which blocks transition from G2 (Gap 2) into M (mitosis) phase of the cell cycle. Irradiation

damage in G2 is repaired mainly through activation of ATM (right-hand side), which can either directly promote

homologous recombination (HR) or block cell cycle progression through activation of CHEK2 (Checkpoint Kinase 2) and

subsequently inhibition of CDC25. Figure modified from Abraham, 200195

. Activation and inhibition are shown by arrows

and bar-headed arrows, respectively.

34

1.4 The Fanconi anemia (FA) pathway

1.4.1 Genetic heterogeneity of Fanconi anemia

Among the diversity of different repair mechanisms, the Fanconi anemia pathway is highly

interconnected with other DNA repair branches and cell cycle control functions. The

genetically heterogeneous recessive disorder Fanconi anemia (FA) belongs to the

chromosome breakage syndromes and is characterized by cytogenetic instability,

hypersensitivity to DNA crosslinking agents, increased chromosomal breakage, defective

DNA repair, bone marrow failure and susceptibility to a variety of cancers221-223. The FA core

complex consists of 14 proteins, which have been implicated in DNA damage signaling of

replication-fork-blocking ICLs, rendering them highly important for prevention of toxic

lesions that inhibit strand separation during replication and transcription20. Drugs which

induce ICLs have been one of the first forms of chemotherapeutics and are still prominent in

cancer therapy. However, functions of the FA complex are not limited to ICL repair but in

fact extend to stabilization and protection of replication forks, regulation of cytokinesis, end

resection and interaction with several other repair pathways223. Up to date, 19 FA gene

products have been identified, and several more are known to be part of the FA complex.

Furthermore, crosstalk with NER, NHEJ and also HR, hence the name FA/BRCA pathway, has

been reported. The clinical characteristics of FA show some connections with other

disorders, for example XP, tumors of breast, ovary, pancreas and especially hematological

malignancies like myeloid leukemia223. Several genes have been described as breast and

ovarian cancer susceptibility genes, for example BRCA2/FANCD1, BRCA1/FANCS,

BRIP1/FANCJ, FANCM, PALB2/FANCN and RAD51C/FANCO. BRCA1, BRCA2, FANCN and

FANCO are also associated with familial predisposition to cancer, the latter being

additionally linked to head and neck cancers223-224. As some of the classical features of FA are

missing in patients with FANCO, RAD51/FANCR and FANCS mutations, these genes have

been designated FA-like genes. The most intensively characterized function of FA genes is

proper repair of ICLs, which picture a threat to genomic integrity by initiation of DNA

breakage and chromosomal rearrangements20.

1.4.2 The FA pathway in crosslink repair

DNA-protein-, or DNA-DNA-crosslinks can be induced by chemical agents such as alcohol,

cigarette smoke, dietary fat and especially crosslinking agents like mitomycin C used in

diagnositics225 and chemotherapeutics (see subsection 2.3.4). Crosslink repair is

characterized by the interplay of FA pathway components and homologous recombination,

requires replication-fork convergence and hence proceeds mainly during S-phase223 226. The

sensing of the damage by FANCM (Fanconi anemia complementation group M) and

recruitment of ATR to the lesion, which phosphorylates and activates FANCM, is the initial

step of ICL repair. FANCM bound to chromatin provides a scaffold for the FA core complex,

which forms nuclear foci dependent on ATR and BRCA2227, and assumes the function of a

constituted ubiquitin ligase for FANCD2 and FANCI. FANCL (Fanconi anemia

complementation group L) catalyzes the first sequence in a complex cascade of

ubiquitination steps, finally emerging in nucleolytic incision to “unhook” the ICL at converged replication forks by ubiquitinated FANCD2228. Subsequently, several

endonucleases and scaffold proteins are recruited, including complexes consisting of XPF

family members, such as EME1 (Essential meiotic endonuclease 1 homolog 1). The sequence

homologue EME2 has been designated as the more active endonuclease that also shows

broader substrate specificity and seems to promotes reactions which are specific to higher

35

eukaryotes229,230. After unhooking of the ICL, the lesion is bypassed by a process known as

“insertion”, in which translesion synthesis polymerases, which can accommodate bulky

adducts, incorporate nucleotides opposite the ICL and extend the nascent strand

(“extension”), however, this process is susceptible to the introduction of mutations223.

Particularly the insertion step is highly error-prone231, which is believed to be accomplished

by a POL ν-RAD51 interaction, thus establishing a link to homologous recombination

repair232-234. The DSB that was introduced during the incision step, is subsequently repaired

by HR proteins235, which are downstream of the FANCD2-I complex223. This complex consists

of the paralogues FANCD2 and FANCI, is activated by the recruitment of the FA core complex

to the site of the ICL, and subsequently ubiquitinated by FANCL in conjugation with

FANCT223. In a complex with BRCA2 and PALB2/FANCN, ssDNA nucleofilaments are formed

by the recombinase RAD51, which catalyzes strand invasion, associates with RPA near the

ICL and catalyzes the extension step236 237. Furthermore, the association of RAD51 with its

paralog RAD51C/FANCO has been described in the context of ICL repair, however, its effects

are downstream of unhooking and FANCD2 monoubiquitination238.

1.4.3 Bridging of the FA pathway with other DNA repair mechanisms

Several lines of evidence indicate the interconnecting functions of the FA pathway with

other DNA repair complexes. As described above, FANCL is a putative E3 ubiquitin ligase

subunit of the core complex of nuclear FANC proteins222, whereas the recombinase

FANCO/RAD51C is a member of the RAD51 family of strand-transfer proteins that is involved

in homologous recombination and repair of DNA239 240. RAD51C deficiency is characterized

by hallmarks of the FA phenotype, such as ICL sensitivity, chromatid-type errors and G2/M-

accumulation, however, it is also associated with breast and ovarian cancer susceptibility. It

plays a major role in HR-mediated repair, replication and intra-S-phase checkpoint control

through CHEK2 activation238, underlining its role in ATM-signaling. Several studies have

shown the synergy of the FA pathway and HR, suggesting that the HR proteins function

downstream of FANCD2 activation, whereas FA-proteins also regulate HR by interaction with

the MRN complex and POL ν223. Furthermore, connections between the BRCA1-binding

helicase FANCJ and MLH1 are known, which demonstrates the role of FA proteins in

mismatch repair241. A functional association of the FA pathway with the DNA-end-resection

factor RBBP8 has been shown, as FANCD2 works in a complex with BRCA1 and MRE11A to

recruit RBBP8 to stalled replication forks242-244, demonstrating its role in initiation of

homologous recombination and fork stabilization through protecting emerging DNA strands

from MRE11A-mediated degradation223. Apart from HR, MR and the replication stress

response, the FA pathway also mediates suppression of NHEJ, therefore displaying a role

outside S-phase. As discussed in section 1.1.2, NHEJ is the major repair pathway of DSBs, but

also highly error-prone, demanding a significant level of regulation. Furthermore, the FA-

related cellular sensitivity to cytotoxic agents can be targeted by inhibiting the NHEJ

components DNA-PK and LIG4 by limiting the binding capacity of the Ku subunit through

resection of the DSB ends by FANCD2245-248. This channels repair towards end-resection-

dependent pathways of HR and the error-prone alternatives end joining and single-strand

annealing pathways, which can lead to genome rearrangements and oncogenic

transformation223,249. Furthermore, an inhibitory relationship between FANCD2 and 53BP1

was shown, which seems to depend on the histone acetylase TIP60. 53BP1 accesses

chromatin through binding to dimethylated H4, which is prevented by TIP60 resulting in

favoring HR over NHEJ245,250,251. FANCD2, which hinders the access of 53BP1 to chromatin in

a TIP60-dependent manner, resulting in increased levels of 53BP1 at chromatin lesions,

36

thereby favors NHEJ over DNA resection and HR250. Recently, the Tudor interacting repair

regulator (TIRR) was identified as regulator of 53BP1 by masking its binding function to H4

and hindering its localization to DSBs252.

From studies with cells from XP patients, a link between the FA pathway and NER emerged,

as cells deficient in NER genes (which applies to XP patients) are also sensitive to the

generation of crosslinks253 and vice versa, inactivation of FA-components can result in

increased sensitivity to UV-light, and hence crosslink-repair254. NER proteins, for example

XPC255, have been shown to be important for recruitment of the FA core complex as well as

excision of ICLs223. The above stated findings suggest that the FA pathway plays a more

general role in favoring genomic stability than previously anticipated. This underlines the

fact that DNA repair pathways are highly interconnected in a complex network of interacting

processes, rather than being absolutely unique in their functions as genomic integrity

wardens.

1.5 The translationally controlled tumor protein as new player in DNA repair

The translationally controlled tumor protein (TPT1, also known as TCTP, fortilin, p23 or

histamine releasing factor/HRF) is ubiquitously expressed in all eukaryotic cells, evolutionary

highly conserved and involved in several cellular processes256. TPT1 can be found in almost

all human tissues, except kidney tissue257. The level of TPT1 mRNA depends on cell type,

developmental stage and extracellular stimuli258. TPT1 has been identified as an important

factor in tumor reversion259 260, is highly expressed in tumor tissues, especially of epithelial

origin256, and promotes cell migration, invasion and metastasis via induction of epithelial to

mesenchymal transition261. The transcription of TPT1 can be positively regulated by the

CRE/CREB complex (cAMP-response element/cAMP-response element binding protein)262

and by DNA damaging agents like etoposid and cisplatin, while it is negatively regulated by

TP53263. TPT1 overexpression can lead to TP53 degradation and loss of TP53-mediated

apoptosis induction264, whereas TP53 can downregulate TPT1 levels259, suggesting

antagonistic effects of the two proteins. While the antagonistic effect on TP53 would suggest

an oncogenic function, Zhang et al. (2012) have reported that TPT1 interacts with TP53 to

inhibit cellular proliferation in irradiated cells265. Furthermore, low-dose γ IR enriched TPT1

in nuclei of normal human cells and its upregulation appeared to be dependent on ATM and

DNA-PK kinases. In that study, TPT1 formed a complex with ATM, phosphorylated H2AX and

53BP1, exhibited a protective effect on irradiated cells and thus may play an important role

in the maintenance of genomic integrity. Conflicting data regarding the TPT1 interactome

has been published as one proteomics study did not identify these proteins as part of the

TPT1 interactome in HeLa cells266. Contrasting these findings, a functional interaction with

RAD51 and other DNA repair components was very recently published in HeLa cells267.

Furthermore, it has been demonstrated that the protein level of TPT1 in breast cancer tissue

is significantly higher than in healthy tissues268, similar to what has been described for

cancers of colon, liver, prostate, skin and throat263. While TPT1 is known as both marker and

prognostic factor for breast cancer, its molecular impact is still incompletely understood269.

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2 Introduction part 2: Individual radiosensitivity in cancer treatment

2.1 Cancer

Cancer reflects one of the leading causes of morbidity and mortality worldwide and has been

catching up to heart diseases as Grim Reaper number one in the last years270-272. The number

of new cancer cases is expected to rise by about 70 % over the next 2 decades273, promoted

by risk factors such as aging of the population and lifestyle changes like smoking,

overweight, physical inactivity as well as alternating reproductive patterns due to economic

development as well as immune system conditions274 275. It is considered as a multigenic and

multicellular disease276 and six hallmarks of cancer have been identified277: unlimited

proliferative potential, evasion of apoptosis, environmental independence for growth,

angiogenesis, invasion and metastasis throughout the body. However, this definition has

been critically discussed, as five of the proposed hallmarks also relate to benign tumors,

which are not invasive or possess metastatic potential278. Due to tremendous efforts in

cancer research, many underlying processes are now well understood and, as early

preventive and treatment options have advanced during the last years, many cancer types

have become curable279.

There are about 200 different types of cancers and classification is complex and subject to

change as increasing amounts of data are available due to rapid progress in research, for

example through access to OMICS data280. Carcinomas, which arise from epithelial cells, are

the most common type and account for up to 90 % of cancers, affecting the internal and

external linings of the body, including the skin281. Further subdivision includes basal cell

carcinomas and squamous cell carcinomas as the two most common human cancer types

which incidence is expected to double within the next 20 years282. Basal cell carcinoma is the

most common cancer, presenting low mortality but high morbidity283, and affecting only the

deepest layer of skin cells281. Squamous cell carcinoma (SCC) occurs in organs that are

covered with squamous epithelium including the top layer of the skin, lips, mouth,

esophagus and airways, urinary tract, prostate, lungs, vagina and cervix281 284. The majority

of cases within the SCC category includes non-melanoma skin cancer, esophageal cancer,

non-small cell lung cancer and head and neck cancer284. About 85 percent of head and neck

cancers are oral cancers which can involve the mouth, tongue, tonsils, the pharynx (throat)

and the nasal passageways285. Rectum cancer, sometimes referred to as part of the second

most common cancer type: colorectal cancer (see Figure 5), belongs to the cancers of the

digestive tract and accounts for 28 % of large intestine cancers286. Prostate cancer belongs to

the cancers of the genitourinary system and accounts for the majority of cancer deaths in

men287. Being the most prevalently diagnosed form of non-cutaneous malignancies in men,

its incidence is continuously rising (Figure 5)287 288. The molecular mechanisms underlying

this form of cancer involve androgens, which are male steroid hormones, and a well

established subject to therapy288. Breast cancer accounts for the largest group of cancer

diagnoses in women and is estimated to increase further (Figure 5). As the majority of

patients in this study were diagnosed with mammary carcinoma, this type of cancer will be

discussed in more detail in section 2.2.

Radiosensitive patients with the following cancers were collected for this study: 13 breast

cancer (two were chemoradiosensitive), one rectum, one prostate (which was

chemoradiosensitive), two oral cavity and pharynx (one hypopharynx and one keratinizing

squamous cell carcinoma of the base of the tongue), one head and neck (squamous

38

epithelium carcinoma of left tonsil) and one skin cancer (squamous cell carcinoma external

ear). Standard treatment of these patients had resulted in high toxicity, see Supplementary

table S-1.

Figure 5 Estimated new cancer cases and deaths in the USA in 2017, adapted from Siegel et al.

289

2.2 Breast cancer

2.2.1 Genetic predisposition and familial breast cancer

Breast cancer has been the leading cause of cancer deaths among females during the last

years275 and can affect females and males in more and less economically developed

countries worldwide. Less sophisticated countries become more and more afflicted, where

breast cancer remains the leading cause of cancer deaths among females275. Apart from

environmental risk factors, several genetic alterations can account for breast cancer

predisposition290 and morbidity and mortality can be reduced by preventative measures

through identification and care of patients with high risk due to genetic background291, while

the interplay between environmental factors and genetic predisposition also remains

substantial290. The growing understanding of the heterogeneous molecular nature of breast

cancer and its subtypes has reduced the mortality during the last two decades292 293,

emphasizing the importance of continuative research to gain additional insights into the

biochemical fingerprint of the disease eventually leading to individualized treatment.

39

Current data suggests that autosomal dominant susceptibility alleles account for up to 10 %

of breast cancers294 295, which are categorized as “hereditary” in contrast to “sporadic”290,

and it has been reported that 25 to 30 % of all breast cancers arise due to genetically

determined factors296. High- to intermediate-penetrance alleles were identified in over 20

genes which participate in DNA damage signaling and repair and some 180 low-penetrance

loci are known297 298. Breast cancer can be promoted by accumulation of mutations in

essential genes, such as BRCA1 (BReast CAncer 1)299 300 and BRCA2 (BReast CAncer 2)299 301

with high penetrance, in less than 7 % of cases302, or due to the cumulative effects of

mutations in several low-penetrance susceptibility genes290. Mutations in tumor suppressor

genes, for example Tumor Protein 53 (TP53) can account for a risk increase to a greater level

than BRCA1 and BRCA2302-304. Furthermore, PALB2 (partner and localizer of BRCA2), which

participates in homologous recombination repair (HR) and Fanconi Anemia is also classified

as high-risk299 305, while classical mutations in ATM297 306 307

(Ataxia Telangiectasia Mutated),

CHEK2 (checkpoint kinase 2)297, BARD1 (BRCA1 associated RING domain 1)306 308 or NBN297 309

310 account for moderate/intermediate risks.

Familial breast cancer (Fam BC) was initially defined as the occurrence of two or more first

degree relatives in the nuclear pedigree including the proband311 and accounts for 15–20 %

of all breast cancer cases290. Germline mutations in BRCA1 and BRCA2 and other rare

variants are associated with 15–20 % of familial breast cancer cases, while BRCA1 germline

mutations were identified in up to 80 % in patients with a family history including breast and

ovarian cancer290. In our study, 11 Fam BC patients served as comparison group to make out

differences in truncating mutations in selected pathways compared to RS (radiosensitive) BC

patients and control for identification of potentially genetically determined cancer and DNA

repair related dysfunctional background.

2.2.2 Breast cancer subtypes and triple negative breast cancer

The phenotypical convergence of genetic and epigenetic alterations into four main breast

cancer classes, which differ in prognosis and therapeutic response, was described by a large-

scale approach in 2012 by The Cancer Genome Atlas Network312. These four classes differ in

outcome prediction and response to treatment. Apart from the occurrence of genetic

susceptibility variants, breast cancer is characterized by hormone receptor status. The most

prominently represented subtype “luminal A” is characterized by high estrogen and progesterone receptor status and can be treated by hormone-based therapy if proliferation

rate of the cancer cells is low, and needs to be supplemented by chemotherapy to target

high proliferating cancer cells (“luminal B” as second most common subtype)312. A third

breast cancer subtype can be classified as “HER2E”, showing high protein and phosphoprotein expression of EGFR (Epidermal Growth Factor Receptor) and HER2 (human

epidermal growth factor receptor 2)312, now referred to as ERBB2 (Erb-B2 Receptor Tyrosine

Kinase 2), which can be treated by monoclonal antibodies like trastuzumab292 or tyrosine

kinase inhibitors like neratinib313.

Of all breast carcinomas, 10–15 % fall into the category of the “Triple negative breast cancer” (TNBC) subtype292, which is the diagnosis of 6 patients in our comparison group of

non-familial BC cases without irradiation side-effects. This subtype is associated with the

worst prognostic outcome314 and histologically characterized by lack of hormone receptor

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expression and missing HER2 overexpression/gene amplification, rendering targeted therapy

extraordinarily challenging292.

2.3 The relationship between cancer and radiosensitivity

Radiosensitivity is defined as relative susceptibility to radiation effects of cells, tissues or

organs315. Toxicity to radiation, for example by cellular death or tissue inflammation can be

associated with mutations in DNA repair genes such as ATM or BRCA2, which can also

increase susceptibility to cancer316-319. However, even though the same genes might be

involved, and the molecular pathways intricate, increased cancer risk through unrepaired

DNA breaks does not necessarily confer radiosensitivity316. Genetically determined

radiosensitivity to current knowledge is usually associated with high cancer risk, but aging

syndromes such as progeria may be an exception316 320 321.

An overview over acute and late effects will be given in Figure 7 and known chromosome

breakage and radiosensitivity syndrome with inflicted genes will be described in Table 2 in

section 2.3.5.

Individual RS can be observed at high doses which are used in radiation therapy, but also at

low doses, which apply to diagnostic radiation procedures like mammography or CT scans322-

325. This observation was confirmed by our group for LCLs and BC cell lines with known

mutations in DNA repair genes (see section 2.4)326 327. In some cases, radiation therapy is

also causative for the development of secondary malignancies328, which however, will not be

further discussed in this project. This project will solely focus on mechanisms of DNA repair

and cell death following radiation therapy in the context of acute and early adverse effects

after cancer treatment and is aimed to unravel ascendancies between the three topics

cancer, radiosensitivity and DNA repair, as depicted in Figure 6.

Figure 6 The relationship between cancer and radiosensitivity Mechanisms of DNA repair, cancer and radiosensitivity are highly interconnected. This project will focus on the

investigation of DNA repair mechanisms, which are hypothesized to represent the superior pathways connecting

tumorigenesis, cancer treatment and adverse effects to radiation therapy.

2.3.1 Benefits and drawbacks of irradiation treatment

Despite significant research progress during the last decades, cancer remains on the rise (see

section 2.1) and its clinical management stays challenging276. Among the different treatment

options ranging from surgery and chemotherapy to immunotherapy and hormone

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therapy276, radiotherapy is applied to about 50 % of all cancer patients329 330 and constitutes

approximately 40 % of treatment328. Radiation therapy was initially applied to treat

hypertrichosis and has been a powerful tool in cancer treatment since shortly after the

discovery of Roentgen radiation at the end of the 19th century316 331. Table 1 shows an

overview of cancer types which can be treated by IR or combined therapy. Neoadjuvant

radiation therapy is applied before surgery, aiming at shrinking the tumor, while adjuvant

therapy after surgery is aimed at elimination of microscopic leftovers276.

Table 1 Examples of cancers treated with radiation therapy (modified from Baskar et al.

276)

Early cancers curable with radiation therapy

alone

Cancers curable with radiation therapy

in combination with other modalities

Skin cancers (squamous and basal cell) Breast carcinomas

Prostate carcinomas Rectal and anal carcinomas

Lung carcinomas (non-small cell) Locally advanced cervix carcinomas

Cervix carcinomas Locally advanced head and neck

carcinomas

Lymphomas (Hodgkin’s and low grade Non-

Hodgkin’s) Locally advanced lung carcinomas

Head and neck carcinomas Advanced lymphomas

Bladder carcinomas

Endometrial carcinomas

Central nervous system tumors

Soft tissue sarcomas

Pediatric tumors

2.3.2 Molecular basis of radiation therapy

Effects of IR on biological tissues are determined by exposure level, dose rate and

physiological conditions of affected cells332. Underlying mechanisms are ionization of

biological material by energy transfer to electron acceptors like molecular oxygen, resulting

in the production of partially reduced or “reactive” oxygen species (ROS), most importantly hydroxyl radicals276 333. Although they can be beneficial in a different context, these radicals

can initiate and propagate chain reactions, which can be highly damaging to cells if the

organism is not capable of responding with an antioxidant reaction333. By damaging the

genetic material of the cells, resulting in either single- or double-strand-breaks (DSBs) in the

DNA (see subsections 1.1.1 and 1.1.2), cells with repair defects are deprived of their

potential to divide and proliferate334. Therefore, the feature of cancer cells to escape normal

DNA repair mechanisms becomes their fate as DNA damage increases to an extent where

cells can no longer survive while normal cells in the adjacent tissues usually are capable of

repairing the damage and surviving the radiation consequences. About 50 % of all cancer

patients require radiotherapy of which 60 % are treated to achieve cure of their disease,

however, radiation dose is limited in all patients to protect the 5–10 % who are vulnerable to

develop severe side-effects328.

2.3.3 Adverse effects on healthy tissues

Side-effects of irradiation affecting healthy tissues have been an issue ever since the first

applications of radiation treatment. “Individual radiosensitivity”, a phenomenon which has been known for over 100 years316, was initially thought to be due to dosimetry errors,

42

leading to subsequent improvement efforts and definition of reliable radiation units316 335. In

the early 1900s, suggestions have already been made that radiosensitivity could be linked to

the proliferation rate of cells336 and might be affected by hereditary or acquired

predisposition316 337. An important step forward and a possibility to actually quantify

radiation effects was the establishment of the “clonogenic (or “colony survival”) assay” as biological endpoint to measure the loss of proliferative potential in 1956338.

Research on normal tissue responses has been an issue for over 100 years and it is now

believed that injuries in normal tissues result from a dynamic and progressive process, rather

than immediate effects, and vary according to genetic predisposition and context of

treatment328. Application of ionizing radiation triggers ROS-related DNA damage, which

exerts a compromising effect on the cellular microenvironment. This triggers inflammation

by release of chemokines, inflammatory and fibrotic cytokines, for example transforming

growth factor-β1 (TGFB1) and changes in cell–cell interactions339. Furthermore, immune

deficiencies can also arise from DDR defects as primary cause334. Several genes involved in

DNA repair, immunological and apoptotic reactions have been suggested as drivers for

radiation side-effect reactions, however, no clear “radiosensitivity gene” apart from genes

inflicted in already known radiosensitivity syndromes (subsection 2.3.5), has been

discovered, see also subsection 2.3.5.

The classification systems of acute and late side-effects have changed over the years and the

first system was the RTOG (Radiation Therapy oncology Group)–EORTC system and was

replaced by the LENT SOMA (Late Effects Normal Tissues: Subjective, Objective,

Management and Analytic) system340-343. This again was exchanged and updated through the

National Cancer Institute (NCI) Common Terminology Criteria for Adverse Effects version 3.0

(CTCAE v3.0), which includes recording of acute and late effects and the category of death

following radiotherapy344, of which an update to version 4.0 is available today345.

Different forms of radiation side-effects have been described and can be divided into acute

and late effects, see Figure 7. Acute effects can arise during or shortly after treatment

(within 90 days of treatment according to315), are normally reversible and not considered

dose-limiting. They usually arise in highly proliferating tissues such as skin through

impairment of wound healing by effects on fibroblasts346, hair, gastrointestinal tract or

haematopoietic system and tend to cause inflammation328. They are unaffected by changes

of radiation dose per fraction but vary with radiation delivery time, but usually subside

during the first weeks after treatment. Acute toxicity is usually handled by expanding general

treatment time in parallel to limiting applied doses, which however, also reduces

effectiveness of cancer cell killing and is therefore contradictory by means of treatment

efficiency. Late effects usually occur during 6 months up to years after radiotherapy (more

than 90 days after treatment according to315) and include severe reactions that can be

permanent328. In contrary to acute effects, these afflictions relate to slow-proliferating

tissues such as heart, central nervous system and kidneys and include vascular damage,

atrophy and fibrosis. Furthermore, second malignancies and hormone deficiencies such as

infertility can arise and opposite to acute effects, late effects seem to be influenced by the

entire therapy time to a lesser extent and rather sensitive to alterations in radiation dose per

fraction328. Variations in patients response by means of acute as well as late effects was

proposed to follow a Gaussian distribution347 and several environmental factors other than

solely genetic inheritance, which is estimated to account for 80 % of side-effects348, need to

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be considered for estimating the risk of side-effects. Risk factors can be the patient’s age, nutritional status, smoking habits, vascular and connective tissue diseases, diabetes mellitus,

infections and hypertension among others. Additional influence factors are radiation

parameters (as radiation dose-response follows a steep correlation), as well as possible

additional therapies such as surgery or chemotherapy and after all, chance according to

Poisson statistics need to be considered additional influence factors349-352.

Figure 7 The toxicity of radiotherapy Overview over a selection of acute and late adverse effects of radiotherapy, figure based on

328. Acute effects are shown in

orange boxes on the left-hand side and late effects are shown on the right-hand side in yellow boxes. Some examples of

effects are given at the bottom boxes.

2.3.4 Chemoradiosensitivity

The use of chemical agents in cancer chemotherapy is a well established and effective

therapy procedure which is directed at introducing DNA lesions in highly proliferative cancer

cells which subsequently die due to failure of repair capacity. Such agents initiate a variety of

DNA lesions ranging from alkylating agents like methyl-methane sulfonate (MMS), which

attach alkyl residues to DNA bases, to crosslinking agents such as mitomycin C (MMC) and

cisplatin, which induce intra-, and interstrand crosslinks2. For decades, 5 Fluorouracil (5FU)-

based therapy, which utilizes the antimetabolite properties of the base analogue 5FU, has

remained the standard first-line chemotherapy treatment in the majority of cancers and its

combination with cisplatin and radiation therapy became common clinical praxis353. In

contrast to surgery or radiation therapy, chemotherapy is not restricted to a certain area but

attacks cancer cells throughout the body. It is successfully used for treatment of the majority

of cancers, however, patients often suffer from side-effects. These can exceed hair loss,

inflammatory responses and skin or intestinal toxicity and extend to severe consequences.

Potentially lethal toxicity has been reported in the context of Dihydropyrimidine

dehydrogenase (DPYD) deficiency after 5FU administration related to defects in the DPYD

gene354. However, only a minority of chemotoxicity effects can be explained by this disorder

44

and the search for chemoradiotherapy-markers during the last decade in order to predict

outcome and benefit of chemotherapy revealed several associations of known DSB repair

genes related to toxicity effects. Those included TP53, BRCA1, XPA/XPC, RAD51, MLH1 and

PARP1 among others. However, not enough data on their usefulness in the clinical praxis are

available up to date355-357. In chemoradiotherapy, a combination of chemotherapy and

radiotherapy is applied in which chemotherapy often serves as radiosensitizer358. Similar to

personal manifestation of sensitivity to radiotherapy, the response to radiotherapy differs

strongly between patients. Assuming that all cells within a tumor have developed from

formally normal tissue cells, the inherent genetic sensitivity towards DNA damage should be

accessible via the genetic profile of the patient359. However, tumors always harbor a mixed

population of cells and highly proliferating cells are more sensitive to DNA damaging agents

compared to quiescent cells, but a recent study has correlated acute organ toxicity with

clinical outcome, suggesting varying levels of inherent repair capacity might serve as

prognostic marker in chemoradiosensitivity360.

2.3.5 Known radiosensitivity syndromes and inflicted genes

Radiosensitivity has been described by reference to borderline cases in an “all-or-none“-

manner, where patients with DNA Ligase 4 (LIG4) and ATM mutations consequently

succumbed to radiation therapy, however, such incidents were extremely rare316 361-363.

Table 2 shows an overview of chromosome breakage syndromes and known radiosensitivity

syndroms, with assignments to involved genes88,140,364-370. Moderate radiosensitivity

reactions such as proctitis (inflammation of the rectum lining) and dermatitis (inflammation

of the skin) arise much more frequently, as up to 15 % of cancer patients without established

radiosensitivity syndromes suffer from severe complications in the course of radiation

treatment316 371-375. None of these observations are due to dosimetry errors, however, one

historical radiation accident needs to be considered in which overdosing thousands of

prostate cancer patients with radiation therapy resulted in a wide variety of reactions

ranging from cure of the patients to decease, even though each patient suffered from the

same conditions (20 % excess of dose)376.

Table 2 Chromosome breakage and radiosensitivity syndroms

Genes Name Function Disease Additional features

BLM Bloom Syndrome

RecQ Like Helicase

Helicase Bloom’s syndrome

Chromosome

breakage syndrome,

cancer

predisposition,defecti

ve immunity

ATM Ataxia telangiectasia

mutated

Serine/threo

nine kinase in

HR, telomere

protection

and cell cycle

arrest

Ataxia

telangiectasia

Chromosome

breakage syndrome,

cancer proneness

(especially of

lymphoid origin),

neurodegeneration,

immunodeficiency,

cellular

radiosensitivity,

radioresistant DNA

synthesis

https://www.mdanderson.org/documents/Labs/Wood-Laboratory/human-dna-repair-genes.html#TOP

https://www.mdanderson.org/documents/Labs/Wood-Laboratory/human-dna-repair-genes.html#TOP

http://www.genecards.org/cgi-bin/carddisp.pl?BLM&search=BLM&suff=txt

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FANCA-

FANCW

Fanconi Anemia

Complementation

Group A-W

(without O,R,S,T)

Various in

DDR

Fanconi

Anemia

Chromosome

breakage syndrome,

cancer proneness,

bone marrow failure,

short stature, skin

abnormalities and

developmental

disabilities

FANCO;

FANCR/RAD5

1; FANCS

Fanconi Anemia

Complementation

Group O,R,S

Various in

DDR

FA-like

syndrome

Symptoms of FA

without bone-marrow

failure and leukemia

predisposition

XPA; XPB;

XPC; XPG;

ERCC4; ERCC6;

DDB2; POLH

Xeroderma

pigmentosum group

of DNA Damage

Recognition And

Repair Factors

Various in

NER

Xeroderma

pigmentosu

m

Chromosome

breakage syndrome,

cancer predisposition

(in cells which receive

solar damage),

sensitivity to sunlight

and chemicals

NBN Nijmegen Breakage

Syndrome 1 (Nibrin)

DDR,

checkpoint

activation

though

recruitment

of apical

kinases

Nijmegen

breakage

syndrome

Cancer predisposition,

radiosensitivity,

microcephaly,

immunodeficiency,

radioresistant DNA

synthesis

LIG4 DNA Ligase 4 Ligase in

NHEJ

LIG4

syndrom

Primary

immunodeficiency,

sensitivity to ionizing

radiation, growth

failure, microcephaly,

predisposition to

lymphoid

malignancies

WRN Werner Syndrome

RecQ Like Helicase

Helicase &

exonuclease

Werner

syndrome

Cancer proneness,

immunodeficiency,pre

mature aging

RECQL4 RecQ Like Helicase 4 Helicase Rothmund-

Thompson

syndrome

Cancer susceptibility,

dwarfism, growth

deficiency, skin

abnormalities

ERCC6;ERCC8 Excision Repair 6,

Chromatin

Remodeling Factor;

Excision Repair 8, CSA

Ubiquitin Ligase

Complex Subunit

Various in

NER

Cockayne

syndrome

Sensitivity to sunlight

and UV radiation,

neural abnormalities,

growth failure,

cachectic dwarfism,

mental retardation,

progerioid appearance

http://www.genecards.org/cgi-bin/carddisp.pl?WRN&search=WRN&suff=txt

http://www.ncbi.nlm.nih.gov/omim/277700

http://www.genecards.org/cgi-bin/carddisp.pl?RECQL4&search=RECQL4&suff=txt

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XPB/ERCC3;X

PD/ERCC2;TFB

5/GTF2H5

ERCC Excision Repair

3, TFIIH Core Complex

Helicase Subunit;ERCC

Excision Repair 2,

TFIIH Core Complex

Helicase Subunit;

General Transcription

Factor IIH Subunit 5

Various in

NER

Trichothiody

strophy

Sensitivity to sunlight

and UV radiation,

progeria, growth

retardation

ATR Ataxia telangiectasia

and Rad3-related)

Serine/threo

nine kinase in

DDR,

replicative

stress

response,

telomere

protection

and cell cycle

arrest

Seckel

syndrome

Primordial dwarfism,

CNS anomalies, ‘bird-

like’ face

RAD50 RAD50 Double Strand

Break Repair Protein

DSB repair,

cell cycle

checkpoint

activation,

telomere

maintenance

RAD50

deficiency/A

TLD

Microcephaly, mental

retardation, ‘bird-like’ face, short stature,

chromosomal

instability, cellular

radiosensitivity, radio-

resistant DNA

synthesis

MRE11A MRE11A Homolog,

Double Strand Break

Repair Nuclease

3' 5'

exonuclease

activity and

endonucle-

ase activity

Ataxia-

telangiectasi

a-like

disorder

(ATLD)

Chromosomal

instability, cancer

predisposition, cellular

radiosensitivity,

radioresistant DNA

synthesis

The chromosome breakage syndroms Ataxia telangiectasia (A-T), Bloom’s syndrome, Fanconi Anemia and Xeroderma pigmentosum have been known since decades140 and share the

common feature of increased cancer risk. Patients suffering from these disorders are

strongly radiosensitive and have been shown to develop gaps in skin fibroblasts after

radiation treatment377-379. A-T results from mutations in the ATM gene which causes cancer

proneness, immunodeficiency, radiation sensitivity, telangiectasia, atropy, cerebellar

degeneration, abnormalities in pigmentation and accelerated hair graying. A-T

heterozygosity is found in 1 % of the population380-382. Bloom’s syndrome, as well as Werner syndrome, and Rothmund-Thomson syndrome/RAPADILINO/Baller-Gerold syndrome, share

mutations in the helicases BLM, WRN, and RTS, respectively, which manifest as rare genomic

instability disorders88,383. Bloom’s syndrome is characterized by immunodeficiency and mutations in BLM result in impairment of its ATPase or helicase functions by

mislocalization87,384 385. In Werner syndrome, the BLM homolog WRN is truncated and results

in a premature aging phenotype, along with senescent features of cells, disturbed telomere

function and high cancer incidence87,386 387. Mutations in the helicase encoded by the

http://www.genecards.org/cgi-bin/carddisp.pl?gene=ERCC2&keywords=xpd

http://www.ncbi.nlm.nih.gov/omim/609188

47

RECQL4 gene causeRothmund-Thomson syndrome, which leads to cancer susceptibility,

growth deficiency/dwarfism and skin abnormalities388 389. RECQL4 is known to localize to

telomeres and mitochondria and mediates growth arrest after DNA damage87,390.

Xeroderma pigmentosum is another chromosome breakage syndrome, associated with

defects in nucleotide excision repair and susceptibility to UV-related damage, leading to

increased cancer risk366,391. Related disorders are Cockayne syndrome (CS) and

trichothiodystrophy (TTD), all based on defects in NER. Mutations in ERCC6 and ERCC8 genes

cause growth implication, microcephaly, cachectic dwarfism and neurodegenration in

patients with CS392-394, while defects in XPB, XPD or TFB5 cause the progeroid disorder TTD,

which is further characterized by growth retardation and a photosensitive phenotype395. As

described in section 1.4, the FA genes are involved in DNA repair and defects in these genes

can result in SSBs, which induces progressive shortening of telomeres and chromosome-end

fusions as well as multinucleated cells396. Mutations in FA-genes result in cancer proneness,

developmental failures, short stature as well as bone marrow failure and skin implications397,

and 19 genes are currently known to cause FA (FANCA-FANCW)223, some of which are also

associated with breast and/or ovarian cancer predisposition in heterozygotes223 396.

The Nijmegen breakage syndrome (NBS) was often confused with LIG4 syndrom or FA, as

patients share a certain number of symptoms, such as cancer predisposition,

radiosensitivity, chromosomal breakage, microcephaly and immunodeficiency370. Similar to

A-T as well as NBS, patients with ataxia-telangiectasia-like disorder (ATLD) due to mutations

in MRE11A, show hypersensitivity to ionizing radiation and an occasional role in cancer

development398,399. Another NBS-like disorder due to mutations in the RAD50 gene, shows a

similar phenotype including chromosomal instability, radiosensitivity, radioresistant DNA

synthesis as well as cell cycle-checkpoint defects400. Furthermore, Seckel syndrome, caused

by ATR mutations, is associated with growth retardation and dwarfism along with central

nervous system anomalies and bird-like face401. Altogether, these syndromes are of very rare

occurrence and therefore of little relevance to adverse reactions in daily routine

radiotherapy, as most radiosensitive patients do not show a distinct phenotype.

2.3.6 Different forms of cell death following irradiation

As described above, the idea behind radiation therapy is to induce cell death in the tumor

tissues, this, however, does not occur immediately after irradiation. It usually takes hours,

days or even weeks until tumor cells have finally died and this also depends on the cell death

mechanism which is triggered by cancer therapy276. Damaged cells often undergo several

(attempts of) mitoses before finally dying and Figure 8 gives an overview of the cell death

mechanisms induced by ionizing radiation.

The most prevalent forms of cell death in radiation therapy are apoptosis and mitotic

catastrophe/mitotic cell death402-405. The programmed cell death apoptosis relies on the

ATM-p53-bax-cytochrome c-caspases pathway406 and is characterized by shrinkage of cells

and apoptotic body formation. Further characteristics are cell membrane blebbing, the

conservation of intact cell membranes, DNA fragmentation and condensed chromatin276.

Mitotic cell death occurs during or after abnormal mitosis, if cells fail to properly segregate

chromosomes, which leads to the formation of giant cells containing multiple nuclei and has

been shown to depend on the p53-caspases-cytochrome c cascade407.

48

Necrosis, however, is a rather uncontrolled form of cell death which is characterized by

destruction of cell membrane integrity and release of cellular components into the

surroundings408. Morphological characteristics of necrotic cells involve altered nuclear shape

with vacuoles and uncondensed chromatin and dispersed cellular organelles, and signaling

cascades involving TNF (alpha)-PARP-JNK-Caspases pathway has been shown to play a role in

this form of cellular death276,409.

Senescence represents a quiescent state of cells, which are still viable but cease proliferative

capacity, can no longer synthesize DNA and show enlarged and flattened morphology with

intense granular structure276. The MYC-INK4A-ARF-p53-p21 pathway is implicated in

senescence410 and this form of cell death is triggered by a strong impact of radiation-induced

DNA damage causing high cellular stress411,412, which eventually has been shown to lead into

apoptosis in a majority of cases.

Autophagy has only lately been identified as another form of cell death which is related to

apotosis as it is also programmed and in which the cell undergoes self-digestion via genetic

regulation involving the lysosomal compartment of the cells276. It is associated to the PI3K-

Akt-mTOR signaling cascade413 and morphologically described by cytoplasmic vacuoles with

double membranes, which sequester organelles414 415.

Although most of these cell death pathways are interconnected, IR-induced death

mechanisms are still a broad subject of research, which aims to draw connections between

the DNA damage response and intracellular signaling cascades leading to cellular death,

especially the question of how it could become possible to specifically induce cell death only

in cancer cells targeted by irradiation therapy while sparing the normal tissue environment.

Figure 8 Forms of cell death in cancer or healthy cells triggered by irradiation Irradiation (displayed by red arrow on the left-hand side) of cancer, as well as healthy cells to some extent, increases

genome instability by induction of DNA damage. Failure in DNA repair leads to cell death which can be apoptotic or through

mitotic catastrophe, which are the two most prevalent mechanisms after irradiation. Also possible are cell death

mechanisms through necrosis, senescence or autophagy, figure modified from Baskar et al.276

.

2.4 Related work on characterization of individual radiosensitivity

Radiation therapy can cause severe side-effects on healthy tissues of patients, which inflicts

several limitations in effective cancer treatment, as described in section 2.3. Unraveling the

reasons for increased radiosensitivity has been subject to intense research for decades and

up to date, the molecular mechanisms that control human radiosensitivity reactions are

incompletely understood. Chromosome aberrations and other cellular RS reactions following

radiotherapy in cells from patients with known radiosensitivity syndromes, such as A-T, NBS

or FA have been repeatedly described in the literature, rendering some of these patients

untreatable by radiotherapy416-420, however, a clear correlation between other

49

radiosensitivity syndromes and cellular survival could not always be established, for example

in patients with Bloom’s syndrome or FA-like condition421 422. It was furthermore reported

that A-T carriers displayed moderately increased cellular and chromosomal radiosensitivity,

suggesting that this could relate to increased clinical RS. Therefore, sequence analysis of the

ATM gene was performed in genomic DNA of cancer patients with at least RTOG grade 3

acute and/or late effects, which showed sequence variations by already known

polymorphism and silent mutations in only 2 of 20 patients423. One of the two is part of this

project, suggesting a different genetic profile might lead to the adverse effects423. This was

further supported by a study in the year 2002, in which no evidence for ATM, NBS, MRE11A

or RAD50 mutation was found in patients with RTOG 3 late reactions, of which four are also

part of this study424. However, a possible association between increased chromosomal

sensitivity and ATM variants in form of polymorphism and silent mutations has been

described in two radiosensitive breast cancer patients, one being also part of the patient

collective used in this project425.

Furthermore, a strong diversity of both acute and late reactions even after identical

treatment parameters has been documented already two decades ago that could not be

attributed to a certain radiosensitivity syndrome347 348 350 351 426-428. At the end of the 1990s

evidence converged that individual radiosensitivity is determined by the genetic background

of a patient328 and prediction of personal risk of side-effects has been considered the “Holy Grail of radiobiology”429 430. In 2003, Dikomey et al. proposed a theory why contradictory

results might have been obtained so far, as the assumption, that only radiosensitive patients

develop reactions might not be true431. On the contrary, they implied that all patients are at

risk of developing side-effects but the time frame after treatment is determinative. This

model is supported by data gained in 2001, where one group described kinetics of the risk of

suffering from late side-effects following an exponential decline for all patients, whether

initially characterized as radiosensitive or not374. This possible lifelong risk of developing late

complications demands continuous follow-up examinations to determine which biological

processes might be responsible for the time dependency of late effects’ manifestation374.

Several studies addressing the relevance of polymorphisms in candidate genes followed, and

positive correlations were reported between variants in TGFB1 (which controls proliferation,

differentiation, is important in wound healing and is upregulated in tumors432 433), SOD2

(Superoxide Dismutase 2, involved in ROS scavenging, apoptosis and cancer434), and the two

DNA repair genes XRCC3 (X-Ray Repair Cross Complementing 3) and XRCC1 (X-Ray Repair

Cross Complementing 1). Increased risk of subcutaneous fibrosis and partly also

telangiectasia was reported435, however, these genes were only partly identified in other

studies429,434 436-439. It soon became clear that individual radiosensitivity reflects a complex

trait, and not a condition that can be broken down to one or two genes, but rather relies on

their synergistic effects434. Following studies aimed at increasing statistical power, providing

homogenous study parameters in terms of patient selection, cancer site, parameters of

treatment and functional end points for measuring toxicity effects, which should be

facilitated by establishment of the international Radiogenomics Consortium440,315.

Further studies focused on relating gene expression profiles to radiation toxicity, as it has

been previously shown that gene expression patterns can be altered in A-T patients441.

However, the outcome of these studies again was different. One study found a high

50

reciprocal correlation of the expression of CDKN1A (Cyclin Dependent Kinase Inhibitor 1A) to

reaction severity442, whereas gene expression of ubiquitin, apoptosis and stress signaling

networks only related to radiosensitivity to some extent in another study443. One study

found 18 genes assigned to apoptosis, extracellular matrix remodeling and cell adhesion,

proliferation and scavenging of ROS. Gene expression profiles could clearly distinguish

between high and low risk patients of IR-induced skin fibrosis in BC patients444, however, the

previously proposed marker gene CDKN1A was not found in concordance with another

study445. Transcriptomics-based studies successfully correlated early and late effects with

differential gene expression in genes involving inflammatory and stress responses as well as

antioxidant metabolism. However, they failed to converge to a final definition of driver

genes as radiotherapy involves distinct effects in a variety of tissues that are also subject to

remodeling and continuous change throughout the duration of therapy, as well as in time

between follow-up investigations328,446,447. Moreover, a summary of several studies aimed at

generation of RNA signatures from fibroblasts and lymphocytes to predict early and late

consequences and several more genes have been proposed to play an important role in the

pathogenesis of radiation toxicity. Their overall functions have been summarized to DNA

damage sensors and mediators, cell cycle checkpoint control genes, apoptosis and

inflammatory genes, oxidative stress mediators as well as genes involved in endothelial cell

damage328 and common variants in oxidative stress response NOS3 (eNOS/Nitric Oxide

Synthase 3) and DNA repair XRCC1 genes have been specifically associated with acute skin

toxicity in breast cancer patients more recently448.

However, candidate gene studies altogether largely failed to identify genetic variants causing

the majority of radiotoxic phenotypes and the pathogeny of the disease still seemed very

multifaceted. Therefore, a GWAS (Genome-wide association study) approach was already

suggested in 2009 to identify variants and the way they might interact, to enable a

pretreatment profile testing of patients328 which, however, requires a very large patient

group and might be difficult to realize as the minority of patients develops late reactions. It

was hypothesized that, in contrast to the candidate gene approach, individual RS might be

determined by multiple loci ranging from common variants with minor effects to rare

variants, with tremendous effects on the RS phenotype, and that the tissue- and endpoint-

specificity is of considerable importance315,439.

As gene expression studies rather concentrate on the phenotype than on the genotype,

radiooncology research underwent a change of direction again, stressing importance of

GWAS studies in finding common genetic variants315, which came into focus in 2010 and

recommendation about gene knockout studies were made429. In 2012, progress on GWAS

was published, stating the identification of 67 marker genes, which were differentially

induced after IR in lymphocytes from radiosensitive patients in a multicentric study449.

However, no match with previously described candidate genes was achieved and

interestingly, functional radiosensitivity assays showed great variability between patients.

Moreover emphasizing the importance of the GWAS approach, 80 % correlation between

radiosensitivity and acute toxicity in patients was found and genes of DNA repair, apoptosis

and cell cycle regulation were again identified, which supports previous data450. This

multifaceted approach confirmed the reproducibility problem, as previous data stating

reduced apoptosis of lymphocytes as predictive marker of radiotoxicity451 could not be

validated, which was supported by other studies452 453. As progress commenced in the field

of next generation sequencing, the radiogenomics field emerged, which included

51

identification of increasing numbers of polymorphisms associated with radiotoxicity and

larger GWAS studies315. Recent progress in this field supported the idea that inter-individual

variation between RS patients is based on common genetic variants with low penetrance. A

large GWAS study in 2014 confirmed association between common genetic variants and

toxicity, which however, seemed to be tumor site-specific, and found associations for

individual endpoints but not as an overall toxicity measure regarding all patients454.

However, none of the SNPs identified in this large study were found in previously described

candidate genes for radiotherapy toxicity455. However, potent radioprotective substances

could be established based on these research findings, for example inhibitors of superoxide

dismutase (SOD) conferred reduction of cytokine production in some tissues, for example

TGFB1, when being used in parallel to several other substances including apoptosis and

senescence inhibitors456. Further progress in the field of next generation sequencing, for

example by exome sequencing, has enabled identification of new players of the DNA

damage response, as was shown for MTPAP (mitochondrial poly-A-polymerase) more

recently457. Advances in genome editing techniques also enable a whole new area of

research and this methodology already emerged into the radiosensitivity field458.

Additionally to the task of unraveling genetic drivers in individual RS, a pre-radiation test

needed to be established, which allowed easy and fast feasibility according to clinical routine

requirements. Quantification of DNA damage by measuring DNA strand breaks in form of

micronuclei formation, chromosome aberrations, clonogenic survival and later also foci

analysis are all established assay systems but time-consuming in the first place and also did

not produce clearly reproducible results over the last decades. While most analyses focused

on investigating differences between cells of patients with established radiosensitivity

syndromes in comparison to healthy controls459, this approach was also addressed

concerning radiosensitive patients with no known RS syndromes. One group found a

significant correlation between clonogenic survival and excess acentric fragments with

radiosensitivity in dermal fibroblasts460 and fibroblast-specific parameters have been

associated with fibrosis observed in clinical procedures461 and radiation-triggered generation

of TGFB1, also in lymphocytes460,462,463. However, the excess risk of fibrosis could not be

reliably predicted in another study although correlation between residual DSBs and the

cellular radiosensitivity of the patients was possible464. Another group proposed an assay

system based on apoptosis of lymphocytes, which showed good correlation with late toxicity

effects in patients with a variety of cancers465, and lymphocyte-associated assay systems

were found to be a good predictor of acute reactions466. Furthermore, one group has

provided evidence for an impairment of the nucleo-cytoplasmic shuttling of the ATM protein

in radiosensitive cell systems467 468. Despite these progresses, however, no assay which met

requirements for clinical use had been established so far339 440, although new techniques are

on the rise. The visualization of DNA DSB sites through immunofluorescence analyses of

repair foci is a well established radiobiological endpoint, and recent findings provide

evidence for the γH2AX assay as predictive clinical ex vivo marker of individual patient

radiosensitivity through blood and eyebrow hair follicle samples469 and it has also been

modified to enhance practicability470. Furthermore, our group could lately show good

correlation with early and residual γH2AX and 53BP1 foci in the low-, and high-dose IR

context of lymphocytes and LCLs of patient cells with mutations in ATM, and triple negative

breast cancer cell lines with impaired TP53/BRCA1 and NBN/BRCA1326 327. Moreover, flow-

cytometry based assays for the prediction of RS for clinical routine have very recently been

established471,472.

52

2.5 Previous and related work on TPT1 in breast cancer and ATM signaling

2.5.1 TPT1 as a candidate BC susceptibility gene

Given that TPT1 levels can be increased in BC cells or BC tissues, which underlines its

function as a tumor marker protein and protective factor in cancer cells268 473 474, and its

possible role in DNA repair, a previous study in our lab sought to investigate whether

mutations in TPT1 were enriched in breast cancer patients475. The six coding exons of TPT1

were amplified from 200 genomic DNA samples of breast cancer patients from the

Hannover-Minsk Breast Cancer series476 and were subjected to mutation identification

through Sanger sequencing. A novel missense substitution, c.452G>A resulting in a Tyr to Cys

substitution p.Y151C, in one patient and a previously recorded synonymous variant,

c.492G>A in another patient were identified. The p.Y151C mutation was predicted to be

pathogenic by SIFT (Sorting Intolerant From Tolerant), Provean and Mutation Taster. These

were the only sequence alterations identified in this exploratory series of 200 fully

sequenced cases, and both changes were not detected in additional 500 breast cancer cases

scanned via HRM (high resolution melting) analysis of the respective exon, indicating that

germline mutations in TPT1 were rare events in breast cancer patients from our series.

2.5.2 The proposed role of TPT1 in ATM signaling

A direct involvement of TPT1 in ATM signaling and DNA repair was published in 2012265,

which has recently been supported by findings of RAD51 stability promotion by TPT1 and

retention of γH2AX and RAD51 foci following TPT1 knockdown267. While the antagonistic

effect of TPT1 on TP53 would suggest an oncogenic function, Zhang et al. (2012) have

reported that TPT1 interacts with TP53 to inhibit cellular proliferation in irradiated cells265.

Furthermore, low-dose IR enriched TPT1 in nuclei of normal human cells and its upregulation

appeared dependent on ATM kinase and DNA-PK. In that study, TPT1 formed a complex with

ATM, phosphorylated histone H2AX (γH2AX) and 53BP1, exhibited a protective effect on

irradiated cells and thus may play an important role in the maintenance of genomic integrity.

In this work, the question was addressed whether TPT1 immunoreactivity is also elevated in

our A-T LCLs and if a translocation and chromatin binding following irradiation, which would

indicate an involvement in the DDR, can be observed in our cellular systems. Figure 9A

shows one of the DDR related functions of TPT1 proposed by Zhang et al, 2012265, and

previous findings of this project showing elevated TPT1 levels in A-T cells compared to

wildtype LCLs477 (Figure 9B, C), which support data by Zhang et al., 2012. This result

confirmed the proposed elevation of TPT1 basal levels in A-T LCLs (160 % +/- 43) compared

to WT, as was also found in another A-T LCL culture with full blown AT477. However, no

induction after IR or changes in the intracellular distribution of TPT1 by ionizing radiation

were observed477. To clarify its role in ATM signaling and gain further insights into its

possible function as radiosensitivity marker, siRNA-mediated knockdown will be performed

in fibroblasts and breast epithelial cells (see section 4.1).

53

Figure 9 TPT1 in DNA repair modified from Zhang et al, 2012

265 and elevated levels in A-T LCLs

Panel A displays the role of TPT1 in ATM signaling as previously published, which was modified to show our approach of

analyzing TPT1 functions in our cellular systems, and its possible role as RS marker. Panel B shows a representative western

blot (experiment 3) of basal TPT1 levels in wildtype (WT) HA325 LCLs compared to A-T (ATM deficient) HA56 LCLs. Results of

densitometric analyses of TPT1 levels in A-T compared to WT LCLs are shown in panel C.

2.6 Hypothesis and aims of this project

Understanding the genetic background of RS is crucial not only to limit toxicity for

radiosensitive patients but also to improve cancer cure and maximize survival rates in the

90–95 % of patients, who are unlikely to suffer from severe and irreversible side-effects. Not

only the mutational status of patients, but also the specific end points of radiosensitivity are

variable. They depend on the site which is irradiated, ranging from skin telangiectasia to lung

pneumonitis, as well as on the volume effect of irradiated organs328.

Finding the genetic determinants of radiosensitivity has been a great challenge ever since its

first documentation. Candidate studies, gene expression analyses, as well as GWAS and

approaches to establish cellular toxicity testing did not agree on deriving biomarkers that

could be used in daily clinical routine to separate responders from non-responders prior to

radiation. A multitude of studies could relate clinically normal tissue toxicity to cellular

radiosensitivity already about 30 years ago328, building the basement of the relevance of

cellular radiation assays in radiooncology. The technical progress in identifying impairments

in the coding regions of the genome by next generation sequencing has enabled detection of

variants related to a wide range of diseases. With this approach, new insights can be gained

into the underlying mechanisms of radiosensitivity, which might overcome limitations of

and/or supplement traditional genetic mapping procedures, transcriptomics and GWAS

approaches. Exome sequencing has become a highly valuable and affordable tool in the last

years478 and given the well established finding that RS is associated with defects in DNA

repair, the analysis of RS patients through exome sequencing, firstly, has the power to

provide evidence for this association. Secondly, it holds the possibility to find new players in

the DNA damage response or other pathways, which have not previously been described.

Genetic material from patients with different cancers will be analyzed for superior RS

candidate genes, which might affect all cancer patients. Furthermore, cancer-specific RS

genes could be identified, as has been already indicated by previous studies addressing

prostate cancer479,480. As depicted in Figure 10, up to date research has not succeeded to

clarify which steps of the cellular DNA damage pathway are eventually involved in the failure

of normal tissue to withstand irradiation therapy. In this project, more insights into the

mechanistic and timely course of events leading to RS might be gained, which could

contribute to the quest of finding prognostic markers of adverse tissue reactions.

54

Figure 10 Cellular mechanisms following irradiation-induced DNA damage Simplified sequence of cellular events following DNA damage in the form of irradiation (displayed by red arrow) in normal

tissue (left panel) and radiosensitive tissue, indicating possible implication in subsequent steps by question marks (right

panel). The DNA damage response is constituted of sensors, for example H2AX (γH2AX in its active form) and the MRN-

complex consisting of MRE11A, RAD50 and NBN, transducers like ATM, effectors such as CHEK2 and different cellular target

options like apoptosis, senescence or DNA repair following cell cycle arrest, modified from Becker and Haferkamp481

. The

decision of cell fate is determined by the level of DNA damage, shown as triangular figure indicating choice of apoptosis by

high damage, senescence after high or medium damage and DNA repair after low damage, modified from Helton and

Chen482

.

This project consists of three parts and three different approaches to characterize individual

radiosensitivity will be made, see Figure 11. Given the hypothesis, that ATM signaling is a

predictive marker of RS, firstly, the RS candidate gene TPT1 will be analyzed with respect to

its possible influence on DSB recognition and repair. Knockdown experiments in skin

fibroblast and breast epithelial cell lines, resembling affected areas of IR treatment and

possible location of side-effect manifestation will be performed.

Secondly, the genetic signature of radiosensitivity will be analyzed by exome sequencing to

gain insights into the mutational background, which possibly leads to adverse effects in the

patients. Given the assumption that individual RS is – at least partly – determined by genetic

factors, variants affecting the coding regions of the genome, which are most likely associated

with functional defects, will be analyzed. The previously established relationship between

ATM signaling and clinical RS could be confirmed using exome sequencing.

55

Thirdly, as most side-effects affecting the body surface can be attributed to reactions in skin,

skin fibroblasts of breast cancer patients will be used for cellular radiosensitivity assays.

Analyses will be performed to address the question whether DSB repair capacity is given in

individual patient cells. These cultures were previously grown out of biopsies from non-

irradiated areas and may be a suitable model system for studying ex vivo irradiation effects,

especially late side-effects483. In order to provide an assay system which is not limited by

replicative senescence and can be used in experiments of extended duration in culture, such

as the colony survival assay, the primary cells need to be immortalized. If the hypothesis is

true, however, that the majority of radiation side-effects is determined by genetics, blood

lymphocytes from patients should also constitute a valuable model system484. Lymphocytes

are more easily gained samples, can be fast and comparatively simply immortalized and

represent a good model to investigate correlation of late side-effects with lethal

chromosomal aberrations424, so they resemble the second cellular system which will be used

in this project. However, the gold standard of radiosensitivity, namely the colony survival

assay, can best be performed in adherent cells by common experimental settings, which

emphasizes the importance of fibroblasts in this project.

Figure 11 Structure of this project

56

3 Material and methods

3.1 Material

3.1.1 Cell lines

Table 3 Cell lines used in this project as described in this thesis

Culture Type Origin/number Immortalization

status

ADP Human skin fibroblasts from a healthy

individual

Würzburg, DE,

self-established

SV40 large T

immortalized MCF10A Human breast epithelial from a healthy

individual485

ATCC, CRL-10317 Spontaneously

immortalized

HA325 Human whole blood lymphocytes from a

healthy individual

Hannover, DE,

self-established

EBV immortalized

HA56 Human whole blood lymphocytes from an

individual with classic A-T

Hannover, DE,

self-established

EBV immortalized

HCC1395 Human TNBC486, mutation in BRCA1, CDKN2A,

PTEN, TP53487,488 and NBN419

ATCC, CRL-2324 Cancer cells

HCC1937 Human TNBC489, mutation in BRCA1 and TP53

487,488 ATCC, CRL-2336 Cancer cells

HCC38 Human TNBC490, 486, mutation in CDKN2A

and TP53

ATCC, CRL-2314 Cancer cells

HA236 Human whole blood lymphocytes from

patient MC (mamma carcinoma) 3

Göttingen, DE

EBV immortalized

BJ5TA Human skin fibroblasts from a healthy

individual

ATCC, CRL-4001 TERT immortalized

MC1 TERT Human skin fibroblasts from patient MC1 Göttingen, DE/

Hannover*, DE,

self-established

TERT immortalized


Hannover*, DE,

self-established

TERT immortalized


Hannover*, DE,

self-established

TERT immortalized

*= Primary fibroblasts were obtained from Göttingen and immortalized with TERT during this

thesis in Hannover.

57

Previously published data was generated with cell lines given in Table 4473,485.

Table 4 Cell lines used in this project as previously published

Culture Type Origin/number Immortalization

status


individual with variant A-T

Hannover*, DE,

self-established

EBV immortalized



Hannover*, DE,

self-established

EBV immortalized


individual with clinical RS (hypopharynx

carcinoma)

Hamburg, DE/

Hannover**, DE,

self-established

EBV immortalized



Hannover*, DE,

self-established

EBV immortalized


healthy individual

Hannover*, DE,

self-established

EBV immortalized


individual with clinical RS (squamous cell

carcinoma)

Hamburg, DE/

Hannover*, DE,

self-established

EBV immortalized


individual with clinical RS (BC)

Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized



Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized



Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized



Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized



Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized



Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized


individual with clinical RS (rectum

carcinoma)

Würzburg, DE/

Hannover**, DE,

self-established

EBV immortalized


individual with clinical chemoradio-

sensitivity (BC)

Magdeburg, DE/

Hannover**, DE,

self-established

EBV immortalized


individual with clinical

chemoradiosensitivity (prostata carcinoma)

Magdeburg, DE/

Hannover**, DE,

self-established

EBV immortalized

58


individual with clinical chemoradio-

sensitivity (BC)

Magdeburg, DE/

Hannover**, DE,

self-established

EBV immortalized


individual with RAD50 deficiency

Hannover*, DE,

self-established

EBV immortalized


healthy individual

Hannover*, DE,

self-established

EBV immortalized


individual with classic A-T

Hannover*, DE,

self-established

EBV immortalized

MC3 Human skin fibroblasts from patient MC3 Göttingen, DE Primary

MC7 Human skin fibroblasts from patient MC7 Göttingen, DE Primary

*= Primary blood lymphocytes were immortalized with EBV in the Molecular Gynaecology unit, Medical School

Hannover, Hannover, mostly by Britta Wieland.

**= Primary blood lymphocytes were obtained from different german hospitals and immortalized with EBV in

the Molecular Gynaecology unit, Medical School Hannover, Hannover, mostly by Britta Wieland.

3.1.2 Antibodies

3.1.2.1 Primary antibodies

Table 5 Primary antibodies

Antigen Host Western

blot

Immuno-

cytochemistry

Antigen

size [kDa]

Company, catalogue number,

concentration

53BP1 Rabbit – 1:200 430 Bethyl Laboratories, A300-272A,

1 mg/ml

ABL1 Mouse 1:750 – 174 BD, 554148, 0.5 mg/ml

ABL1 Rabbit 1:750 – 174 Santa Cruz, K12 sc-131, kindly

provided by Dr. Koch, MHH

p-CHEK2

(Ser19)

Rabbit 1:500–1:1000

– 62 Cell signaling, 2666

p-KAP1

(Ser824)

Mouse 1:2000–1:5000

– 130 Bethyl Laboratories, A300-767A,

0.2 mg/ml

RAD50 Mouse 1:500 – 154 Abcam, ab 89, 1.38 mg/ml

RAD51 Mouse – 1:200 37 Genetex, GTX70230, 1.39 mg/ml

SP1 Rabbit 1:500 – 81 Santa Cruz, sc-59, 100 µg/ml;

ß-actin Mouse 1:3000 – 37 Sigma-Aldrich Aldrich, A5441,

2 mg/ml

TERT Rabbit 1:500 – 127 Biorbyt, orb215529, Lot: DF414

TPT1 Rabbit 1:50000 1:250 20 Abcam, ab133568

TPT1 Rabbit 1:750 1:250 20 Abcam, ab37506, 1 mg/ml

TPT1 Rabbit – 1:800 20 Proteintech 10824-1-AP, Lot:1

yH2AX

(Ser139)

Mouse – 1:300 17 Millipore/Upstate, 05-636,

1 mg/ml

yH2AX

(Ser139)

Rabbit – 1:300 17 Epitomics, 2212-1, Lot: YE080802R

59

3.1.2.2 Secondary antibodies

Table 6 Secondary antibodies

Antigen Host Western blot Immuno-

cytochemistry

Company, catalogue

number,

concentration

Alexa Fluor anti-

mouse IgG 546

Goat – 1:200 Invitrogen, A-11018;

Lot: 1817158,

2 mg/ml

Alexa Fluor anti-

rabbit IgG 488

Goat – 1:200 Invitrogen, A-11070;

Lot: 161 8692,

2 mg/ml

FITC-conjugated

anti-mouse IgG

antibody

Goat – 1:200 Zymed, 62-6511,

1 mg/ml

Alexa Fluor anti-

rabbit IgG 546

Goat – 1:200 Invitrogen, A11071,

Lot: 1789904 2 mg/ml Anti-mouse Sheep 1:10000 – Amersham, NA9310

Anti-rabbit Donkey 1:10000 – GE Healthcare,

NA9340

3.1.3 Plasmids and kits

Table 7 Plasmids and kits

Plasmid/kit Company/catalogue

number (concentration)

Registered office/

distributor

Human TERT, pGRN145 ATCC MBA-141 Manassas, USA

Pmax GFP vector Lonza (1 µg/ml) Cologne, DE

RNAimax transfection kit Lipofectamine

RNAiMAX

Invitrogen, 13778 Karlsruhe, DE

EndoFree Plasmid Purification kit Mega Qiagen, 12381 Hilden, DE

Senescence β-Gal Staining kit Cell Signalling, 9860S Danvers, US

P2 Primary Cell 4D-Nucleofector X Kit Lonza, V4XP-2024 Cologne, DE

60

3.1.4 Chemicals

Table 8 Chemicals

Chemicals Company Registered office/

distributor

0.1 % gelatin from bovine skin, in

0.9 % NaCl

Gelatin, Sigma

NaCl, Sigmaultra

Kindly provided by

Susanne Alfken, AG

Cantz, REBIRTH, MHH

30 % Hydrochloric acid (HCl) Roth Karlsruhe, DE

4′,6-Diamidino-2-phenylindole

(DAPI)

Invitrogen Karlsruhe, DE

Agarose (ultra-pure) Invitrogen Karlsruhe, DE

Ammonium persulfate Bio-Rad Munich, DE

Aprotinin Serva, Feinbiochemika Heidelberg, DE

ATM-Inhibitor Ku55933 KuDos Pharmaceuticals Cambridge, UK

Bis-acrylamide 2 % Bio-Rad Munich, DE

Bovine Serum Albumin (BSA) New England Biolabs Ipswich, US

Bromophenolblue Sigma-Aldrich Steinheim, DE

Chloroform Roth Karlsruhe, DE

Coomassie Roti-Blue (5x) Roth Karlsruhe, DE

Crystal violet solution 1 % Sigma-Aldrich Steinheim, DE

Developer solution Kodak Sigma-Aldrich Steinheim, DE

Dimethyl sulfoxide (DMSO) Applichem Darmstadt, DE

Disodium hydrogenphosphate Roth Karlsruhe, DE

Dithiothreitol (DTT) Sigma-Aldrich Steinheim, DE

Ethanol, absolute J. T. Baker Deventer, NL

Ethanol, uvasol Merck Darmstadt, DE

Ethylenediaminetetraacetate

(EDTA)

Sigma-Aldrich Steinheim, DE

Ethyleneglycoltetraacetate (EGTA) Sigma-Aldrich Steinheim, D

Fixing solution Kodak Sigma-Aldrich Steinheim, DE

Formaldehyde 37 % Roth Karlsruhe, DE

Glycerol Merck, AppliChem Darmstadt, DE

Glycogen Affymetrix California, US

Hydrogen peroxide Merck Darmstadt, DE

HPLC water J. T. Baker Deventer, NL

Isopropanol Roth, Th. Geyer Karlsruhe, DE, Hamburg,

DE.

Leupeptin Serva, Feinbiochemika Heidelberg, DE

L-Glutamine PAA Pasching, AT

Luminol (5-Amino-2,3-dihydro- 1,4-

phthalazinedione)


Mercaptoethanol Sigma-Aldrich Steinheim, DE

Methanol Merck Darmstadt, DE

My budget dNTP Set BioBudget Krefeld, DE

Normal goat serum (NGS) Dianova Hamburg, DE

NP-40 (NonidetP-40) Sigma-Aldrich Steinheim, DE

p-Coumaric acid Merck Darmstadt, DE

61

Phenol Sigma-Aldrich Steinheim, DE

Phenol/chloroform/isoamyl alcohol

(25:24:1)

AppliChem Darmstadt, DE

Phenylmethansulphanylfluoride

(PMSF)


Polyethylene glycol (PEG) 8000 Merck Darmstadt, DE

Ponceau S solution AppliChem Darmstadt, DE

Potassium chloride Roth Karlsruhe, DE

Potassium dihydrogen phosphate AppliChem Darmstadt, DE

Prolong Gold Invitrogen Karlsruhe, DE

Protein Assay Dye Reagent

Concentrate

Bio-Rad Munich, DE

Sodium carbonate AppliChem Darmstadt, DE

Sodium chloride Roth Karlsruhe, DE

Sodium dodecylsulfate (SDS) Roth Karlsruhe, DE

Sodium fluoride Sigma-Aldrich Steinheim, DE

Sodium hydrogen carbonate Roth Karlsruhe

Sodium hydroxide pellets AppliChem Darmstadt, DE

Sodium metavanadate Sigma-Aldrich Steinheim, DE

Sodium pyruvate Biochrom Berlin, DE

Sucrose Sigma-Aldrich Steinheim, DE

Tetramethylethylenediamine

(TEMED)

Bio-Rad Munich, DE

Tris Roth Karlsruhe, DE

Tris HCl Roth Karlsruhe, DE

Triton-X-100 Sigma-Aldrich Steinheim, DE

Trypanblue Sigma-Aldrich Steinheim, DE

Tween 20 Sigma-Aldrich Steinheim, DE

Xylene cyanol Merck Darmstadt, DE

Hepes 2-[4-(2-

hydroxyethyl)piperazin-1-

yl]ethanesulfonic acid


Form amide Merck Darmstadt, DE

Boric acid Merck Darmstadt, DE

Polyethylene glycol (PEG) 8000 Merck Darmstadt, DE

Sodiumacetate anhydrous Sigma-Aldrich Steinheim, DE

Glycine Roth Karlsruhe, DE

β-Glycerophosphate Merck Darmstadt, DE

62

3.1.5 Enzymes and siRNAs

Table 9 Enzymes and siRNAs

Enzyme/siRNA Company/number Registered office/

distributor

Benzonase EMD Millipore, 70664 Billerica, US

DNase I Roche, 92161121 Basel, CH Hot Star Taq Polymerase + buffer Qiagen, 1007837 Hilden, DE.

Proteinase K AppliChem Darmstadt, DE

Scrambled siRNA (control) Ambion/Applied Biosystems

International

Waltham, US

siRNA against TPT1, sense

(5’3’:AAGGGAAACUUGAAGAACAtt) antisense

(5’3’:UGUUCUUCAAGUUUCCCUUtg)

Ambion/Applied Biosystems

International,

AM16708A, 289422

Waltham, US


(5’3’:GGAAACAAGUUUCACAAAAtt) antisense

(5’3’:UUUUGUGAAACUUGUUUCCtg)


International, AM16708A, 13153

Waltham, US


(5’3’:GGGAAACUUGAAGAACAGAtt) antisense

(5’3’:UCUGUUCUUCAAGUUUCCCtt)


International,

AM16708A, 284697

Waltham, US

TopTaq Polymerase + buffer Qiagen, 200205 Hilden, DE

Trypsin/EDTA 0.25 % Biochrom Berlin, DE

3.1.6 Medium and other materials

Table 10 Medium and other materials used in this work

Material Company/number Registered office/

distributor

1 Kb Plus DNA Ladder Invitrogen Karlsruhe, DE

Dulbecco's modified Eagle‘s medium

(DMEM)

Sigma-Aldrich, 6546 Steinheim, DE

Dulbecco's modified Eagle‘s medium (DMEM)

Gibco, 21969-035 California, US

Dulbecco's modified Eagle‘s medium (DMEM) without Na-Pyruvate

Sigma-Aldrich, 6171 Steinheim, DE

Fetal calf serum (FCS) Biochrom Berlin, DE

Gel loading dye GelRed Biotium California, US

Hygromycin B 50 mg/ml Invitrogen, 10687010 Carlsbad, DE

Marvel milk powder Premier Foods plc St. Albans, UK

Medium 199 Sigma-Aldrich, M4530 Steinheim, DE

MEGM (Mammary Epithelial Cell

Growth Medium)

Lonza, CC-3151 Basel, BE

MEGM SingleQuot Kit Suppl. & Growth

Factors

Lonza, CC-4136 Basel, BE

Mynox Gold Minerva Biolabs Berlin, DE

63

NanoPOP6 polymer NimaGen Rotterdam, NL

Opti-Mem Gibco/Life Technologies Carlsbad, US

Penicillin/Streptomycin PAA Pasching, AT

Pierce Super-Signal West Dura Pierce/Thermo Scientific Rockford, US

Primer Eurogentec Seraing, BE

RPMI 1640 + L-Glutamine Gibco/Life Technologies,

Sigma-Aldrich

Carlsbad, US,

Steinheim, DE

Western Bright Quantum Biozym,

Advansta

Hessisch Oldendorf,

DE,

Menlo Park, US

3.1.7 Buffers and solutions

Table 11 Buffers and solutions prepared and used in this project

Protein lysate preparation and SDS-PAGE DNA isolation, PCR, sequencing, agarose gel

electrophoresis, immunocytochemistry, colony

survival assay, common solutions and western

blot

Whole cell lysate

buffer

50 mM Tris pH 7.4 10x STE buffer 0.5 M Tris-HCl

150 mM NaCl 1 M NaCl

2 mM EGTA 0.01 M EDTA

2 mM EDTA Fill up to 1 l with ddH2O

(pH 7,5)

25 mM NaF

25 mM ß-glycerophosphate Proteinase K reaction

mix (per sample)

190 μl sterile HPLC grade ddH2O

0.1 mM Na3VO4 150 μl proteinase K (10 mg/ml)

0.1 mM PMSF 40 μl 10x STE

5 µg/ml leupeptin 20 μl 10 % SDS

1 µg/ml aprotinin

0.2 % (v/v) Triton X-100 1x TE/DNA

suspension buffer

10 mM Tris pH 8.0

0.3 % (v/v) NonidetP-40 0.1 mM EDTA

Cellular

fractionization

buffer A

50 mM Hepes (pH 7.4) Agarose loading dye

(5x)

0.25 %

bromophenolblue

10 mM KCl 0.25 % xylene cyanol

1 mM EDTA 100 ml 100 % form

amide

1 mM EGTA

1 mM DTT 1x TBE buffer 890 mM Tris

0.5 % NonidetP 890 mM boric acid

0.1 mM PMSF 20 mM EDTA

5 µg/ml leupeptin Fill up to 1 l with ddH2O

64

1 µg/ml aprotinin

PEG 26.2 g PEG 8000

Cellular frac-

tionization buffer

B

1.7 M sucrose 0.12 g MgCl2

50 mM Hepes (pH 7.4) 0.42 g C2H3NaO2

10 mM KCl, Fill up to 100 ml with

ddH2O

1 mM EDTA

1 mM EGTA Fixation solution for

immunocytochemistr

y and colony survival

assay

2 % (w/v) sucrose

1 mM DTT 3 % (w/v) formaldehyde

in PBS

0.5 % NonidetP

0.1 mM PMSF ICC preextraction

buffer

10 mM Hepes (pH 6.8)

5 µg/ml leupeptin 100 mM NaCl

1 µg/ml aprotinin 300 mM sucrose

3 mM MgCl2

Cellular

fractionization

buffer C

10 % glycerol, 1 mM EGTA

50 mM Hepes (pH 7.4) 0.5 % triton X-100

400 mM KCl, in 1xPBS

1 mM EDTA

1 mM EGTA 10x PBS 80 g NaCl

1 mM DTT 2 g KCl

0.1 mM PMSF 11,5 g Na2HPO4

5 µg/ml leupeptin 2 g KH2PO4

1 µg/ml aprotinin Fill up to 1 l with H2O

20 % SDS 200 g SDS 1x PBS 100 ml 10x PBS

Fill up to 1 l with ddH2O 900 ml ddH2O

10 % APS 100 g APS 10x carbonate buffer 0.1 M NaHCO3

Fill up to 1 l with ddH2O 30 mM Na2CO3

Fill up to 1 l with ddH2O

Separation gel

buffer

1 M Tris HCl

Fill up to 1l with H2O 1x carbonate buffer

(working solution)

100 ml 10x carbonate

buffer

pH 8.7 with HCl 700 ml ddH2O

200 ml MeO4

Stacking gel buffer 0.5 M Tris HCl 1.8 ml 20 % SDS

Fill up to 1 l with H2O

pH 6.8 with HCl 1x PBS-T 1x PBS

0.05 % (v/v)

tween 20

SDS loading buffer 1 M Tris HCl pH 6.8

65

(5x)

14.25 % (w/v) SDS Blocking buffer 1x PBS-T

47.5 % (v/v) glycine 5 % (w/v) Marvel milk

powder

14.25 % (v/v) β-

glycerophosphate

1.4 % (w/v)

bromophenolblue

Luminol, 250 mM 440 mg luminol

Fill up to 10 ml with DMSO

10x GTS 1.9 M glycine

0.25 M Tris p-Coumaric acid,

90 mM

150 mg p-coumaric acid

1 % (w/v) SDS Fill up to 10 ml with DMSO

Fill up to 1 l with ddH2O and dilute to 1x GTS with

ddH2O

Luminol detection

reagent, solution 1

500 μl luminol (250 mM)

220 μl p-coumaric acid

(90 mM)

Fill up to 45 ml with

ddH2O

5 ml Tris HCl pH 8.7

Luminol detection

reagent, solution 2

100 mM Tris HCl pH 8.7

30.5 μl H2O2

3.1.8 Devices and disposables

Table 12 Devices and disposables

Equipment/disposables Company/number Registered office/distributor

4D-Nucleofector core unit Lonza, AAF-1001B Cologne, DE

4D-Nucleofector X-unit Lonza, AAF-1002X Cologne, DE

6-well plate Nunc/Thermo Scientific Braunschweig, DE

6-well plate Eppendorf Hamburg, DE

Agarose gel tank

Peqlab 40-1410

Peqlab Erlangen, DE

Agarose gel tank

Horizon58

Life technologies California, US

CO2 incubator Heracell 240i Thermo Scientific Braunschweig, DE

Cell culture flasks (T25 cm2,

T75 cm2 & T175 cm

2)

Nunc/Thermo Scientific, Rockford, US

Cell scraper Sarstedt Nümbrecht, DE

66

Centrifuge Universal 320R Hettica Tuttlingen, DE

MegaFuge 16R Thermo Scientific Braunschweig, DE

Collagen I-coated 6-well plate BD Falcon/Corning,

#354400

Kindly provided by Katja

Borns/Dr. Bianca Schröder-

Heurich

Confocal laser scanning

microscope FV 1000

Olympus Hamburg, DE

Menzel cover glasses Thermo Scientific Braunschweig, DE

Cryo vial 2 ml Greiner Frickenhausen, DE

Disposable gloves Kimberly-Clark Roswell, US

Disposable needles 27G Braun Melsungen, DE

Disposable pipettes Sarstedt Nümbrecht, DE

Disposable syringes Braun Melsungen, DE

Elektrophoresis chamber Peqlab Munich, DE

Fluorescence microscope DMI

6000B

Leica Heidelberg, DE

Gel documentation

Transilluminator UXT-20M-8E

INTAS

Bioview Rehovot, IL

Gel documentation

Gel Image System

INTAS GDS

Vilber Lourmat Eberhardzell, DE

Genetic Analyzer 3100-Avant,

instrument protocol

Seq_50 cm_POP6_Set_E

Applied Biosystems Foster City, US

Rotofix 32 A Hettich, 1324 Tuttlingen, DE

Rotator Thermo Scientific,

75003652

Braunschweig, DE

Heatblock Eppendorf Hamburg, DE

Hyperfilm ECL GE Healthcare Chalfont St Giles, UK

Ice machine Ziegra Isernhagen, DE

Incubator Heraeus/Thermo

Scientific

Braunschweig, DE

Kleenex tissues Kimberly-Clark Roswell, US

Laminar flow cabinet safe, 2020 Thermo Scientific Braunschweig, DE

Linear accelerator Elekta Synergy, Siemens Munich, DE

Microscope Slides Super Frost

Plus

Thermo Scientific Braunschweig, DE

Mr. Frosty (cryocontainer) Nalgene/Thermo Fisher

Scientific

Waltham, US

NanoDrop 8000 Peqlab Erlangen, DE

Neubauer cell counting chamber ASSISTENT (Hecht AG) Sondheim v. d. Rhön, DE

Parafilm Bemis Wisconsin, US

67

PCR-performance 96 well Sarstedt Nümbrecht, DE

pH meter Mettler Toledo Columbus, US

Photometer Eppendorf Hamburg, DE

Pipet boy Brand Wertheim, DE

Pipette 0.5–10 μl Eppendorf Hamburg, DE

Pipette 2 μl–20 μl Peqlab Erlangen, DE




Pipette 200 μl–1000 μl Gilson Middelton, US

Pipette tips (10 μl, 200 μl,

1000 μl)

Sarstedt Nümbrecht, DE

Capillary tips Biozym Hessisch Oldendorf, DE

Plastic film Omnilab Bremen, DE

Power supply peqPOWER Peqlab Erlangen, DE

Power supply Power Pack P25 Biometra Göttingen, DE

Elektrophoresis power

supply Consort EV202


Precision Plus Protein All

Blue Standards

Bio-Rad Laboratories Munich, DE

Scalpel Feather,

pfm medical AG

Osaka, J,

Cologne, DE

Scanner LiDE 110 Canon Middlesex, UK

Autoclavable glass bottles

100 ml, 250 ml, 500 ml, 1 l, 2 l

VWR Radnor, US

Shaker Biosan Riga, LV

Shrink-wrap device Serverin Folio Sundern, DE

Thermal cycler

PTC-200

MJ Research,

Biozym

Quebec, CA,

Hessisch Oldendorf, DE

Transfer unit Peqlab Erlangen, DE

UVette Eppendorf Hamburg, DE

Vortex Genie-Mixer Jürgens Bremen, DE/Hannover, DE

Scales Kern, Feinwaage? Balingen, DE

Water bath Biosan,

Jürgens

Riga, LV,

Bremen, DE/Hannover, DE

Whatman paper Whatman Maidstone, UK

X-ray cassette GE Healthcare Chalfont St. Giles, UK

Greiner cell star tubes, 15 ml Greiner, 188271 Frickenhausen, DE

Greiner cell star tubes, 50 ml Greiner, 227261 Frickenhausen, DE

Autoclaves Jürgens,

Systec

Bremen, DE/Hannover, DE,

Linden, DE

Nitrocellulose-membrane, Amersham Freiburg, DE

68

0.2 µm

Sterile filter unit (0.45 μm, 0.2 μm)

Sartorius Göttingen, DE

Reaction tube, 0.5 ml Sarstedt Eppis Nümbrecht, DE

Pipette 0. 5 μl–10 μl Eppendorf Hamburg, DE

Comb, 20 slots (0.8 mm) Peqlab Erlangen, DE

Reaction tube, 1.5 ml Sarstedt Eppis Nümbrecht, DE

3.1.9 Software

Table 13 Software used in this project

Software Company/version

GraphPad prism GraphPad, version 5.01, San Diego, US, 5.01

ImageJ Wayne Rasband, National Institutes of Health, US,

version 1.51

Venny Venn's diagrams drawing tool for comparing up to four

lists of elements. Version 2.0

http://bioinfogp.cnb.csic.es/tools/venny/

ApE-A plasmid Editor M. Wayne Davis, version 2.0.47

MaxEntScan MaxEntScan: score5ss for human 5' splice sites,

http://genes.mit.edu/burgelab/maxent/Xmaxentscan_sco

reseq.html

Leica Application Suite

Advanced Fluorescence

Leica, version 4.0.0.11706

Olympus software FluoViewStart FV10, Version 4.2b

Ingenuity Pathway Analysis Qiagen, version 460209M

Reactome browser491 492

Version 3.5, https://reactome.org/PathwayBrowser/

NextGene next generation

sequencing software

Soft Genetics, version 2.4.2

Sequencing analysis software Applied Biosystems, version 5.1.1, analysis protocol

POP6_BDTv1.1

3.1.10 Gene Nomenclature

HUGO gene nomenclature committee (HGNC) defined the gene nomenclature of all gene names

referred to in this thesis (http://www.genenames.org/). For reference gene sequences the website

of the National Center for Biotechnology Information (www.ncbi.nlm.nih.gov) was used.

3.2 Cell culture methods

3.2.1 Culture, counting and cryopreservation of cells

For experiments in section 4.1, SV 40 large T immortalized primary fibroblasts of a healthy individual

(ADP, kindly provided by Prof. Detlev Schindler, Würzburg, DE) and normal human breast epithelial

cells (MCF10A, obtained from ATCC, CRL-10317) were used. ADP cells were cultured in DMEM with

10 % FCS, 500 U/ml penicillin (pen), 0.5 mg/ml streptomycin (strep) and 2 mM L-glutamine (gln) and

http://www.genenames.org/

69

MCF10A cells were grown in MEGM medium, supplemented with single quots MEGM according to

the manufacturer’s instructions. Furthermore, the triple negative breast cancer cell lines HCC1937

(ATCC CRL-2336), HCC1395 (ATCC, CRL-2324), and HCC38 (ATCC CRL-2314) were used and cultured in

RPMI medium supplemented with 15 % FCS, 500 U/ml pen, 0.5 mg/ml strep and 2 mM gln.

In section 4.3, fibroblasts of breast cancer patients with clinical radiosensitivity (RTOG 3) and a

normal wildtype fibroblast cell line (BJ5TA, immortalized with TERT) were used. BJ5TA cells were

obtained from ATCC (CRL-4001) and cultured in a mixture of four parts Dulbecco's Modified Eagle’s Medium and one part Medium 199 with 10 % FCS, 500 U/ml pen, 0.5 mg/ml strep and 2 mM gln.

Primary cultures were obtained from Margret Rave-Fränk, Göttingen, DE, and the radiosensitive cell

lines MC1, MC3 and MC7 were TERT-immortalized using nucleofection (see section 3.2.2) and

subsequently treated against mycoplasma (see section 3.2.3). Both, primary and immortalized

cultures, were grown in DMEM without Na-pyruvate with 10 % FCS, 500 U/ml pen, 0.5 mg/ml strep

and 2 mM gln. Because the TERT plasmid includes resistance against the selection marker

hygromycin B, the culture medium of BJ5TA and MC TERT cells was supplemented with hygromycin B

(10 μg/ml) to promote TERT-expression and to eliminate all the cells which have not obtained the

plasmid. All cells were grown at 37 °C in a humidified atmosphere supplemented with 5 % CO2.

Passaging of all adherent cell lines was performed after a confluence of 70–90 % was

reached and medium was changed twice a week and/or one day after passaging. For

splitting the cells, the medium was removed, the cells were washed with sterile 1x PBS and

incubated with 1x trypsin/EDTA ranging from 1 min to 5 min (MCF10A). After the

detachment of cells from the flask was verified by light microscopy, a surplus of culture

medium was added for stopping the trypsin activity. The cell suspension was transferred into

a reaction tube (15 or 50 ml, respectively) and centrifuged for 5 min at 200xg at room

temperature. After discarding the supernatant and resuspending the pellet in culture

medium, the cells were released into new cell culture flasks depending on the expansion

rate.

Lymphoblastoid cells (LCLs), which were previously generated from whole blood samples of

different patients and immortalized with Epstein-Barr virus (EBV) by Britta Wieland, were

cultured in RPMI medium supplemented with 15 % FCS, 500 U/ml pen, 0.5 mg/ml strep and

2 mM gln. The suspension cells were cultured in upright T25 cell culture flasks and passaged

through transferring dilutions of 1:4–1:8 of cell suspension in fresh medium to new flasks. If

cells were in critical condition, the content of the whole flask was centrifuged at 200xg for

5 min at room temperature, the pellet was resuspended in fresh medium and transferred to

a new flask.

Long-term storage of cells can be achieved through cryopreservation in liquid nitrogen and

was performed in special freezing medium containing DMSO for adherent cells, which

prevents crystal formation and subsequent cell damage493. Cryopreservation conditions

varied between cultures and composition of freezing media are given in Table 14. For

cryopreservation, cells were harvested in the same way as described for passaging, however,

cell pellets were resuspended in 1–1.5 ml of freezing medium and quickly transferred into

cryovials, which were placed into freezing containers immediately and stored in a –80 °C

freezer overnight. The cryovials were subsequently transferred to liquid nitrogen for

extended storage. Thawing of cells was performed by warming up the cryovial at 37 °C,

70

quickly transferring the contents to a reaction tube with 5 ml of prewarmed culture medium

and immediate centrifugation at room temperature for 5 min at 200xg. The pellet was

resuspended and transferred to a culture flask with fresh medium, which was changed again

after 24 h, similarly to the passaging procedure.

Cells were counted using trypan blue staining and a Neubauer counting chamber with a light

microscope. The harvested cells were resuspended in culture medium and 80 μl of cell

suspension was transferred to a 1.5 ml reaction tube. Trypan blue staining solution (20 μl)

was added for identifying viable cells and in order to distinguish living from dead cells, which

were excluded from the counting. Straight away, the cell counting chamber was filled with

this mixture and two segments were evaluated. The cell number per ml was calculated using

the following equation:

Cells

ml=

Mean

4x dilution factor x chamber factor

Mean = Mean of cell numbers determined in two counted segments, dilution factor= 1.25; chamber

factor= 10000

Table 14 Culture and cryopreservation conditions of cell cultures

Culture Growth medium Cryopreservation medium

ADP DMEM with 10 % FCS, 500 U/ml pen,

0.5 mg/ml strep, 2 mM L-gln

Normal growth medium with

10 % DMSO

MCF10A MEGM (Mammary Epithelial Cell Growth Medium) with SingleQuot Kit Suppl. & Growth

Factors

Normal growth medium with 10 % DMSO

HCCs RPMI with 10 % FCS, 500 U/ml pen, 0.5 mg/ml

strep, 2 mM L-gln


5 % DMSO

LCLs RPMI with 15 % FCS, 500 U/ml pen, 0.5 mg/ml

strep, 2 mM L-gln


20 % FCS and 10 % glycerol

BJ5TA DMEM with 10 % FCS, 500 U/ml pen,

0.5 mg/ml strep, 2 mM L-gln


60 % FCS and 10 % DMSO

MCs (primary/TERT

immortalized)

DMEM without Na-pyruvate with 10 % FCS,

500 U/ml pen, 0.5 mg/ml strep, 2 mM L-gln


20 % FCS and 8 % DMSO

3.2.2 Telomerase reverse transcriptase immortalization

Immortalization has been defined as the ability to yield cell lines that can be serially

cultivated without undergoing crisis494. Primary fibroblasts naturally undergo differentiation

or senescence in culture after repeated passaging495-497, and the TERT (telomerase reverse

transcriptase) activity is silenced upon differentiation in many cell types498. TERT is a

specialized reverse transcriptase that catalyzes the addition of telomeric DNA repeats to the

ends of chromosomes499, thus preventing premature aging and loss of genetic material500.

Mutations in the TERT gene are the most common mutations in many cancers and arise early

during the transformation process498. As cancer cells escape aging through TERT activation,

artificial introduction of TERT into primary skin fibroblasts can provide a cell line that is not

subject to aging- or differentiation-associated proliferation limitation. In contrast to one of

the other prominent immortalization protocols through transformation with oncogenes such

71

as simian virus 40 large T antigen (SV40 large T), TERT does not interfere with TP53 and thus

exerts less influence on elevated chromosomal instability501 502.

The plasmids containing TERT and GFP (green fluorescent protein) were obtained from ATCC

(pGRN145, # MBA-141) and Lonza (supplemented with P2 primary cell kit, #V4XP-2024),

respectively. They were amplified and purified using endotoxin-free solutions and

disposables and were kindly provided by Dr. Kristine Bousset, Molecular Gynaecology unit,

Clinics of Obstetrics and Gynaecology, Hannover Medical School. The nucleofection device

was kindly provided by Prof. Axel Schambach, Department Experimental Hematology,

Hannover Medical School. The immortalization procedure with TERT was established on

primary fibroblasts, using the nucleofection programs “CF-158” and “DS-138” and a

concentration range of plasmid DNA from 2–4 µg/ml. Subsequently, plasmid concentrations

of 4 µg/ml of TERT and 2 µg/ml of GFP, respectively, were chosen. Hygromycin B titration

was performed to determine the lethal concentration necessary to kill the non-transfected

cells. Short-term high-dose selection with hygromycin B was tested versus long-term

medium dose selection until a concentration of 10 µg/ml hygromycin B was chosen for

application of medium/long-term selection as well as follow-up culture conditions.

For nucleofection, the P2 primary cell kit (Lonza, #V4XP-2024) was used with 100 µl single

cuvettes. 6-well plates were prepared with cell culture medium and warmed to 37 °C prior to

nucleofection. Cells were harvested at subconfluent conditions (maximum 70 % confluency)

and counted as described in subsection 3.2.1. 0.5x106 cells were prepared for each

experiment and centrifuged at 90xg for 10 min at room temperature. The supernatant was

carefully removed and the pellet was resuspended in 100 µl room temperature

nucleofection solution consisting of 82 µl nucleofector solution, 18 µl supplements and

corresponding plasmids (2 µg of GFP and 4 µg of TERT plasmid). Following bubble-free

transfer into the nucleocuvette, the program was immediately initiated. After completion of

the program, the nucleocuvette was placed into the cell culture incubator for 5 min. 500 µl

of prewarmed culture medium was added to the cells using the pipettes supplied with the

kit. The cell suspension was carefully mixed and transferred to the 6-well plates containing

1.5 ml culture medium, and placed into the incubator for recovery. 24 h post transfection,

the cells were analyzed for the development of GPF fluorescence as reporter using a

fluorescence microscope.

Selection with 10 µg/ml hygromycin B was started at 24–48 h after nucleofection, depending

on the conditions of the cells, and medium was changed back to normal growth medium

after the majority of non-transfected cells had died during the selection process. For the first

1–2 weeks, the medium was changed every day when a prominent number of cells had

undergone cell death. The selection pressure was maintained through subsequent boosts of

hygromycin B treatment, until a fully immortalized culture was obtained. If cells did not grow

well, they were transferred to new cell culture flasks in order to stimulate proliferation. Cells

in outgrowing colonies were separated and transferred to larger culture flasks. After the

respective recovery phases, the cells were tested for TERT levels by western blot and culture

conditions with hygromycin B were maintained if presence of TERT was confirmed.

3.2.3 Mycoplasm treatment

Cells, which were positively tested for mycoplasm contamination by routine PCR

(polymerase chain reaction) testing, were subjected to mycoplasm treatment with Mynox

72

Gold reagent according to the manufacturer's instructions. After confirmation of mycoplasm

clearance by PCR, cells were routinely tested for re-infection every three months or

additionally after freezing and thawing cycles.

3.2.4 Reverse transfection and siRNA silencing

siRNA-mediated knockdown is a well established tool for functional analyses aiming at

focusing on individual genes within living cell cultures. For knockdown experiments in

section 4.1, siRNAs capable of targeting TPT1 were obtained from Ambion (AM16708A

#284697, #13153, #289422) and were used as steady mixture265. Scrambled (scr) siRNA

duplex (Ambion) was included as control, and reverse transfection with Lipofectamine

RNAiMAX was used to apply siRNAs to subconfluent cells 48–72 h prior to analysis

(irradiation), as recommended by the manufacturer. This transfection reagent utilizes

cationic liposomes to deliver the siRNA and can yield high efficiency also in hard-to-transfect

cells. Reactions were performed in 6-well plates with 5x105 cells per well for MCF10A and

8x105 cells per well for ADP, respectively, which were harboured at subconfluent conditions

and counted as described in subsection 3.2.1. During the transfection, normal culture

medium without antibiotics was applied. Before complexion, RNAi duplexes and

lipofectamine reagent were diluted in Opti-MEM I Reduced Serum Medium. 10 pmol of each

siRNA was diluted in 100 µl Opti-MEM in the well of the culture plate and gently mixed. 5 µl

of Lipofectamine RNAiMAX was added, gently mixed and incubated for 15 min at room

temperature. 500 µl of cells were diluted in growth medium without antibiotics, applied to

the well in a total volume of 2.5 ml, gently mixed and incubated for 48 h. As knockdown was

confirmed to be complete after 48 h (see Supplementary figure S-1B), this incubation period

was chosen for TPT1 silencing.

3.2.5 ATM inhibition

For ATM inhibition experiments shown in Supplementary figure S-2, the cells were treated

with different concentrations (2 μM or 10 μM in DMSO) of the ATM inhibitor Ku55933 (KuDos Pharmaceuticals, Cambridge, UK) one hour before IR. Control cells were treated with

DMSO only.

3.2.6 Irradiation

Cells were usually seeded one day before irradiation (except for knockdown experiments

that were performed 48 h prior to IR treatment) and supplemented with fresh culture

medium shortly before IR. Ionizing radiation with doses between 60 mGy–8 Gy was applied

to the cells at room temperature using an Elekta Synergy accelerator (Siemens, Munich, DE).

The energy of the X-radiation was 6 MVX and a dose-rate of 400 MU/min was applied to the

cells.

3.2.7 Lysate preparation and immunoblotting

For preparation of protein extracts, cells were harvested by trypsination as described in

subsection 3.2.1, and all subsequent steps were performed on ice to avoid degradation of

proteins. Pellets were washed once in 5 ml ice cold 1x PBS and centrifuged for five minutes

at 4 °C. Subsequently, pellets were resuspended in 1 ml 1x PBS and centrifuged eight

minutes at 1000xg (3000 rpm) and 4 °C.

http://www.dict.cc/englisch-deutsch/X-radiation.html

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3.2.7.1 Generation of whole cell lysates and Bradford assay

For whole-cell lysis 50 µl-150 µl cell extraction buffer was applied to the pellets for 45 min on

ice. Protein extracts were cleared through centrifugation at 19500xg for 15 min, and protein

concentration was determined via the Bradford assay. This assay is based on the shift of the

absorption maximum of the dye Coomassie Brilliant Blue-G250 from 365 nm to 595 nm after

its binding to proteins via hydrophobic interactions503. Calibration was performed with

bovine serum albumin in concentrations of 0, 2, 4, 6, 8, and 10 mg/ml to generate the

standard curve. The Bradford solution was diluted 1:5 in ddH2O and 1 μl of the

corresponding lysis buffer in 1 ml of the dilution was used to blank the photometer.

Afterwards, 1 µl sample was added to 1 ml of the Bradford dilution, carefully mixed,

transferred to the UVette and measured in the photometer at λ= 595 nm immediately.

3.2.7.2 Subcellular fractionation

For cytoplasmic, nuclear and chromatin-bound protein isolation, cells were lysed in buffer A

(see subsection 3.1.7) for 10 min on ice by frequent vortexing intervals. Cytoplasmic

fractions were harvested by centrifugation with 4000xg for 4 min on ice. Pellets containing

nuclei were washed once with buffer B (see subsection 3.1.7) and centrifuged for 30 min at

full speed (15000xg). To harvest nuclei, pellets were resuspended in buffer C (see subsection

3.1.7) and incubated 30 min on ice with frequent vortexing intervals. Soluble nuclear

proteins were separated from insoluble chromatin by centrifugation at full speed (15000xg)

for 5 min at 4 °C. The final chromatin pellet was resuspended in 1 U/µl DNase I (Roche) in

buffer C and incubated for 30 min at 37 °C to release chromatin-bound proteins. Subsequent

centrifugation at 1300xg for 15 min at 4 °C was applied to harvest chromatin-bound proteins

in the supernatant. Antibodies directed against SP1 (SP1 Transcription Factor) and RAD50

were used for quality control of the fractionization, as they are known to localize to the

nucleus. Protein concentrations of the fractions were determined by Bradford assay as

described in section 3.2.7.1.

3.2.8 Sodium dodecyl sulfate polyacrylamide gel electrophoresis and western blot

After determination of the protein concentration by Bradford assay (see section 3.2.7), 30 µg

of protein lysates, generated either by whole cell or fractionization procedures, were mixed

with loading buffer containing sodium dodecyl sulfate (SDS), diluted in ddH2O and heated to

95 °C for 5 min. As a consequence of heating and binding of SDS to hydrophobic regions of

proteins, denaturation and charge-masking of proteins is triggered, respectively.

Subsequently, protein samples can be separated according to their size by segregation

through SDS polyacrylamide gel electrophoresis (PAGE) either directly, or stored at -80 °C

until further processing. Stacking gels were used to accumulate proteins and compensate

volume differences before the proteins were separated through separation gels with

according pore sizes. Stacking, as well as separation gels, were prepared according to Table

15 using 10 % gels for ATM signaling experiments and 15 % gels for all experiments involving

TPT1. The separation gel was poured into the gel chamber until approximately 60–70 % of

the total volume was covered and overlayed with propan-2-ol. After polymerization of the

gel, the propan-2-ol was discarded and the gel chamber filled up with stacking gel.

Immediately after, the comb was inserted with care to form even sample slots. After

74

polymerization of the stacker, the gel was stored at 4 °C covered in moist paper towels for a

few days or used straight away.

Before usage, the comb was removed and the sample slots were washed with ddH2O. The

gel was then transferred to the electrophoresis chamber, which was filled with 1x GTS (Table

11). The electrophoresis was run at room temperature at 80 V until the samples reached the

separation gel. If the samples moved evenly through the gel, the voltage was then increased

to 120 V. Otherwise it was either slightly increased or not changed. The electrophoresis was

stopped just before the dye front ran out.

Table 15 Composition of western blot gels

Separation gel 10 % Separation gel

15 %

Stacking

gel

40 % Acrylamide 5 ml 7.6 ml 1.28 ml

2 % Bis-acrylamide 1.32 ml 1.88 ml 0.7 ml

H2O 6.12 ml 4 ml 5.5 ml

20 % SDS 100 μl 100 µl 50 μl 1M Tris-Cl (pH 8.7) 7.52 ml 7.52 ml –

0.5M Tris-Cl (pH

6.8)

– – 2.46 ml

TEMED 20 μl 20 μl 40 μl 10 % APS 100 μl 100 μl 80 μl

In order to enable access of specific antibodies to the proteins separated by SDS-PAGE, the

wet immunoblot (tank blot) technique was applied using a nitrocellulose membrane. For the

transfer onto the membrane, the gel was taken out of the electrophoresis chamber and

placed on the blotting module in the following order: blot module with negative terminal,

sponge, two Whatman papers, gel, nitrocellulose membrane, two Whatman papers, sponge

and blot module with positive terminal. Everything was prepared in 1x carbonate buffer and

placed in the blotting chamber, which was filled with 1x carbonate buffer to the maximum.

The transfer was carried out at 4 °C for three hours at 35 V.

To check whether the transfer was successful, the membrane was removed from the

blotting module and a Ponceau S staining was performed, which unspecifically stains

abundant proteins enabling estimation of transfer completeness504. The following steps

were carried out at room temperature, if not stated otherwise, and while being gently

shaken. The membrane was once washed with 1x PBS and incubated with Ponceau S

solution for a few minutes, until the protein lanes were clearly visible. The staining solution

was then discarded and the membrane washed with ddH2O to remove the stain. Afterwards,

the membrane was blocked one hour in blocking solution (5 % skim milk powder in PBS-T)

and then incubated with primary antibody (diluted in fresh blocking solution) overnight at

4 °C, to allow marking of target proteins505. Subsequently, the antibody was removed and

stored at -20 °C for following usage. The membrane was washed four times with sufficient

1x PBS-T for ten minutes each, and the secondary antibody, also diluted in blocking solution,

was added for an incubation time of two hours. The membrane was again washed four times

with sufficient 1x PBS-T for ten minutes. For detection of the secondary antibody, which was

75

coupled to horseradish-peroxidase and also enables amplification of the signal, the

membrane was incubated with enhanced chemiluminescence (ECL) solution, based on

luminol, according to the manufacturer’s instructions. The peroxidase catalyzes the

oxidation of luminol, which subsequently emits light that can be detected by photographic

density of X-ray films. If the targeted protein was ß-actin, the secondary antibody was

detected with self-prepared luminol, due to the high abundance of the protein resulting in

strong photographic density. After incubation with the detection solution, the membrane

was shrink-wrapped in a plastic foil and the protein signals detected by light sensitive films in

the dark room. The exposure time depended on the signal strength and was varied from a

few seconds for ß-actin and TPT1 to half an hour for phospho-antibodies. The films were

subsequently scanned and analyzed with Image J.

3.2.9 Immunocytochemistry and pre-extraction

Immunocytochemistry, - or more precisely - immunofluoresence analyses were performed

to provide information on presence of proteins in intact cells and simultaneously collect data

on their localization. Proteins were marked with primary antibodies analogous to the

immunoblot technique and fluorescence-coupled secondary antibodies were used to enable

amplification and visualization of the signal with a fluorescence microscope. For detection of

irradiation-induced foci by immunofluorescence, cells were seeded and grown on cover

glasses in six-well plates (Nunc) one day prior to IR treatment. Depending on the

experimental setting, cells were washed three times in 1x PBS and fixed at time points

ranging from 1 h to 48 h, by treatment with 3 % (w/v) formaldehyde, 2 %(w/v) sucrose in

PBS for 10 min. Permeabilization was performed with 0.2 %(v/v) triton X-100 in PBS, in order

to allow penetration of the cell membrane by antibodies. Primary antibodies against the

target proteins were incubated in 2 % (w/v) normal goat serum (Dianova) for 2 h. After PBS

washing, cells were incubated with Alexa Fluor Anti-mouse IgG 488 (Invitrogen, #A11018)

and Alexa Fluor Anti-rabbit IgG 546 (Invitrogen, #A11071) or FITC-conjugated Anti-mouse IgG

antibody (Zymed, #62-6511) and Alexa Fluor Anti-rabbit IgG 488 (Invitrogen, #A11070) for

2 h, respectively. DNA was counterstained with DAPI (Invitrogen) and cover classes were

mounted onto slides with Pro-Long® Gold (Invitrogen) and dried overnight before evaluation

by fluorescence microscopy. For pre-extraction of proteins, which are abundant in the

cytoplasm, cells were subjected to detergent extraction with pre-extraction buffer

containing 10 mM Hepes (pH 6.8), 100 mM NaCl, 300 mM sucrose, 3 mM MgCl2, 1 mM EGTA

and 0.5 % triton X-100 in PBS for 5–10 min to remove the majority of non–chromatin-bound

proteins before fixation and immunostaining, in order to enable a noisefree view of the

nuclear forms of these proteins265.

3.2.9.1 Fluorescence micoscropy and confocal laser scanning microscopy

Images were taken by Leica DMI6000B microscope (63x–100x magnification) or, for a more

detailed inspection, using an Olympus confocal microscope FV 1000 (60× magnification),

Table 16. Confocal microscopy is a form of light microscopy which enables depiction of

three-dimensional structures by scanning different levels of a sample with a laser, which

excites fluorescence molecules and produces very high resolution images506. Table 16 shows

details about microscopes, objectives, and corresponding wavelengths used for excitation,

as well as applied software for data processing. γH2AX and 53BP1 foci were counted

manually with Image J software on pictures in an average of 100 cells after siRNA treatment

76

and/or IR for each of at least two independent experiments, independent from the cell-cycle

phase. Cells with apoptotic morphology or cells with intensely and completely stained

nucleus were excluded from the counting process. Colocalisation was defined as yellow

stained dots in overlay pictures generated with confocal microscopy. In general, the

colocalization rate in experiments described in subsection 4.1.3 was very low, but at least 10

colocalization-positive cells were examined and counted manually in control cells and at

least 15 cells in irradiated samples, respectively. RAD51 foci (see Supplementary figure S-25

and Supplementary figure S-27) were counted directly under the Leica fluorescence

microscope using the 100x oil objective.

Table 16 Fluorescence microscopy devices and parameters

Microscope Objective with numeric

aperture (NA)

Filter/excitation

wavelength

Software

Leica DMI6000B PLAN L PH2 (40x, NA: 0.6), A/BP 400/20 nm Leica

Application

Suite 1.9.0

HCX PLAN L (63x, NA: 0.7) L5/BP 480/40 nm

HCX PLAN L Oil (100x, NA: 1.3) Y3/BP 545/40 nm

Olympus

confocal

microscope FV

1000

Oil immersion (60x, NA: 1.35)

532nm, 559nm,

655nm

FluoView1000

3.2.10 Image processing and foci analyses

Image processing was performed with the programs Leica Application Suite, Olympus

FluoView1000, GraphPad Prism and ImageJ. For foci analysis, pictures of the cells were taken

with a Leica DMI6000B microscope with settings stated in Table 17. The settings were just

slightly changed during observation of one slide.

Table 17 Microscope settings used for foci images

Blue

channel,

λ = 425 nm

Red channel,

λ = 572–648 nm

Green channel,

λ = 512–542 nm

Fluorescence

Intensity Manager

[%]

100 55 30

Exposure time [ms] 30–200 60–390 50–260

Gain 2.6–6.0 2.0–10 2.0–10

The foci were counted by eye with support of the Image J software for γH2AX and 53BP1 foci and directly under the microscope for RAD51 foci, respectively. Results of RAD51 foci

analysis in primary cells were already published507 and RAD51 analysis in TERT-immortalized

cells were done by Katharina Stemwedel in the course of her student assistant work (as

pointed out by “observer 2” in Supplementary figure S-27). For analysis with the Image J

77

software, the images were split to single channel images and the area of the nucleus was

manually selected. The Image J option to find maxima within this area was chosen to find,

mark and count the foci. The noise factor was optimized for each picture by eye and all of

the counted were foci proof-read. Cells with apoptotic morphology or intensely stained

nucleus were excluded from this process. The threshold of at least three foci per nucleus was

applied and only cells meeting these criteria were considered as “foci-positive”. At least 100

cells were counted for each cell line and time point. Foci counting in subsection 4.4.2. was

performed by Katharina Stemwedel in the course of her bachelor thesis and the foci

counting procedure was validated by two second observers during an internship of two Life

Sciences students.

3.2.11 Colony survival assay

The colony survival assay is known as the “gold standard of radiosensitivity”508 and is a well

established method to assess effects of cell survival after different treatments. It is based on

the premise that surviving single cells can undergo a series of cell divisions and eventually

form colonies, which can be counted by microscopy. The effect of different treatments such

as irradiation or chemotherapeutics can be related to the surviving fraction of cells, which is

calculated based on the initial input of single cells. The CSA measures the sum of all modes

of cell death, including both early and late events such as delayed growth arrest.

One day prior to IR, subconfluent cells were harvested and counted as described in

subsection 3.2.1. Different seeding concentrations were tested from 1250–5000 cells per

flask for untreated and 5000–20000 cells per flask for irradiated cultures, respectively, until

optimal seeding densities for each cell line were obtained. In order to harvest evaluable

colonies, cells need to be seeded in higher densities for IR treatment compared with

controls. One day after seeding, cells were subjected to 2, 4, and 6 Gy radiation treatment

and kept in culture for up to three weeks. The medium was changed twice a week and

pictures of cells were taken once a week to assess progress of colony formation. When

visible colonies of at least 50 cells each were detected in the controls, the assay was

stopped. The medium was aspirated and cells were washed with 1x PBS three times. Cells

were fixed with 2 % sucrose, 3 % formaldehyde in 1xPBS for 30 min at room temperature.

The fixing solution was discarded and 0.5 % crystal violet in ddH20 was added for 30min at

room temperature. Afterwards, the staining solution was removed and stored for further

usage. Cells were washed several times with water until clearly stained colonies were visible.

Cell culture flasks/6-well plates were dried at room temperature at least overnight and

colonies were analyzed using light microscopy.

In order to provide physiological attachment surfaces for the radiosensitive cells, 6-well

plates coated with gelatin and collagen, respectively, were also tested. For preparation of

gelatin coating, a 0.1 % gelatin solution in 0.9 % NaCl was warmed to 37 °C, applied to the

culture plate or T25 flask and incubated for 20 min. It was subsequently discarded and the

plates or flasks were left to dry prior to addition of cells.

3.2.12 Senescence assay

The β-galactosidase staining assay was performed to analyze development of senescence in

cells subjected to irradiation treatment. It is based on β-galactosidase (β-gal) cleavage of the

artificial substrate X-gal (5-bromo-4-chloro-3-indolyl-beta-D-galactopyranoside), which is

78

subsequently metabolized and detected as blue color509. The β-galactosidase staining kit

(Qiagen, Table 7) was used to detect pH-specific (pH 6.0) activity of β-galactosidase, which is

associated with senescence510. The procedure was followed according to the manufacturer’s

instructions. Subconfluent cells were seeded in 6-well plates one day prior to IR. Optimal

seeding densities were established for each cell line and ranged from 5000–10000 cells for

early time points 24 h and 48 as well as the unirradiated controls and from 1000–3000 cells

per 6-well for late time points 7 d and 9 d. One day after seeding, cells were subjected to IR

with 4 Gy and fixed after 24 h, 48 h, 7 d or 9 d, respectively. The medium was aspirated, cells

were washed with 1xPBS and fixed for 15 min at room temperature. Subsequently, the fixing

solution was discarded and freshly prepared staining solution was added to the cells. The 6-

well plates were sealed with parafilm to prevent evaporation and placed into a 37 °C

incubator without CO2 supply for 48 h. Cells were checked for the development of blue color

and pictures were taken with the staining solution remaining on the cells. Cells were counted

according to positive criteria of development of blue color. Only clearly blue cells were

considered senescent, while cells with normal shape and appearance that lacked blue color

were considered non-senescent. Cells with apoptotic morphology and/or intense

vacuolization, which lacked β-galactosidase staining, were excluded from the counting

procedure. Non-senescent cells were normalized to total cells numbers counted (75–100

cells per well), plotted and analyzed with GraphPad Prism software. The results of the pilot

experiments were additionally anlyzed by Katharina Stemwedel (as indicated by “observer two” in Figure 34) during the course of her student assistant work.

3.3 Other methods

3.3.1 Statistics

All experiments were performed at least two times in section 4.1 and at least three times for

experiments in section 4.4. Comparisons between treatments or groups and respective

controls were conducted using unpaired two-tailed t-test or unpaired two-tailed Mann-

Whitney test by GraphPad Prism version 5.01 for Windows, GraphPad Software, San Diego

California USA. If data deviated from normal distribution parameters, tested by GraphPad

column statistics (D’Agostino and Pearson omnibus normality test), median was preferred

over the mean as subject to further testing. Outliers were determined using Grubb’s Test511.

Regression analyses and three-way ANOVA of data in subsection 4.1.4 were performed using

STATA12 by Dr. Thilo Dörk-Bousset. P values < 0.05 in the pairwise comparison of groups or

in interaction analyses were considered significant. The number of independent experiments

is indicated by “n”, given by the number of symbols of each column or explained in the according subtext of figures. Significance levels are given by p ≤ 0.001 (***), p ≤ 0.01 (**),p ≤ 0.05 (*), or p > 0.05 (ns= not significant). In Ingenuity Pathway Analysis, p-values of overlap

were calculated based on Fisher’s Exact Test, see explanation in Figure 12. The Null

hypothesis is defined by default as: no overlap between molecules from the dataset and a

disease/function/upstream regulator/pathway. Fisher’s Exact Test compares the set of molecules in the uploaded dataset to a reference set that includes all known molecules, for

example in the Ingenuity Knowledge Base dataset (Figure 8A).

79

Figure 12 P-value of overlap calculation in Ingenuity Pathway Analysis by Fisher’s Exact Test IPA utilizes Fisher’s Exact Test to calculate p-values of overlap, which are given in Figure 18–Figure 25, Supplementary figure

S-8–Supplementary figure S-11 and Supplementary figure S-22–Supplementary figure S-23. This test determines whether a

biological attribute is significantly enriched in a given dataset and if the overlap is larger than would be expected by random

sampling of the dataset. It compares molecules in the uploaded dataset to a reference dataset, which in this work was

chosen to be the Ingenuity Knowledge Base (displayed as blue circle and first choice in panel A, right-hand side). Fisher’s Exact Test calculates the probability that molecules from the uploaded dataset, which could be mapped to the Ingenuity

Knowledge Base (Analysis-ready molecules, orange circle), overlap with molecules within a given pathway in the reference

dataset (Non-analysis-ready molecules associated with biological category, violet circle). The Null hypothesis, that this

overlap is due to chance, is tested (panel B), and the default significance value of p ≤ 0.05 was used in this thesis. It is valid for small and large sample sizes, can test data that has unequal proportions between classifications/categories, it calculates

the exact p-value for a specific number of overlapping molecules and molecules are classifies as successes (as belonging to a

certain pathway) or failures (as not belonging to this pathway) in a process of sampling without replacement. The

probability follows a hypergeometric distribution and is computationally efficient. IPA uses a right-tailed Fisher’s Exact Test and the exact p-value is the sum of probabilities for all outcomes at least as extreme or more extreme than the given

threshold, if the Null hypothesis is true. Information in this figure was taken from IPA webinar and website512,513

.

3.3.2 Patients

Lymphocytes and/or skin fibroblast samples of 19 radiosensitive cancer patients had been

collected at four hospitals throughout Germany during the last 20 years and were provided

by Dr. Margret Rave-Fränk (Göttingen), Prof. Dr. Detlev Schindler (Würzburg), PD Dr. Kerstin

Borgmann (Hamburg) and Prof. Dr. Markus Stumm (Magdeburg). Clinical data are

summarized in Supplementary table S-1.

3.3.3 DNA extraction

For extraction of DNA from patient cells, the cells were harvested as described in subsection

3.2.1. The cells were centrifuged at 1000xg (3000 rpm (rounds per minute) for 10 min at

80

4 °C. After discarding the supernatant, the pellet was washed twice with ice cold sterile 1x

PBS and centrifuged again at 1000xg (3000 rpm) for 10 min at 4 °C. After transfer to a new

1.5 ml reaction tube, the samples were centrifuged at 2800xg (5000 rpm) for 10 min at 4 °C

and after removal of the supernatant, pellets can either be frozen at -20 °C or directly

processed.

3.3.3.1 Phenol-chloroform extraction and ethanol precipitation of genomic DNA

For removal of protein contamination, the pellet was resuspended in 400 μl proteinase K

reaction mix (Table 11) with subsequent proteolysis at 56 °C overnight in a thermal shaker.

Impurities were removed by vigorous shaking of samples after proteinase K reaction with

400 μl of equilibrated phenol/chloroform/isoamyl alcohol mixture (25:24:1 in TE, pH 8.0).

After incubation on ice for 10 min, the emulsion was centrifuged for 10 min, 18900xg (13000

rpm), at 4 °C, and the upper aqueous phase was collected in new autoclaved 1.5 ml tubes.

This step was repeated once again with an equal volume of phenol/chloroform/isoamyl

alcohol, the emulsion centrifuged for 10 min, 18900xg (13000 rpm), at 4 °C, and the upper

aqueous phase again transferred to new autoclaved 1.5 ml tubes. Subsequently, an equal

volume of pure chloroform was applied to the supernatant (upper aquaeous phase),

carefully mixed and incubated for 10 min on ice. After centrifugation for 10 min, 18900xg

(13000 rpm), at 4 °C, the upper aqueous phase was collected for precipitation. Nucleic acids

were precipitated by addition of 40 µl (1/10 volume) 3 M sodium acetate (pH 4.8) and 1 ml

(2.5 volumes) of absolute ethanol/uvasol (100 %). The mixture was then carefully swayed,

incubated for 30 min on ice to complete DNA precipitation and centrifuged (30 min, 4 °C,

19500xg (13200 rpm)). The pellet was washed twice with 500 µl 70 % ethanol/uvasol to

remove residual salts and centrifuged (15 min, room temperature, 18900xg (13000 rpm).

After washing, the supernatant was carefully aspirated and the pellet was dried at 50 °C for

5–7 min.

Depending on the subsequent application, the dried pellet was resolved in either 1x TE

buffer or ddH2O, respectively. For exome sequencing, 1x TE buffer (depending on the size

100 µl–500 µl) was used to dissolve the pellet, the suspension was carefully vortexed and

the pellet dissolved either at room temperature for 1 h or overnight at 4 °C. After 1:5

dilution with 1x TE, the concentration of the DNA is determined by measuring in a NanoDrop

8000 device (Peqlab).

3.3.4 Exome sequencing

Exome sequencing has emerged as powerful tool to specifically enrich and analyze the

genetic background of the coding sequences of the genome. To investigate possible genetic

mutations underlying the clinical radiosensitivity of 19 cancer patients, and to analyze the

genetic background of two matched pairs in parallel, genomic DNA was isolated from whole

blood cells and subjected to exonic sequence enrichment using the Agilent SureSelect XT

Human All Exon V5 Library in cooperation with Dr. Robert Geffers at the Helmholtz Center

for Infection Research (HZI), Braunschweig. This was followed by exome sequencing at 100x

coverage on an Illumina HiSeq_PE200 platform, as performed by Dr. Sabin Bhuju at the HZI.

Sequencing reads were quality trimmed and aligned to human reference genome (hg19) by

Dr. Geffers. Variants were called by GATK-HaplotypeCaller and further evaluated using GATK

pipeline recommendations. Annotation of variants was performed by the Annovar tool.

Mutations identified were filtered for their predicted effect (truncating and splice site only),

for minor allele frequency < 0.005, and for simultaneous occurrence in <3 patients.

81

Mutations were then verified by direct Sanger sequencing of the corresponding genes and

regions by use of an in-house sequencer (3.3.7 and Table 12).

3.3.5 Primer design and polymerase chain reaction

3.3.5.1 Primer design

For validation of prioritized mutations identified by exome sequencing (for prioritization

criteria see section 4.2), sequence-specific primers were designed. The sequence was

retracted from the National Center for Biotechnology Information (NCBI) database514,

reference genomic sequence 37.p13 primary assembly. The region spanning 1000 bp (base

pairs) around the mutation was used as reference to design primers in the forward and

reverse 5’3’ direction with at least 50 bp distance to the region of interest. Primers were

designed to yield a PCR product of maximum size 600 bp, consisted of 20 bp stretches with

equal A/T–G/C content and initiated and terminated by G/C. Forward and reverse primer

were checked to be non-complementary and were designed outside of highly repetitive or

palindromic sequences, if possible. A complete list of primers is given in Supplementary table

S-6–Supplementary table S-8.

3.3.5.2 Polymerase chain reaction and purification of products

Polymerase chain reaction (PCR) is a technology to amplify selected pieces of DNA and was

invented by Kary Mullis in 1983515. It is one of the most important techniques in the field of

molecular biology as it very sensitive and requires only a small amout of DNA to generate

billions of replicates in a short time516. The general principle of PCR starts from a pair of

oligonucleotide primers that are designed so that a forward or sense primer directs the

synthesis of DNA on one strand in a 5’3’ direction, and a reverse or antisense primer on

the complementary strand vice versa. From the second cycle on, the daughter strands can

also serve as templates for PCR products with restricted lengths defined by both primers.

During several extension cycles of PCR, the Taq DNA polymerase (a heat stable

polymerase)517 catalyzes the synthesis of new DNA strands complementary to the template

DNA from the 5’3’ direction by a primer extension reaction, resulting in the exponential

production of the selected DNA region flanked by the two primers.

A mix for PCR was prepared with final concentrations of 0.2 mM dNTPs, 1.5 mM MgCl2, 1 U

heat stable DNA polymerase from Thermus Aquaticus (TopTaq or HotStar, if TopTaq was not

successful), 0.5 μM of each primer, 1 x specific amplification buffer, recommended by

manufacturers of enzymes, 50 ng genomic DNA and sterile HPLC-grade water to yield up to

15–25 μl end volume in either 0.5 ml PCR tubes or 96-well plates. Amplification was

performed in a peltier-controlled thermocycler (mostly PTC-200 from Biozym/MJ Research)

where an initial denaturation of 15 min (for HotStar Polymerase) or 5 min (for GoTaq

Polymerase) was followed by a range of 33 to 40 cycles of denaturation-annealing-extension

steps, depending on the primer pair. Denaturation and extension steps were performed for

1 min. Denaturation temperature was 95 °C, extension temperature 72 °C. Annealing

temperature was adjusted according to primer composition and was selected for each

primer pair independently in a prior optimization procedure with temperature gradient 54 °C

to 64 °C, see Table 18.

82

Table 18 PCR protocol for primer optimization and validation sequencing

Step Temperature Time

Initial denaturation 95 °C 5 min for TopTaq

15 min for HotStar

Annealing 54 °C to 64 °C 1 min Extension 72 °C 1 min

Denaturation 95 °C 1 min

35 cycles Go to 2, 35 times

Final extension 72 °C 5 min

Cooling 8 °C Until samples are removed

Purification of PCR products was performed by polyethylene glycol (PEG) precipitation. 1x

volume of PEG was applied to the PCR product and the sample was vortexed thoroughly.

After 10 min incubation at room temperature, the PCR product was centrifuged at 15700xg

for 10 min, the supernatant was removed and samples were washed with 100 µl absolute

ethanol/uvasol. The PCR products were incubated again for 10 min and centrifuged at

15700xg for 10 min. The supernatant was discarded and the dry pellet was dissolved in 10–20 µl HPLC-purified water. To check for loss of PCR product, 4 µl of PEG-purified sample were

run on a 2 % agarose gel.

3.3.6 Agarose gel electrophoresis

Electrophoresis is a technique by which a mixture of charged macromolecules, especially

nucleic acids or proteins, can be separated in an electric field according to the correlation of

electrophoretic mobility and the macromolecule’s charge to mass ratio. Nucleic acids can be separated according to their lengths by gel electrophoresis through agarose gels, with the

separation range being dependent on the agarose concentration. In this work 1–3 % w/v

agarose in TBE was prepared. The amount of 1–3 g of agarose was dissolved in 100 ml 1 x

TBE buffer, boiled in the microwave, cooled down to about 50–80 °C before addition of Gel-

Red (1000 fold in DMSO, final dilution approximately 1:50000), thoroughly mixed by gentle

swirling and then poured into an electrophoresis tray with appropriate comb(s). After

solidification of the agarose, the tray was transferred to a horizontal electrophoresis

chamber and the gel was covered with 1x TBE buffer. The 4–8 μl of sample were mixed with

2–4 μl of 6 x loading buffer (Table 11), applied onto the gel, and run at 100–150 V at RT until

samples were separated. To check for complete separation and for determination of size of

the nucleic acids fragments on agarose gels, molecular weight ladders were loaded in

parallel. After gel electrophoresis, the DNA was visualized on a UV transilluminator.

3.3.7 Sanger sequencing

With the progress in next generation sequencing techniques such as exome sequencing, a

new era of high-throughput and highly parallel sequencing has advanced. However, the

traditional sequencing protocol according to Dr. Frederick Sanger518 is still a very important

method for validation of findings among other applications. Using this chain termination

method, the order of nucleotides in a given DNA fragment can be determined. Modified

nucleotide substrates (most commonly di-desoxyribonucleoside triphosphates labeled with a

separate fluorescent dye, ddNTPs) account for the sequence-specific termination of a DNA

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synthesis reaction. Sequence-specific primers composed of short oligonucleotide sequences

complementary to the template at the region of interest, are designed for the forward, and

the complementary reverse reaction on the opposite strand in 5’3’ direction. After binding of the primer, it is extended using a DNA polymerase which incorporates the

desoxyribonucleosidetriphosphates but also occasionally utilizes a chain terminating

nucleotide, each with a different fluorescent dye detectable at a different wavelength.

Incorporation of the ddNTPs at different positions in repeated cycles results in a series of

related DNA fragments that are terminated only at positions where that particular

nucleotide is used. The end-labeled fragments are then size-separated by electrophoresis

either in a slab gel or in a narrow glass tube (capillary) filled with a viscous polymer.

In this work, sequencing reactions were performed with the Sanger method using a Big Dye

Terminator Cycle Sequencing-Kit v.-1.1 (Applied Biosystems, Darmstadt). The sequencing

reaction was carried out in a total volume of 10 μl, usually containing 2 μl of purified PCR

products, 1 μl of sequencing primer (5 μM) and 1.5 μl BigDye reaction mix (contains reaction

buffer, dNTPs, four differentially labeled ddNTPs and polymerase) supplemented with

fluorescence-free HPLC grade water (Baker). Elongation and chain termination follows a

specific program in a thermocycler, see Table 19.

Table 19 Cycling conditions for sequencing reaction

Step Temperature Time

Initial activation 95 °C 5 min 26 cycles 50 °C 15 s

60 °C 4 min

95 °C 30 s

Subsequently, the DNA was precipitated by adding 1/10 volume 3 M sodium acetate and 3x

volume absolute uvasol/ethanol. The samples were vortexed and incubated for 1 h at room

temperature in the dark before being centrifuged for 30 min at 15700xg at 4 °C. The

supernatant was discarded and the pellet was washed with 300 µl 70 % ethanol/uvasol.

After centrifugation at 15700xg for 10 min at 4 °C the pellet was dried and resuspended in

20 µl 95 % form amide. The samples were incubated for 1 h at room temperature in the dark

and DNA was denatured for 3 min at 93 °C in a thermal cycler. The samples were transferred

onto a 96 well plate and sequenced using the Genetic Analyzer 3100-Avant by Applied

Biosystems with the following instrument protocol: Seq_50cm_POP6_Set_E and the analysis

protocol POP6_BDTv1.1. Dr. Natalia Bogdanova and the students Julia Enssen and Louisa

Weinhold helped with PCR amplifications and subsequent sequencing for the majority of the

mutations. For unambiguous identification of several mutations in the heterozygous state, a

control was sequenced as direct comparison.

3.3.8 Bioinformatics

3.3.8.1 GeneCards Database

For initial annotation of genes, which were identified by exome sequencing, the GeneCards

database was accessed519. It was developed and maintained by the Crown Human Genome

Center at the Weizmann Institute of Science, Israel, and has been used by scientists since

1998520,521. It can be utilized for collecting data on biomedical information about the gene

itself, the encoded protein and also associated diseases522. In this database, information

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from over 90 data resources is unified, including NCBI, Ensembl (Ensembl genome database

project)523,524 and the HUGO Gene Nomenclature Committee521,520. GeneCards is a

searchable, integrative database that provides information on all annotated and predicted

human genes. It automatically integrates gene-centric data from ~125 web sources,

including genomic, transcriptomic, proteomic, genetic, clinical and functional information.

3.3.8.2 Ingenuity Pathway Analysis

Ingenuity Pathway Analysis (IPA) was used to annotate the exome sequencing data and

identify pathways or functions which could be overrepresented in RS patients. The following

settings were applied: data in the form of genelists, retrieved from exome sequencing hits of

truncating mutations, was uploaded using import filters: flexible format, gene symbol

identifier type and no specified array platform. Core analyses in the form of “variants effects

analyses” were performed using the Ingenuity Knowledge Base (genes + endogenous

chemicals) reference set. Only direct relationships were chosen to be considered,

endogenous chemicals were included in interaction networks calculations and causal

networks were scored using causal paths only. All node types and data sources were

considered, confidence parameters were set to only experimentally observed data and

species was restricted to human using stringent filter for molecules and relationships. All

available tissue and cell line data was used with also stringent filtering and all mutation types

were included. Comparison analyses were performed using either original datasets and Venn

diagrams to display overlapping genes or using separately conducted core analyses

generated by the procedure above. For statistical anlyses in IPA, Fisher’s Exact Test was applied, see subsection 3.3.1.

3.3.8.3 Reactome Pathway Browser

Reactome is an open-source, curated and peer reviewed pathway database and utilizes data

based on publications with PubMed links525,491,492. It provides bioinformatics tools for the

visualization, interpretation and analysis of pathway knowledge to support basic research,

genome analysis, modeling and systems biology.

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4 Results

4.1 Assessment of TPT1 as candidate radiosensitivity marker in ATM signaling

4.1.1 TPT1 does not affect early ATM signaling after irradiation

Previous data on normal human primary cells as well as cancer cell lines strongly support a

role of TPT1 in DNA damage sensing and repair processes265 267. In order to investigate

whether TPT1 is required for ATM signaling, the TPT1 gene was silenced by siRNA in large T

immortalized human skin fibroblasts (ADP) and in spontaneously immortalized human breast

epithelial cells (MCF10A)526, and the phosphorylation of ATM target proteins KAP1 (at

Ser824)205,206,527,528 and CHEK2 (at Ser19)529 was investigated in response to low (60 mGy) or

high (6 Gy) dose irradiation.

At 30 min post-irradiation, KAP1 pSer824 and CHEK2 pSer19 were easily detected in cell lines

ADP and MCF10A after 6 Gy, but neither showed differences in phosphorylation levels after

TPT1 knockdown compared to scrambled controls (Figure 13 and Supplementary figure S-

1A). These experiments indicated that TPT1 levels exert no considerable influence on ATM

kinase activity towards these substrates.

To investigate vice versa whether ATM exhibits a direct effect on TPT1 levels in our cell

systems, we inhibited the kinase activity of ATM 1 h prior to IR with the specific inhibitor

Ku55933. As shown in Supplementary figure S-2, TPT1 levels were unaffected by ATM

inhibition, while there was strong reduction in KAP1-phosphorylation. Consistent with the

absence of ATM dependency, levels of TPT1 in whole cell extracts did not change at 30 min

after low or high dose IR in ADP, MCF10A and the triple negative BC cell lines HCC1395 and

HCC1937 (Supplementary figure S-1C-D).

Figure 13 Knockdown of TPT1 does not influence ATM signaling by means of KAP1 (Ser824) phosphorylation Western blot of ADP and MCF10A cells treated with TPT1 siRNA (si) or scrambled control (ctrl) 48 h prior to IR and lysed

30 min after no (0 Gy), low dose (0.06 Gy) or high dose (6 Gy) IR. The immunoreactivities of p-KAP1 (Ser824), TPT1 and β-

actin as loading control are shown.

http://www.dict.cc/englisch-deutsch/spontaneously.html

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4.1.2 Intracellular distribution of TPT1 does not change after irradiation

As TPT1 is both a cytosolic and a nuclear protein, it was next examined whether the

intracellular localization pattern of TPT1 after IR may change according to a functional

recruitment of TPT1 in DNA damage sensing and repair processes in our cellular systems.

The intracellular distribution of the protein was analyzed by immunofluorescence analyses

(Figure 14, Supplementary figure S-3 and Supplementary figure S-4A) as well as by cellular

fractionation (Supplementary figure S-2B). The specificity of the immunofluorescence

staining was validated with two different TPT1 antibodies (Figure 14A and B; Supplementary

figure S-3 and Supplementary figure S-4A) at 1 h after IR. No gross changes in TPT1

localization at 1 h after low (0.06 or 0.25 Gy), medium (1 Gy) or high doses (6 Gy) of IR were

detected, respectively, when assessed in asynchronous subconfluent fibroblasts by

conventional fluorescence microscopy. Foci-like structures of TPT1 were visible by confocal

laser microscopy, which appeared in both cytoplasm and nucleus in irradiated and control

cells. There was no evidence for a translocation of TPT1 to the nucleus after 1 Gy IR in ADP

as well as MCF10A cells analyzed by confocal analyses (Supplementary figure S-3 and

Supplementary figure S-4C). In some cells, TPT1 moreover appeared to accumulate in the

nuclear periphery after IR (Supplementary figure S-4). Immunostainings in different triple

negative BC cell lines also provided no evidence for nuclear translocation of TPT1 at 1 h after

IR with 0.25 Gy and 1 Gy (Supplementary figure S-4A) or 0.06 Gy and 6 Gy (data not shown),

respectively. Consistent with this data, no robust evidence for chromatin binding of TPT1 in

ADP or MCF10A cells without or 30 min after IR with 60 mGy or 6 Gy was found

(Supplementary figure S-2B and data not shown). KAP1 was phosphorylated and present in

cytosolic, nuclear and chromatin-bound fractions. In contrast, TPT1 was only present in

cytosolic and nuclear fractions and not chromatin-bound, independent of treatment, and its

localization did not detectably change after IR. Furthermore, no increment in nuclear

translocation of TPT1 after IR in lymphoblastoid cells of healthy and radiosensitive

individuals was observed477. These findings supported the immunofluorescence data of ADP

and MCF10A (Figure 14; Supplementary figure S-3) HCC1937 (Supplementary figure S-4), as

well as HCC1395 and HCC38 (data not shown).

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Figure 14 No evidence for colocalization of TPT1 and γH2AX in ADP and MCF10A cells Asynchronous, subconfluent cells were preextracted with Triton X-100

265 and fixed 1 h after IR. Panel A shows

immunofluorescence stainings for TPT1 (red) (ab37506) and γH2AX (green) in ADP cells and areas of colocalization are

visible in yellow in the overlay picture. Scale bar = 25 µm. As comparison, TPT1 stainings in ADP cells were performed with a

second antibody (ab133568) visualized in green, which are shown in panel C after 1 Gy IR. γH2AX foci and areas of

colocalization were counted manually and are shown as means with standard deviations for ADP in panel B and MCF10A

cells in panel D.

4.1.3 Limited colocalization of TPT1 with γH2AX foci after irradiation

Given the lack of evidence for an involvement of TPT1 in ATM signaling and its uniform

intracellular distribution after IR, the question was adressed whether the nuclear fraction of

TPT1 shows colocalization with the γH2AX repair foci after IR in our cellular systems. In order

to reduce cytoplasmic background staining, cells were subjected to a previously described

preextraction procedure with Triton X-100 prior to fixation265. The cells were analyzed at 1 h

after 1 Gy IR, with stainings for TPT1 and γH2AX also being performed in TPT1 knockdown

cells and non-preextracted cells (Supplementary figure S-3) as well as in irradiated triple

negative BC cell lines (represented in Supplementary figure S-4 for HCC1937, data for

HCC1395 and HCC38 not shown). In order to validate the staining, two different TPT1

antibodies were used, one of which has already been published in this context265. Although

both antibodies showed a spotty pattern of TPT1 in the cytoplasm as well as in the nucleus,

colocalization of TPT1 and γH2AX was poorly detectable in either cell type under any

condition. These results were confirmed by a second analyzer, namely Dr. Natalia

Bogdanova. Knockdown of TPT1 in ADP and MCF10A cells was approved by confocal

immunofluorescence analyses (Supplementary figure S-3A-B), in agreement with the

western blot results shown in Figure 13, and served as a negative control for antibody

specificity. Very few areas of colocalization were detected according to the overlay of TPT1

and γH2AX staining and were counted in accordance with γH2AX foci. The proportion of

colocalized foci is displayed as means with standard deviations in Figure 14C for ADP and

Figure 14D for MCF10A cells. It was below 10 % in ADP and below 5 % in MCF10A cells.

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4.1.4 Knockdown of TPT1 does not impair formation of γH2AX foci after irradiation

Next, the role of TPT1 in the context of γH2AX foci formation and disassembly including early

and later time points after IR was investigated. In order to monitor the effects of TPT1 on

DNA damage sensing as early as 1 h after IR and ongoing repair from 6 h to 48 h after IR,

TPT1 was silenced by siRNA in ADP and MCF10A cells, and the number of γH2AX foci (Figure

15 and Supplementary table S-2) and 53BP1 foci (Supplementary figure S-7 and

Supplementary table S-3) was counted by using immunofluorescence analyses. Regression

analysis revealed a strong correlation between γH2AX foci and 53BP1 foci in both cell lines,

irrespective of TPT1 silencing (total R2= 0.972), but significant differences between γH2AX

foci in TPT1 knockdown (si) or scrambled control (ctrl) cells were not observed at 1 h after IR

(Figure 15). However, these findings indicated a cell type-specific influence on retention of

γH2AX foci, as a slight (but not statistically significant) effect of silencing could be detected in

MCF10A at early and in ADP cells at later time points, respectively. Three-way ANOVA

analyses further supported these findings. Moreover, no significant changes in 53BP1 foci

numbers were detected between silenced and control cells in both cell lines at all time

points (Supplementary figure S-7).

Taken together, TPT1 silenced ADP fibroblasts showed slightly increased γH2AX as well as

53BP1 foci numbers at all time points except 6 h after IR compared to scrambled controls.

Although none of these changes were statistically significant, a borderline significant effect

of siRNA-treatment on γH2AX foci formation in ADP cells, especially at 24 h after IR, could

not be finally excluded (p-value of 0.073 for normalized values). The data suggests that there

might be subtle differences in DNA damage resolution processes between time points of 6 h

to 48 h after IR but not the early foci formation at 1 h after IR in ADP cells. MCF10A cells

show slightly increased foci numbers at 6 h and 48 h after IR in silenced cells, however, not

significantly different from scrambled controls. Altogether, these results indicate a limited

role of TPT1 in DNA damage sensing and repair, which might be cell-type specific rather than

following a general principle. Considering the borderline, if any, effect on repair foci after IR,

TPT1 was no longer considered as candidate marker for individual radiosensitivity.

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Figure 15 γH2AX foci numbers in TPT1 knockdown cells after irradiation Asynchronous, subconfluent ADP and MCF10A cells were treated with siRNA against TPT1 (si, light blue columns) or

scrambled controls (ctrl, dark blue columns) 48 h before IR with 1 Gy. Cells were fixed on glass slides at 1 h, 6 h, 24 h or 48 h

after IR and stained for TPT1, γH2AX and DAPI. γH2AX foci were counted manually in an average of 100 cells on each slide

and cells with a minimum of 3 foci were considered foci-positive and subjected to counting. Foci numbers were normalized

to unirradiated controls [%] (right-hand side, panels A and D) and means with standard deviations from two independent

experiments are shown. Original data are shown in scatter plots on the left-hand side in panels A and C. Raw data are given

in Supplementary table S-2. Means with standard deviation are shown and unpaired two-tailed t-tests using GraphPad

Prism Software were performed. Significance levels are given by p ≤ 0.01 (**), or P > 0.05 (ns = not significant).

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4.2 Assessment of the functional relationship between clinical and cellular

radiosensitivity

In the second and third part of this project (see Figure 11 for overview), the experimental

procedures focused on patient material that had been collected throughout the past 20

years at different institutions. Figure 16 shows the workflow which was followed starting

from analyzing the genetic background of the RS patients, over generation of cell culture

models to establishment of a functional association between clinical and cellular

radiosensitivity.

Figure 16 Workflow for characterization of individual radiosensitivity using patient material

4.2.1 The genetic signature of radiosensitivity

4.2.2 Annotation of exome sequencing data by GeneCards

The exome sequencing of lymphocyte (from LCLs) and fibroblast (from primary cultures)

genomic DNA from 19 RS patients (11 BC, 3 Chemo RS, 5 with other cancers) and 2 BC

patients without radiation side-effects (see Supplementary figure S-1), was performed at the

Genome Analytics Unit of the Helmholtz Center for Infection Research, Braunschweig (Dr.

Robert Geffers). Filtering for mutation effect (stop gain, frameshift or intronic), for low

frequency in SNP databases (MAF<0.005) and for non-redundancy across the exomes (N<3)

was performed at our lab (Dr. Thilo Dörk-Bousset). The final list contained 527 truncating

mutations in RS patients and 60 truncating mutations in the two controls. For one patient,

MC3, genomic DNA from fibroblasts as well as from LCLs was extracted and subjected to

separate exome sequencings to examine whether somatic mutations would be a

confounder. However, no differences in mutations were observed between the two tissues.

For annotation, findings were cleared from genes involving the highly polymorphic human

olfactory (OR) and human leukocyte antigen (HLA) clusters, and the ZNF717 gene. Genes

with truncating mutations were preferred in further investigations, as their functional effect

on the respective protein can be considered likely deleterious.

For annotation and classification of genes revealed by exome sequencing, the GeneCards

database was accessed. Categories were chosen based on Kyoto Encyclopedia of Genes and

Genomes (KEGG)530 and Biocarta531-grouping: cancer, DNA repair, immune system, signal

transduction, cell-cell interaction, transport, gene expression, chromatin regulation, cell

cycle, cell death, metabolism, skin diseases and other/unknown, see Figure 17. The category

“skin diseases“ was chosen based on the observation, that a common manifestation of

irradiation side-effects includes skin burns and necrosis of epithelial tissue378,532-534.

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Furthermore, the categories Cancer”, “DNA repair” and Immune System” were considered of

strongest interest for this project and chosen for further investigations. They are highly

represented in RS patients and do not vary significantly between the RS patient groups with

different cancers, according to the classification described above (Figure 17). The GeneCards

annotation shows a strong inter-individual variability in all categories, and no obvious

overrepresentation, which might be clearly associated with radiosensitivity, was found. Next,

the Ingenuity Pathway Analysis (IPA) program was used to assess superior pathways or

functions which might be associated with the radiosensitive phenotype. Furthermore IPA is

capable of emitting p-values of overlap (Fisher’s exact test) indicating the degree of

association between gene functions and disorders or canonical pathways (see subsection

3.3.1). Fisher’s Exact Test compares the set of molecules in the uploaded dataset to a reference set that includes all known molecules, and in this work the Ingenuity Knowledge

Base was chosen as reference dataset (Figure 8).

Figure 17 GeneCards annotation of genes with truncating mutations in RS patients Exome sequencing results of RS patients were filtered for genes with truncating mutations, which were annotated by

GeneCards database and categorized according to KEGG and Biocarta pathway suggestions. Grouping of patients was done

based on cancer type: BC (breast cancer) in panel A, other radiosensitive (RS) cancer patients (CP) in panel B (see

Supplementary table S-1) and chemoradiosensitive patients (chemo RS) in panel C. Median values of cancer, DNA repair

and immune system categories are shown. Unpaired t-tests were performed and showed no significant differences

(ns: p>0.05, panel D). Colors in the BC group represent patients MC1= green, MC3= blue and MC7= yellow, which were

functionally analyzed later.

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4.2.3 Ingenuity Pathway Analysis

4.2.3.1 Ingenuity Pathway Analysis of radiosensitive cancer patients

The IPA core analyses with the three RS patient groups revealed significant associations in

the “Diseases and Disorders” section with p-values as low as 1E-09, see Figure 18 (for

complete analysis results see Supplementary figure S-8 - Supplementary figure S-11).

Figure 18 Comparative IPA analyses between RS cancer patients Results of the “Diseases and Disorders” section of IPA core analyses performed with 11 RS BC patients, 5 RS patients with

other cancers and 3 Chemo RS patients. P-values of overlap calculated by Fisher’s exact test, are given as red dots in the p-

value range section and median values are indicated by vertical blue bars. The numbers of molecules in the dataset

belonging to each pathway are indicated on the right-hand side. Cancer” and “Organismal Injury and Abnormalities” are

highlighted with red and faint red arrows, respectively, as discussed further in the text.

A high representation of “Cancer” in the RS and chemo RS patients and “Dermatological

Diseases and Conditions” in the RS group of patients with other cancers was found. The

superior category “Organismal Injury and Abnormalities” encloses functions associated with

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injuries and abnormalities of multicellular organisms, including functions related to

abnormal tissue physiology such as lesions, ulcers, scars and wounds535. In this analysis, most

genes found in this category were also found in the Cancer” category (Supplementary figure

S-15). The category “Reproductive system disease” includes diseases and abnormalities of

the reproductive system, for example degeneration of oocytes, endometriosis and infertility

of organisms535. “Neurological disease” includes neurological system diseases such as

atrophy of axons, convulsion, dyskinesia and swelling of brain535. Most prominent hits in

categories “Neurological Disease”, “Reproductive system disease” and “Dermatological

diseases and conditions” in this analysis also relate to cancer-associated functions, as shown

in Supplementary figure S-16. The category “Hereditary Disorder” found in RS patients with

other cancers basically relates to hereditary prostate cancer (association of EHBP1, MSR1)

and hair and dental disorders. Several hits were also obtained in the category related to DNA

repair, as DNA Replication, Recombination and Repair, was one of the top networks in RS

patients, see Supplementary figure S-12). Upstream analysis revealed the transcription

regulator SMARCA4 (SWI/SNF Related, Matrix Associated, Actin Dependent Regulator Of

Chromatin, Subfamily A, Member 4) as common regulator of genes regarding RS patients,

which was identified by using the pathdesigner tool (Figure 19). SMARCA4 has been

implicated in a variety of cancers536-540, including breast cancer and binds BRCA1541,542.

Figure 19 IPA upstream analysis results of RS patients Ingenuity Pathway Analyses (IPA) upstream analysis conducted with results of exome sequencing regarding genes with

truncating mutations identified in the RS patient collection by pathdesigner tool applied to upstream network results.

SMARCA4 (SWI/SNF Related, Matrix Associated, Actin Dependent Regulator Of Chromatin, Subfamily A, Member 4) was

identified as upstream regulator, which directly regulates MICB543

(MHC Class I Polypeptide-Related Sequence B), KCNQ3543

(Potassium Voltage-Gated Channel Subfamily Q Member 3), TNFRSF9543

(TNF Receptor Superfamily Member 9) and

SPHK1543

(Sphingosine Kinase 1). IPA identified relationships between SMARCA4 and AR544

(Androgen Receptor), between

AR and RELA545

(Proto-Oncogene, NF-KB Subunit) and between AR and ESR1546

(Estrogen Receptor 1). MICA547

(MHC Class I

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Polypeptide-Related Sequence A) and STIM1543,544

(Stromal Interaction Molecule 1) are targeted by RELA; NUSAP1

(Nucleolar And Spindle Associated Protein 1) is targeted by AR548

, and TNFRSF10A549

(TNF Receptor Superfamily Member

10a), MUC20549

(Mucin 20, Cell Surface Associated) and ZNF141549

(Zinc Finger Protein 141) are targeted by ESR1. Patient

IDs are given below genes (see Supplementary table S-1 for clinical data) and corresponding rs-numbers indicate already

known variants. All unknown gene mutations were validated except indicated by *=validation was not possible. Samples, in

which the mutations were identified, are indicated. Results of the overlay-tool for diseases and functions with p-values of

overlap and numbers of involved molecules (# Mol.) are given below.

Based on the findings, that cancer/DNA repair genes are strongly represented in the RS patients, the

hypothesis was elaborated that the accumulation of mutations in cancer-related and/or DNA repair

genes may contribute to the secretory phenotype, which activates immunological responses of RS

patients after irradiation therapy. In order to investigate whether these findings are specific for

radiosensitive cancer patients, a comparison with exome data from non-radiosensitive cancer

patients and non-radiosensitive familial breast cancer patients was performed. The latter category

was included to examine whether the presumably strong genetic background in heritable breast

cancer can be identified by IPA.

4.2.3.2 Comparative Ingenuity Pathway Analysis

In order to investigate whether mutations in genes related to cancer and DNA repair

pathways are significantly enriched in radiosensitive breast cancer patients, which comprises

the biggest group of RS patients with 11 individuals, genes with truncating mutations from

11 breast cancer patients without radiation sensitivity were used as comparison. Two BC

patients without RS, MC4 and MC6, are matched pairs of RS BC patients MC1 and MC3,

respectively. The other patients were analyzed in ongoing studies in our lab (data provided

by Dr. Thilo Dörk-Bousset). 11 exomes from an additional group of patients with familial

(Fam) breast cancer were also used as comparison (data provided by Dr. Thilo Dörk-Bousset).

The question was addressed whether IPA can identify a genetic predisposition for breast

cancer in this group and how this would relate to the radiation sensitivity disposition. Figure

20 shows overlapping genes of the three datasets, which were found by IPA.

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Figure 20 Overlapping genes of datasets for comparison between cancer patients Venn diagram showing number of genes identified in each patient set (11 RS BC patients in A, 11 BC patients in B and 11

Fam BC patients in C) by Ingenuity Pathway Analysis. Numbers of overlapping genes are given in intersection areas and

associated gene symbols are shown in adjacent squares. The area shaded in blue represents genes identified in all three

datasets/patient groups.

It was hypothesized that genes, which are not restricted to RS patients, may not be involved

in the RS IR response. Therefore, all the comparisons were done in parallel with sets of

unique genes from every patient group. Figure 21 shows the results of the core analyses of

gene lists from 11 RS BC, 11 BC and 11 Fam BC patients.

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Figure 21 Comparative IPA analyses between cancer patients Results of the “Diseases and Disorders” section of Ingenuity Pathway Analysis (IPA) core analyses performed with 11

radiosensitive (RS) breast cancer (BC) patients, 11 BC patients without RS and 11 Familial (Fam) BC patients without RS. P-

values of overlap calculated by Fisher’s exact test, are given as red dots in the p-value range section and median values are

indicated by vertical blue bars. The numbers of molecules in the dataset belonging to each pathway are indicated on the

right-hand side. “Cancer” and “Organismal Injury and Abnormalities” are highlighted with red and faint red arrows in all

three groups, respectively. “Reproductive System Disease”, “Neurological Disease” and “Hereditary Disorder” are specific to RS BC and Fam BC patients and highlighted with blue, green and orange arrows, respectively. See Supplementary figure S-

20 and Supplementary figure S-21 for corresponding heatmaps.

Cancer is overrepresented in all three datasets. By comparison, the strength of the

association between the genes with truncating mutations and cancer is highest in RS BC

patients according to p-values and number of molecules, followed by Fam BC patients and

BC patients. The category “Dermatological Diseases and Conditions” is represented in all

three datasets and also shows the strongest association in RS BC patients, whereas

“Neurological Disease” and “Reproductive System Disease” is restricted to RS BC patients only and both classifications include mainly cancer categories (heatmaps of Supplementary

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figure S-20). “Hereditary Disorder” comprises a category of diseases and disorders that result

from genetic defects, and is only represented in the Fam BC patient group, showing strong

association with hereditary breast cancer, but also hereditary prostate cancer (heatmaps of

Supplementary figure S-21). More details about the core analysis results of the three patient

groups are given in form of heatmaps in Supplementary figure S-17 - Supplementary figure

S-19. They show high contingency between “Cancer” and “Organismal Injury and

Abnormalities”, as well as strongest associations of cancer-related subcategories in the

remaining categories.

A comparative analysis in IPA revealed the smallest p-values of overlap with cancer,

immunological diseases and DNA repair pathways in RS BC patients compared to BC and Fam

BC patients, see Figure 22A.

Figure 22 Pathways of interest in comparison analyses of RS BC, BC and Fam BC patient groups in IPA Comparative analyses of core analyses performed with genes including truncating mutations found by exome sequencing of

11 RS BC, 11 BC and 11 Fam BC patients in Ingenuity Pathway Analysis (IPA). Panel A shows average –log(p-value of overlap

calculated by Fisher’s Exact test) indicating association of genes in the given pathways in the 3 patient groups. The threshold indicates a p-value of 0.05, as shown by the orange horizontal line. As every superior category such as “Cancer”

or “DNA repair” includes several sub-categories, these are plotted in panel B to reveal numbers of subcategories and

involved genes in these two pathways, as they show prominent differences between groups. Sub-pathways that were found

in all three datasets and contained the highest number of genes involved, were chosen and plotted with respect to

individual –log(p-values of overlap) and number of genes in panel C. Patient groups are represented in the following colors:

RS BC = green, BC = violet, Fam BC = orange. The arrow in the bottom panel C indicates a unique pathway in the DNA repair

category that could only be identified in RS BC patients and is referred to “DNA damage response of cells”. Involved genes are given in the square box in panel B, bottom. Lines in panel C show results of linear regression performed with GraphPad

Prism.

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Each superior category is divided into several subcategories by IPA, which are exemplarily

shown in Figure 22B. For better comparison conditions, subcategories that have the highest

number of associated molecules, and are present in all three datasets, were chosen and

plotted for number of identified genes in the given pathway against the –log(p-value of

overlap), as visualized in Figure 22C for “Cancer“ and “DNA repair”. Strikingly, RS BC patients

show overrepresentation in cancer, immunological diseases as well as DNA repair. However,

it is noteworthy that a direct side-by-side comparison in the category of DNA repair is not

possible as the category with the strongest representation of the DNA damage response is

restricted to RS BC patients only (involved genes are listed in the box in Figure 22B, bottom).

Consequently, both categories (“Repair of DNA” as well as “DNA damage response of cells”)

are plotted for RS BC patients in Figure 22C, bottom. The arrow indicates the unique

subcategory “DNA damage response of cells”. Regression analyses of genes with

corresponding p-values (displayed as –log(p-value)) in the cancer and DNA repair category

indicate almost linear relationships between numbers of genes and p-value for all

subcategories. However, slight differences were observed between Fam BC and BC patients

in the subcategory “Cancer of cells” and between Fam BC and RS BC patients in “DNA repair”, respectively (Figure 22C). In both cases, Fam BC patients show the same number of

genes in the given pathway, but a stronger correlation by means of p-value.

The original category that includes DNA repair in IPA encompasses also DNA replication and

recombination535. In order to focus on the genes involved in DNA repair only, the output list

was reevaluated by means of the GeneCards database and as shown here includes solely the

DNA repair genes (Figure 22). The unfiltered output can be found in Supplementary table S-

9. The two subcategories “Repair of DNA” as well as “DNA damage response of cells” are

given in Figure 23 in the subcellular view together with the DNA damage markers H2AFX

(H2AX), TP53BP1 (53BP1), RAD51, CHEK2 and KAP1, which will be addressed in section 4.3.

To examine whether an analysis using only genes which were uniquely found in each

dataset, would provide unbiased results, the comparison analysis was performed after

removal of double hits (see Figure 20 and Supplementary figure S-22). Subtle differences

were detected in all categories, but tendencies remained similar.

Figure 23 Subcelluar view of genes associated with DNA repair sub-pathways by comparative IPA analyses

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Subcellular view of genes associated with the subcategories “DNA damage response of cells” and “Repair of DNA” of the superior category “DNA replication, recombination and repair” given by Ingenuity Pathway Analysis (IPA), see Supplementary table S-10. Findings were further restricted to solely “DNA repair” by GeneCards database analysis, see

Supplementary table S-9 for unfiltered results. Genes were identified and grouped into pathways through comparative

analyses of core analyses performed with genes including truncating mutations found by exome sequencing of 11 RS BC, 11

BC and 11 Fam BC patients in IPA. DNA repair markers H2AFX (H2AX), TP53BP1 (53BP1), RAD51, CHEK2 and KAP1 are

additionally shown in grey as they will be subject to following functional assays. Genes from the RS BC dataset are shown in

green, genes from the BC dataset in violet and genes from the Fam BC dataset in orange. NEIL1 was identified in RS BC as

well as Fam BC patients.

Moreover, superior canonical pathways identified by comparative analyses, as well as

pathways related to the cancer subcategory in the “Diseases and biofunctions” section are

shown in heatmaps in Figure 24A and B, respectively. Interestingly, both RS BC and BC

patients showed associations with dopamine degradation and inflammatory signaling,

whereas DNA DSB repair is strongly related to RS BC and particularly to Fam BC patients

(Supplementary table S-11). Results of filtering the gene lists for DNA repair genes (as

described above) are shown for superior canonical pathways and “Diseases and

biofunctions” in Figure 24C and D, respectively. Apart from a prominent attribution of the RS

BC group to ATM signaling (p-values of 0.0007 for RS BC, 1 for BC, and 0.016 for Fam BC),

DNA repair pathways were identified in all three groups, for example mismatch repair was

mostly attributed to BC patients and homologous recombinational repair mostly to Fam BC

(Supplementary table S-12). Moreover, the association between Fam BC and hereditary

breast cancer signaling comprises one of the strongest findings using this approach.

Furthermore, a relation between cell-cycle genes and the Fam BC as well as the RS BC group

was detected. Diseases and biofunctions findings in Figure 24D supplement the data shown

in Figure 22 and Figure 23, as “DNA damage response of cells” is solely found in RS BC

patients and shows the strongest contribution within the whole category (p-values of 3.81E-

10 in RS BC, 1 in BC, and 0.044 in Fam BC, respectively). “Repair of DNA” is significantly associated with all patients, however strongest in Fam BC (p-values for RS BC= 0.0003, BC=

0.0002, Fam BC= 5.97E-08, respectively).

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Heatmaps of canonical pathways identified by Ingenuity Pathway Analysis comparison tool. Panel A shows results of

superior canonical pathways in 11 radiosensitive (RS) breast cancer (BC) patients, 11 BC and 11 familial (Fam) BC patients.

Pathways of interest are enclosed by squares and marked by arrows. Panel B shows the results of the comparison analysis

in the “Diseases and biofunctions” section, filtered for “Cancer” subcategory. Panels C and D show the results of

comparison analysis with the modified datasets filtered for results obtained in the “DNA Replication, Recombination and Repair” category and further restricted to “DNA repair” as revised by GeneCards analysis, see also Figure 22. The genes

found in the “DNA Replication, Recombination and Repair” category in the three datasets are listed in Supplementary table

S-9. P-values of overlap for canonical pathway heatmaps in panel A and panel C are given in Supplementary table S-11 and

Supplementary table S-12, respectively).

Canonical pathway analyses with unique datasets were performed to assess whether

removal of the NEIL1 gene, which was found in both RS BC and Fam BC patients (Figure 20),

would alter these findings (Supplementary figure S-23C-D). No obvious differences were

observed in the DNA repair category as well as in the remaining categories (Supplementary

figure S-23A-B), which confirmed the findings shown in Figure 23 - Figure 24 and

Supplementary figure S-22, that the overlapping genes do not contribute strongly to the

outcome of the analyses.

As the previous results show the comparison of three datasets, all patients in one group are

analyzed as one dataset and inter-individual differences between patients cannot be

addressed. As some patients might contribute very strongly to the overrepresentation of

pathways, while others might have no effect, as shown for the GeneCards annotation (Figure

17), a comparison analysis with all 11 patients from one dataset was performed. Figure 25

shows the results of the comparative analyses with each patient through which a high

variability in association with the categories “Cancer”, “Immunological diseases” and “DNA repair” can be detected. Differences in the DNA repair category between RS BC and BC patients, as well as between Fam BC and BC patients are identified.

In order to supplement the IPA results, the exome sequencing results of the 11 BC and Fam

BC patients were subjected to GeneCards annotation using the categories described in

subsection 4.2.2. Furthermore, similar analyses were conducted with Reactome Pathway

Analysis491,492 and the three annotation methods were compared side-by-side, as shown in

Figure 26 and Figure 27.

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Figure 25 Comparative IPA analyses with single patients in RS BC, BC and Fam BC groups Single-patient comparative analyses of core analyses performed with genes including truncating mutations found by exome

sequencing of 11 radiosensitive breast cancer (top), 11 breast cancer (middle) and 11 familial breast cancer (bottom)

patients in Ingenuity Pathway Analysis (IPA). Each core analysis was conducted separately for each patient (represented by

individual colors) and 11 patients in each group were compared to each other. Columns represent average –log(p-value of

overlap calculated by Fisher’s Exact test) indicating association of genes in the given pathways cancer, immunological

diseases and DNA repair. The threshold was set at p-value of 0.05, as indicated by the orange horizontal line. The superior

IPA category “DNA replication, recombination and repair” was further restricted to solely “DNA repair” by GeneCards

database analysis, as described before. Patients are either named by internal labeling (Supplementary table S-1) or

according to their cancer history, if known, and in case no other internal labeling was performed. FH= family history,

ColonCa= colon cancer, CxCa= cervix cancer, ThCa= throat cancer, TNBC= triple negative breast cancer.

4.2.4 Reactome Pathway Analysis and comparison of annotation tools

As third method of annotation, the Reactome browser was accessed, which is a well

established pathway analysis database491,492. Only about half of the DNA repair genes, which

were found by GeneCards and IPA, could also be found by Reactome, see Figure 26.

Therefore, a direct comparison of the results is not possible. Underlined genes as shown in

Figure 26 (left-hand side) were picked up by all three methods. For results regarding the

remaining two prioritized categories “Cancer” and “Immune System” see Supplementary

table S-14–Supplementary table S-15.

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Figure 26 Comparison of annotation methods: DNA repair pathway

DNA repair genes, which were identified by exome sequencing of 11 radiosensitive (RS) breast cancer (BC), 11

BC and 11 familial (Fam) BC patients, were annotated by GeneCards, Reactome and Ingenuity Pathway Analysis

(IPA), and are given in the table (left-hand side). Genes, which were identified by all three annotation methods,

are underlined. The Venn diagram on the right-hand side shows overlapping findings by the three methods of

the RS BC group and numbers of overlapping genes are indicated.

As shown in Figure 27, nominally significant differences were only detected between the RS BC and

the BC patients in the category “DNA repair” by two of the three annotation methods: GeneCards

annotation at p-value: 0.002 and IPA annotation at p-value: 0.019. The percentage of truncating

mutations in DNA repair genes is highest in RS BC patients, closely followed by Fam BC patients and

lowest in BC patients, see Figure 27. Apart from known cancer and DNA repair genes, mutations in

the TNF-receptor superfamily genes TNFRSF9 and TNFRSF10A were identified in two patients, the

latter of which was recently related to lymphocyte radiosensitivity and prediction of dermatitis as

radiation consequence550. As these genes were, however, not directly related to DNA repair by any of

the annotation tools (but were part of the ”Cancer” and “Immune System” categories, see

Supplementary table S-15 for TNFRSF10A identified in RS BC), they were not included in the “DNA repair” category. Furthermore, they are both subject to regulation by SMARCA4 according to IPA, as shown in Figure 19.

All the results shown in this subsection were obtained by using validated exome sequencing

data, see subsection 4.2.5.

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Figure 27 Comparison of annotation tools for DNA repair, cancer and immune system genes

Genes, which were identified by exome sequencing in 11 radiosensitive (RS) breast cancer (BC), 11 BC and 11

familial (Fam) BC patients, were annotated by GeneCards, Reactome and Ingenuity Pathway Analysis (IPA)

databases. Median of genes (percentages based on total number of mutations in the respective patient) in the

priority categories “DNA repair” (panel A), “Cancer” (panel B) and “Immune system” (panel C) are shown and

unpaired two-tailed t-tests using GraphPad Prism Software were applied. Significance levels are given by

p ≤ 0.01 (**), p ≤ 0.05 (*), or P > 0.05 (ns = not significant). Patients MC1= green, MC3= blue, MC7= yellow are

highlighted, as we obtained TERT immortalized fibroblasts from these individuals (see subsection 4.3.1).

MC4= light green and MC6= light blue are “matched pairs“ considering age and disease stage to the patients MC1 and MC3, respectively, see Supplementary table S-1.

4.2.5 Validation of exome sequencing data

After annotation, genes with truncating mutations were prioritized according to association

with cancer, DNA repair, immune system, cell-cell interaction, cell cycle, cell death and skin

diseases. 315 mutations out of 587 for 19 RS patients and the two matched pairs MC4 and

MC6 from the BC group were subjected to validation sequencing in the course of this

project. Dr. Natalia Bogdanova, Julia Enssen and Louisa Weinhold kindly helped with PCR

amplification and sequencing. In total, 223 mutations could be validated while 70 emerged

to be false-positives (Supplementary table S-6–Supplementary table S-7). In 22 cases the

validation procedure was not successful due to technical problems, for example poly-A

regions, C/G-rich regions, or highly repetitive sequences. 272 mutations were not part of the

validation sequencing progress as they failed prioritization requirements, for all details see

Supplementary table S-8. The remaining 9 BC and 11 Fam BC exomes were part of former

studies and previously validated data was provided for comparison studies only.

https://www.dict.cc/englisch-deutsch/prioritization.html

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In summary, strong interindividual variability in DNA repair, cancer and immune system

related truncating gene mutations was observed in RS BC patients as well as in the two

comparison groups. The comparative analyses in IPA revealed overrepresentation of the

category “Cancer” in RS BC patients compared to BC and Fam BC patients. Truncating

mutations in DNA repair genes are significantly enriched in RS BC patients compared to BC

patients after annotation with GeneCards and IPA. In order to be able to carry out functional

radiosensitivity assays, fibroblasts from radiosensitive breast cancer patients MC1, MC3 and

MC7 were immortalized with TERT, as described in the next section.

4.3 Generation of cell cultures and functional assays

Primary human fibroblasts can only be cultured in vitro for a very limited time (usually up to

12–14 passages) until they undergo differentiation or replication-induced senescence495-497.

As primary cells from individual patients are difficult to harvest and especially hard to

surrogate if the patient has left the clinic or might have died, cells need to be immortalized

in order to generate long-lived stably proliferating assay tools. Therefore, the TERT

immortalization assay was established to generate immortal cells which can theoretically be

used in culture for indefinite time.

4.3.1 Immortalization of primary skin fibroblasts from RS BC patients

An example of the TERT immortalization progress using primary cells of patient MC7 is

shown in Figure 28A. Co-transfection of the TERT plasmid, which also includes the resistance

to hygromycin B as selection marker, with a GPF reporter plasmid was performed by

nucleofection. GFP-positive cells could be detected 24 h after nucleofection and it was

assumed that if plasmid uptake occurs, a cell will take up both of the plasmids. Depending on

the viability of the cells, two to three days after recovery from the nucleofection procedure,

the hygromycin B selection was started. During this process, about 70 % of the cells died,

which might have not taken up the TERT plasmid (see Figure 28 panel A, second picture).

Depending on the transfection efficiency, colonies of immortal cells grew out after several

weeks, as shown for MC7 cells in Figure 28A, right-hand side. Immortalized cell cultures from

patients MC1, MC3 and MC7 could be successfully generated with positive TERT

immunoreactivity as shown in Figure 28B. After the second hygromycin B boost, however,

TERT could not be detected in MC1 cells anymore, although it had initially been present.

Nevertheless, the MC1 cell line continued growing in the same manner as MC3 and MC7.

In all three patients, a significant representation of mutations in DNA repair genes was

detected by IPA, as shown in Figure 29. The mutations in HERC2, RAD51C and ABL1 all lead

to truncated versions of the respective proteins, whereas the FANCL variant encodes an

alternative C-terminus, but the protein might still be functional222 551-553, see Supplementary

figure S-24, Supplementary figure S-25, and Supplementary figure S-26. The FANCL variant

was not analyzed further since, in a side-project, it turned out not to be associated with

breast cancer551 and the functional impact of this variant was uncertain. The protein level of

ABL1 (c-abl) in MC7 TERT cells was analyzed by western blot with two different antibodies

and showed a reduction by about 50 % (48,6+/- 15 %) compared to the control BJ5TA

(Supplementary figure S-24). This appeared consistent with the heterozygous status of these

cells. Furthermore, immunocytochemical analyses were performed in MC3 cells to assess a

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potential relevance of the RAD51C mutation for homologous recombinational repair as

monitored through RAD51 foci. This experiment revealed significant impairment of RAD51

foci formation in both untreated and irradiated MC3 primary cells compared to controls507.

The splice variants in RBBP6 and NPAT were predicted to be silent or leaky by MaxEntScan

and were not investigated further (Supplementary figure S-25-Supplementary figure S-26).

Thus, the most relevant DNA repair gene mutations in the three newly established RS BC

fibroblast lines were considered to target HERC2 in MC1, RAD51C in MC3 and ABL1 in MC7.

Figure 28 Immortalization of MC1, MC3 and MC7 primary fibroblasts with TERT

Panel A shows a typical course of the TERT immortalization procedure starting with detection of GFP 24 h after

nucleofection (left), white arrows indicating cells positive for GFP. About 70–80 % of cells die during the

hygromycin B selection process (middle) until immortalized cells grow colonies (right). Panel B shows western

blot results indicating immunoreactivity of TERT as detected compared to the positive control BJ5TA after

immortalization. Different blots are separated by vertical lines. Scale= 75 µm.

Figure 29 Mutations in DNA repair genes in RS BC patients MC1, MC3 and MC7

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Results of comparative Ingenuity Pathway Analysis indicating enrichment in DNA repair genes in patients MC1

(green bar), MC3 (blue bar) and MC7 (yellow bar), as marked by red arrows. Positions in the human reference

genome (version 37) and types of validated mutations, which were identified by exome sequencing, are given

in the table below. For prediction of mutation effects, see Supplementary figure S-24, Supplementary figure S-

25, Supplementary figure S-26).

4.4 Functional studies in TERT immortalized cells of RS BC patients

4.4.1 ATM signaling after irradiation

To investigate the impact of the DNA damage response in cell culture models of the three

highly radiosensitive breast cancer patients MC1, MC3 and MC7 (Supplementary table S-1),

the immortalized cells were characterized through ATM-specific CHEK2 and KAP1

phosphorylation as early as 30 min after irradiation by western blot to analyze early signaling

of DSBs. Furthermore, γH2AX and 53BP1 foci kinetics were evaluated from 1 h up to 48 h

after IR, and cells were furthermore grown in colony survival as well as senescence assays to

follow the long-term IR response of these cultures for up to three weeks.

The checkpoint kinase CHEK2 as well as the transcriptional regulator protein KAP1 (also

known as TRIM28554) are both well known targets of the ATM kinase (see section 1.1.2 and

subsection 1.3.2) and also established DNA damage response markers. TERT immortalized

MC1, MC3 and MC7 cells were irradiated with 1.5 and 6 Gy and harvested at 30 min after IR

to investigate early activation of these proteins via phosphorylation by ATM. These data

were generated in the course of the bachelor thesis of Katharina Stemwedel.

As shown in Figure 30, detection of both proteins was possible in all analyzed cell lines and

significant increments were observed between 1.5 Gy and 6 Gy in all cultures after

densitometric analyses, except MC1 TERT (n= 3, Supplementary table S-16). In these cells, no

significant increment in p-KAP1 levels between 1.5 and 6 Gy was observed, probably due to

already pronounced p-KAP1 signal after 1.5 Gy IR treatment. However, increase of p-KAP1

levels between 0 and 6 Gy was highly significant in these cells, therefore indicating an IR-

induced effect (p-value of < 0.0001). MC7 TERT already showed a significant elevation of p-

KAP1 levels between 0 and 1.5 Gy (p-value: 0.021) and pSer19-CHEK2 levels in MC1 TERT

were lower at 6 Gy compared to the other cultures, however, not significantly (p-value:

0.056 for comparison to BJ5TA).

Furthermore, pSer824-KAP1 immunoreactivity appeared to be decreased in RS BC TERT cells

at 30 min after 1.5 Gy irradiation compared to BJ5TA, however, this was only significant

between MC7 TERT and BJ5TA (p-value: 0.04) and significantly higher levels of p-KAP1 were

detected in MC1 TERT compared to MC7 TERT after 1.5 Gy IR (p-value: 0.025).

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Figure 30 ATM targets CHEK2 and KAP1 after irradiation in RS BC TERT cells Western blot results of early ATM signaling in TERT immortalized RS BC fibroblasts from patients MC1, MC3 and MC7 and

healthy BJ5TA wildtype control. Cells were irradiated with 1.5 Gy or 6 Gy and harvested after 30 min together with non-

irradiated controls (0 Gy). Antibodies against CHEK2 phosphorylated at serine 19 (Ser19) (p-CHEK2), KAP1 phosphorylated

at serine 824 (Ser824) (p-KAP1), and β-actin as loading control were used. The vertical line indicates that samples were on

two different blots with a control each. Three biological replicates were analyzed and representative blots are shown.

4.4.2 Kinetics of DNA damage recognition and repair in TERT immortalized cells of

RS BC patients

For a more detailed and extended inspection of DSB repair kinetics in the TERT immortalized

MC1, MC3 and MC7 cells, γH2AX and 53BP1 foci formation and resolution analyses were

performed. Cells were irradiated with 1 Gy and stained after 1 h, 6 h, 24 h, and 48 h by

immunocytochemistry techniques. Foci numbers were counted and are shown in Figure 31.

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Prism Software and significance levels are given by p ≤ 0.001 (***), p ≤ 0.01 (**),p ≤ 0.05 (*), or P > 0.05 (ns = not

significant). At least three biological replicates were analyzed, given by the number of symbols of each column.

There were only subtle differences between the control and the RS cell cultures in foci

kinetics of γH2AX as well as 53BP1 foci. Initiation of foci formation 1 h after IR was functional

in all cultures, however, differences in foci resolution were visible between MC1 TERT and

the remaining three cultures. MC1 TERT seemed to return slower to the zero state, as the

drop between 6 h and 24 h was not significant for both γH2AX as well as 53BP1 foci in these

cells. Numbers of γH2AX and 53BP1 foci in MC3 TERT and MC7 TERT cells declined faster

after 6 and 24 h compared to MC1 TERT, however, similar to the control BJ5TA cells. The

final drop between time points 24 h and 48 h was only significant in MC1 TERT cells for both

analyzed proteins. Comparisons between cell lines revealed significant differences between

53BP1 foci numbers at the later time points of 24 h and 48 h. MC1 TERT cells displayed

significantly more 53BP1 foci at 24 h after 1 Gy IR compared to BJ5TA (p-value: 0.014), while

foci numbers in MC1 TERT were also significantly reduced compared to MC3 TERT at 24 h (p-

value of 0.004) and compared to MC7 TERT at 48 h (p-value: 0.002). For complete analysis

see Supplementary table S-16 and Supplementary table S-17.

Taken together, early as well as extended ATM signaling is functional in all four cell lines

tested, although, slight reductions in p-CHEK2 Ser19 levels 30 min after 6 Gy and as

marginally narrowed γH2AX as well as 53BP1 foci numbers at 1 h after 1 Gy of radiation were

observed in MC1 TERT cells. MC3 as well as MC7 TERT cells both showed a significant drop in

γH2AX as well as 53BP1 foci numbers between 6 h and 24 h after 1 Gy IR, whereas this was

not observed in MC1 TERT cells.

4.4.3 Previous studies on RAD51 foci formation in primary RS cells and comparison

to results obtained with TERT RS cells

In previous studies with MC3 and MC7 primary cultures, an impairment of RAD51 foci

formation 4 h after 6 Gy IR was observed, which was different in MC3 cells compared to ADP

controls507. Results in primary cells indicated significant increase of foci-positive cells after IR

in ADP as well as MC7 cells (p-values of 0.002= ADP and MC7, 0.08= MC3). MC3 primary cells

showed significantly less foci after IR compared to ADP as well as MC7 (p-values of 0.0002

and 0.0007, respectively). In order to investigate whether the TERT immortalization could

influence the DNA damage response via RAD51 foci formation in these cultures, these

analyses were repeated in MC3 TERT and MC7 TERT, in comparison to MC1 TERT (which was

not included in the primary cell experiment) and BJ5TA. Results are shown in Supplementary

figure S-27 and indicated, that the immortalization procedure indeed could have an impact

on RAD51 foci formation in cells from patients MC3 and MC7. However, background levels of

repair in the unirradiated condition were also strongly elevated in BJ5TA cells compared to

ADP cells. Therefore, the TERT immortalization procedure might have a strong effect also on

wiltype fibroblasts, compared to immortalization with large T in ADPs. In these studies, the

MC7 TERT showed the strongest impairment of RAD51 foci formation after IR, which was

significant compared to BJ5TA (p-value of 0.009). Increase in numbers of foci-positive cells

was only significant in BJ5TA after IR (p-value of 0.004). Normalization to the background

repair levels observed in unirradiated samples revealed significant impairment of RAD51 foci

formation after IR only in MC3 primary and MC7 TERT compared to respective controls (p-

values: MC3: 0.017, MC7: 0.087, MC1 TERT: 0.229, MC3 TERT: 0.607, MC7 TERT: 0.008).

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As early steps in DNA damage sensing and repair seemed to be – despite subtle differences –functional in all RS cultures, and repair foci of γH2AX as well as 53BP1 at 48 h were

comparable to the control cells, it was tempting to investigate cellular survival after IR for an

extended time period as functional endpoint of radiosensitivity in these cultures, as will be

described in the next subsections.

4.4.4 Colony survival after irradiation as functional endpoint

In order to evaluate colony survival as a consequence of functional DNA repair after IR

damage over a time period of up to three weeks, cells were seeded in very low densities in

culture flasks and survival by means of colony formation ability was monitored. The colony

survival assay is a very well known and established method and has been known as the “gold standard of radiosensitivity” for many years508. The cells were seeded in the lowest densities

possible to achieve a good balance between single cell status and spatial proximity to allow

colonies arising from single cells, as well as cellular communication to take place. Colony

formation was monitored for up to three weeks and crystal violet stained cells are shown in

Figure 32.

Figure 32 Colony survival of TERT immortalized MC1, MC3 and MC7 cells after irradiation compared to BJ5TA Panel A shows the macroscopic view of colony survival results performed in T25 cell culture flasks. The cells were seeded in

the following densities given in cell numbers per flask: BJ5TA - 0 Gy = 2500 and 4 Gy = 10.000 cells; MC1 TERT - 0 Gy = 5000

and 4 Gy = 20.000; MC3 TERT - 0 Gy = 5000 and 4 Gy = 16.000; MC7 TERT - 0 Gy = 5000 and 4 Gy = 20.000, and have been

stained with crystal violet after 21 days after IR or without IR (0 Gy). Selected areas of panel A, indicated by numbered

white squares, were magnified in panel B for better visualization of colonies. Panel C shows microscopic views of flasks

above in 4x (left panels), 20x or 40x magnification (right panels). Cells with altered morphology are marked by white arrows

in MC3 TERT cells. Scale bars= 100 µm, except top left-hand side picture of panel C= 1000 µm.

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It was very difficult to receive colonies from the radiosensitive cell cultures, even without IR.

In the traditionally utilized 6-well format, colony formation was only possible for the BJ5TA

cells, see Supplementary figure S-29A. For each cell culture, different seeding conditions

were established and collagen-, as well as gelatin-coated plates were used, see

Supplementary figure S-28. Furthermore, the cells were subjected to a boost with 10 µg/ml

hygromycin B (10H), which should activate TERT expression, to ensure that the failure of

colony survival is not due to loss of TERT during subsequent passaging after immortalization.

No changes were observed whether the cells were supplemented with 10H or normal

growth medium. Collagen-coating improved cell growth in the MC3 TERT cells, however, this

could not be considered as true colony formation because cells rather assembled together in

one region of the well than arising from colony-initiating single cells (Supplementary figure

S-28). None of the coatings had any effect on either survival and assembly of cells or colony

formation in MC7 TERT cells. By contrast, the control fibroblast line BJ5TA grew well in all

formats and coating conditions applied.

Using T25 flasks instead of 6-well plates enabled colony growth of all cultures in unirradiated

condition, see Figure 32A, top row. Characteristically, MC3 and MC7 TERT cells grew

preferably at the edge of the flasks and only very small colonies of MC3 TERT cells formed in

the middle of the flask after IR, while MC7 TERT did not show any colony formation in

irradiated flasks. In a different experiment, small colonies of MC3 TERT cells were observed

in the middle of the flask in the unirradiated condition when seeded in lower densities, see

Supplementary figure S-29C. MC1 TERT however, although strongly reduced, showed some

colony formation and size similar to BJ5TA when seeded in high densities, see Figure 32, also

after 4 Gy IR. This dose was chosen as medium dose to conduct comparative analyses with

all four cultures, considering the range of 2 Gy - 8 Gy, which is common for CSA508, and was

applied during establishment of the method for each cell line. In total, 7 out of 7

experiments for BJ5TA in T25 flasks were successful, while MC1 TERT only formed colonies in

1 out of 3 experiments, MC3 TERT formed only one very small colony in 1 out of 3

experiments and MC7 failed to yield any colonies after IR (n=3 for 4 Gy). Results were similar

for doses 2 Gy, 6 Gy and 8 Gy tested for MC3 TERT, MC7 TERT and BJ5TA cells.

Changes in the shape and granular pattern of especially irradiated cells of MC3 TERT and

MC7 TERT were observed, which are indicated by white arrows in Figure 32. These variations

were also detected through intensity changes of the crystal violet staining, as closely

assembled, small and round cells are stained darker than cells with flattened and granular

morphology, see also Supplementary figure S-29. Whereas BJ5TA and MC1 TERT cells looked

similar in the middle and at the edge of the flasks, MC3 TERT cells, which have assembled

closely at the edges, retained a rather normal morphology. However, cells which were in

single cell status (shown by white arrows in Figure 32C, bottom) were considerably bigger

and displayed flattened as well as granular morphology. These morphological changes

appeared in MC3 and MC7 TERT cells independent of their localization in the flasks especially

after IR.

For better understanding of the process of morphological changes and failure of colony

survival in the radiosensitive cell cultures after IR, the time course of cellular appearance and

colony outgrowth with and without preceding IR was monitored. Figure 33 shows a typical

course of colony formation over 7 days (panels B - C) and 21 days (panels D - E), respectively,

after IR with 4 Gy. Alterations in the morphology of cells particularly appeared in irradiated

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flasks of the RS cultures as early as 7 days after IR, and examples of single cells with changed

shape are indicated by red arrows. At this time point, the BJ5TA had already started to form

colonies (panel C, top row). Similar to Figure 32, crystal violet stained cells are shown in

panels D - E of Figure 33, showing colonies located at the middle (M) of the flasks in all

cultures (except MC3 TERT at transition area, panel D) and colonies located in the middle

after IR only in BJ5TA and MC1 TERT cells. MC3 TERT cells assembled preferentially at the

edge (E) of the flasks after IR (apart from the single colony shown in Figure 32), while closely

assembled cells with altered morphology were observed in MC7 TERT cells throughout the

whole area of the flask after 4 Gy IR (panel E).

Figure 33 Time course of colony formation assay in TERT immortalized MC1, MC3 and MC7 cells Microscopic view of colony survival assays performed with BJ5TA, MC1 TERT, MC3 TERT and MC7 TERT cells grown in T25

flasks. Panel A shows single cells 24 h after seeding in the unirradiated control flasks, while panel B shows the same flasks 7

days after seeding. Single cell cultures, which have been growing for 7 days after 4 Gy IR, are shown in panel C and

morphologically altered cells are indicated by red arrows, which were predominantly found in the radiosensitive cell lines.

Panel D and E show crystal violet stained cultures after 21 days in either unirradiated (D) or 4 Gy irradiated state. The area

of the flask, in which the picture was taken, is indicated by M= middle or E= edge. Transition areas are depicted as

“edge/middle” (E/M). Scale bar = 100 µm.

As the altered morphology of the cells was overrepresented in RS cell cultures following IR,

the question was adressed whether this change could represent IR-induced senescence.

Senescence is a known form of cell death following endogenous as well as exogenous

stresses, such as insults by reactive oxygen species formed after radiation exposure (see

subsection 2.3.6).

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4.4.5 Irradiation-associated senescence as functional endpoint

Due to the fact that the application of the colony survival assay as reliable functional

endpoint failed, because it was not evaluable in MC3 TERT and MC7 TERT cells after IR, it

was next investigated whether the compromised colony formation capacity in these cells

could be triggered by early onset senescence after IR. The senescence-associated β-

galactosidase assay was performed at 24 h, 48 h and 7 days after 4 Gy IR, and cells were

screened for development of blue color under a light microscope by comparison with non

irradiated samples.

Initially, a pilot experiment was conducted with all three radiosensitive cultures compared to

BJ5TA control cells, to determine the cell line with the strongest response compared to the

control. Figure 34 shows the evaluation of β-galactosidase-negative cells (non-senescent

cells), as counted by two different observers.

Figure 34 Pilot experiment to determine senescence after irradiation in TERT immortalized RS BC cell lines Evaluation of the senescence-associated β-galactosidase assay given in percentages of non-senescent cells, which were β-

galactosidase-negative and normally shaped, referred to total numbers of counted cells under a light microscope (panel A)

and further normalized to unirradiated controls (panel B). Cells were analyzed by two different observers (light petrol

blue= K. Neuhäuser and dark petrol blue= K. Stemwedel) and median values were tested by two-tailed unpaired t-tests

using GraphPad Prism Software. Significance levels are given by p ≤ 0.01 (**), p ≤ 0.05 (*), or P > 0.05 (ns = not significant).

A range of 75–175 cells at different random positions of the well was counted for each condition and β-galactosidase-

negative cells with altered cell shape were excluded from the counting process. Raw data are shown in Supplementary table

S-19.

A decline in the proportion of non-senescent cells after IR with 4 Gy was detected in all four

cultures, including the control. However, significant differences between residual cells after

7 days were not detected in MC7 TERT cells and were particularly pronounced in MC3 TERT

cells (Figure 34A and Table 20).

In order to investigate whether these changes could be attributed to IR, values from

irradiated cultures were normalized to the 0 Gy controls, see Figure 34B. This plot indicated

significant differences particularly in MC3 and MC7 TERT cells (see Table 20 for

corresponding p-values). Although not detectable by eye, MC1 TERT cells showed a

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significant decrease in non-senescent cells after normalization at 24 h after IR (p-value=

0.03) compared to BJ5TA.

Table 20 P-values of senescence analysis in radiosensitive cell cultures after irradiation compared to BJ5TA

MC1 TERT compared

to BJ5TA

MC3 TERT compared

to BJ5TA

MC7 TERT compared

to BJ5TA

7 d after 4 Gy 0.021 0.008 0.092

7 d after 4 Gy

normalized

0.22 0.022 0.042

As the steepest decline in the proportion of non-senescent cells after IR was observed in

MC3 TERT cells, this culture was chosen for further experiments, shown in Figure 35.

Figure 35 Irradiation-associated senescence in MC3 TERT cells compared to BJ5TA Non-senescent cells counted in the senescence-associated β-galactosidase assay after 4 Gy IR in BJ5TA and MC3 TERT cells.

Percentages of non-senescent cells, which were β-galactosidase-negative and normally shaped, with reference to total

numbers of counted cells under a light microscope (panel A) and further normalized to unirradiated controls (panel C) are

given. Panel B shows examples of β-galactosidase staining (blue areas) in unirradiated cells (upper panel), 7 days after 4 Gy

IR (middle planel) and in positive control cells in different densities (lower panel). Positive control 1 and 2 were very high

passage primary fibroblasts, which were known to have entered quiescence due to extended passaging in culture. Scale

bar = 100 µm. Median values of 3 independent experiments for the 9 day value and 4 independent experiments for all other

time points were analyzed by two-tailed unpaired t-tests using GraphPad Prism Software, and significance levels are given

by p ≤ 0.001 (***), p ≤ 0.01 (**), p ≤ 0.05 (*), or P > 0.05 (ns = not significant). Numbers of counted cells ranged between

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75 - 175 cells at different random positions of the well. β-galactosidase-negative cells with altered cell shape were excluded

from the counting process. Raw data are shown in Supplementary table S-20.

Figure 35 shows results of four independent experiments performed with BJ5TA and MC3

TERT for all time points, except 9 days after 4 Gy IR, as this time point was chosen to be

added after the first experiment was finished. Panel A shows a significantly lower proportion

of non-senescent cells in MC3 TERT cells compared to BJ5TA in all tested conditions (for p-

values see Table 21). Especially following IR with 4 Gy, differences between the two cultures

were highly significant. To investigate whether these differences are IR-initiated, the

nonsenescent cells were normalized to respective unirradiated controls, which is shown in

Figure 35C. After normalization, percentages of non-senescent cells were only significantly

reduced at 48 hours and 7 days after 4 Gy IR in MC3 TERT cells compared to BJ5TA. Examples

of the output data are given in Figure 35B, which shows β-galactosidase-positive (blue) and

β-galactosidase-negative (transparent) cells in the two cultures compared to two positive

controls.

Table 21 P-values of senescence analysis in MC3 TERT cells compared to BJ5TA control

0 Gy 24 h after 4 Gy 48 h after

4 Gy

7 d after 4 Gy 9 d after 4 Gy

MC3 TERT

compared to

BJ5TA

0.027 0.0005 < 0.0001 0.009 0.007

MC3 TERT

compared to

BJ5TA

normalized

– 0.744 0.002 0.023 0.079

As culture conditions for the two cell lines were slightly different, additional tests were

performed. To exclude effects of the MC medium on accelerated senescence in culture, a

side-by-side comparison of BJ5TA cells grown in parallel in their usual medium as well as in

MC medium, was carried out. No significant differences between BJ5TA cells grown in

regular medium and MC medium were detected (data not shown). Furthermore, to test

whether hygromycin B supplementation exerts any influence on the senescence progress in

MC3 TERT cells, a side-by-side comparison of MC3 TERT cells growing in normal MC medium

and MC medium supplied with hygromycin B was performed. For both conditions, similar

results were obtained and differences were not significant (data not shown).

The data obtained for BJ5TA and MC3 TERT cells were subjected to regression analysis with

GraphPad Prism software, see Supplementary figure S-30. Data were fitted to an exponential

decay (one-phase) model and correlations with R2>0.5 were obtained for both cell lines.

Furthermore, genes identified in BC, Fam BC and the complete cohort of RS patients were

compared with a list of genes recently correlated to aging555, by using Venny 2.0. None of

the genes from the BC patient group were overlapping with the published findings but

BRCA2 in the Fam BC and also AKR1C2 (Aldo-Keto Reductase Family 1 Member C2) and

DHCR7 (7-Dehydrocholesterol Reductase) in the RS patient dataset were shared by the

aging-associated group of genes, see Supplementary figure S-31.

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5 Discussion In the past decades, several attempts have been made to decipher the underlying genetic

background of individual radiosensitivity and many approaches aimed at identification of

prognostic markers prior to radiation treatment (section 2.4). In this work, three

methodological strategies were followed to characterize clinical and cellular radiosensitivity

(compare Figure 11).

5.1 TPT1 as candidate marker for individual radiosensitivity

TPT1 was investigated as candidate for individual radiosensitivity as it has been implicated in

DNA repair and especially, ATM signaling265,267. Previous reports have shown that TPT1

directly regulates ATM activity in Drosophila melanogaster cells556, that IR furthermore

increases TPT1 levels in nuclei of human AG1522 WT cells in an ATM-dependent manner and

that TPT1 colocalizes to radiation-induced foci to actively participate in DNA repair265. These

features of TPT1 could make this protein particularly useful as a biomarker for radiation

exposure and a possible target for radiosensitization. Furthermore, a recent study has

confirmed the finding that TPT1 can be upregulated in tumor cells and found that

inactivation of TPT1 can sensitize cancer cells to DNA damaging agents267. Also, its strong

association with tumor progression and severity of the disease pointed to the possibility that

TPT1 could promote genetic instability259 260 263 268 269 557-560. However, a previous study in our

lab did not find a strong association of mutations in the TPT1 gene with breast cancer

predisposition475.

Ionising radiation induces DNA double strand breaks (DSBs) that are signaled via ATM kinase,

which is activated rapidly after IR by direct or indirect pathways561 (subsection 1.3.2). In its

activated form, ATM can phosphorylate (and mostly activate) many downstream targets, for

example KAP1, CHEK2, or the histone H2AX leading to γH2AX. The activation of γH2AX

represents a very early consequence of DNA damage562, and it furthermore serves as a

platform to recruit additional proteins working in the DNA damage response. Subsequent

recruitment of numerous DNA repair or damage-signaling factors to the break is mediated

by chromatin modification and/or direct interactions of these factors with γH2AX562. The role

of TPT1 in this context is presently poorly understood, although TPT1 has been shown to

exhibit a broad spectrum of cellular functions including apoptosis, cell survival and DNA

damage sensing and repair265 563 564.

5.1.1 No evidence for a role of TPT1 in early ATM signaling

In this study, there was no indication of effects of TPT1 on ATM function after low or high

dose IR by assessing KAP1-phoshorylation on Ser824 in MCF10A and ADP cells, although this

phosphorylation site is a main target of ATM205,206,527,528. Similarly, no alterations in p-CHEK2

Ser19 levels after TPT1 depletion were observed. Although direct interactions between ATM

and TPT1 have been found in human cell cultures and also in fruit fly in vivo models after

IR265,556, ATM, 53BP1 or γH2AX had not been identified as being part of the potential TPT1

interactome by two recent studies using HeLa cells266,267. Furthermore, TPT1 does not seem

to be necessary for e. g. the translocation of ATM to the nucleus and formation of IR induced

ATM foci556. Interestingly, ATM depletion decreased TPT1 foci formation although it still

translocated to the nucleus556. These published findings using a Drosophila model indicate

that TPT1 does not seem to be necessary for ATM function, which is consistent with results

presented in this thesis. However, vice versa, the depletion of ATM seems to affect TPT1 foci

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formation in Drosophila but not its nuclear translocation. In the presented work, however,

neither IR-induced TPT1 foci nor a prominent localization of TPT1 to the nucleus in human

cells generated from skin or breast epithelium were detected, indicating a distinct function

of TPT1 in cells of different origin.

5.1.2 No evidence for nuclear translocation or chromatin binding of TPT1 upon

irradiation

In the course of this work, no changes of TPT1 levels in whole cell extracts after ATM

inhibition and IR were detected in both ADP and MCF10A cells, while nuclear forms of TPT1

were visible 30 min after IR with previous ATM inhibition in MCF10A cells. However, the

amount of nuclear TPT1 was not affected by ATM inhibition and chromosome-bound TPT1

was not detectable. A previous study within this project using lymphoblastoid cell cultures,

indicated some chromatin binding of TPT1 only in one out of three WT cell lines477. This,

however, did not change after IR, and there was only a slight increase in nuclear TPT1 after

IR in two of the three cell lines.

Consistently, no translocation of TPT1 to the nucleus and no formation of nuclear TPT1 foci

was detected by ICC in several cell lines and the localization of TPT1 did not change after IR,

which is partially in line with published findings265,267,556. Although a spotty pattern of TPT1

was observed in five cell lines (which was validated in two of the cell lines with a second

TPT1 antibody), this pattern was different from foci, did not increase after IR and could

similarly be detected in the cytoplasm. In some cells, TPT1 seemed to assemble in the

vicinity of the nucleus after IR, but did not localize to the nucleus itself, as was confirmed by

confocal analyses.

The finding that TPT1 was not enriched in chromatin fractions after IR in several cell lines is

consistent with the absence of radiation-induced TPT1 foci. TPT1 has previously been

reported to show a granular localization pattern in the vicinity of and around the nucleus in

ovarian epithelial cells565. Furthermore, a spotty pattern of TPT1 in ovarian carcinoma cells

was described in the literature, while TPT1 was found to be present in the cell nucleus or cell

periphery in other cell types, thus presenting evidence for cell type dependent variation of

TPT1 localization259,265,566. Altogether, cytoplasmic as well as nuclear localization of TPT1 is

known256 557, and cell-type specific as well as cell-growth specific variations have been

reported263 566 567. However, clearly as such identified TPT1 foci were only described by Hong

et al. in the fruit fly556 and Zhang et al.265 in primary human fibroblasts and could not be

reproduced by Li et al.267 in a recent study using HeLa cells.

Three different antibodies directed against TPT1 were applied in this work, one of which was

also used by Zhang et al.265. The conflicting findings addressing the localization of TPT1 and

its capability of forming visible foci raise the question whether the specificity of the

antibodies could be confirmed. In the presented thesis, a mix of three TPT1 siRNAs, which

has also been applied by Zhang et al.265, was used for silencing. The specific effect of this

siRNA mixture could be confirmed by western blot (showing no additional bands) as well as

immunostainings in ADP and MCF10A cells. This renders the possibility of unspecificity of the

antibody unlikely.

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There is evidence that the increase of TPT1 stability and elevation of immunoreactivity after

IR could be dependent on its initial level in the analyzed cell line. Zhang et al. found a

prominent upregulation in whole cell extracts, nuclear translocation as well as foci formation

of TPT1 after IR in primary wildtype fibroblasts. No detailed investigations were made to

determine the basal levels of TPT1 in that work, however, it was shown to be similar to the

housekeeper α-tubulin in the primary cells265. Cancer cell lines with different endogenous

TPT1 levels were addressed by Li et al267. The mutant cervical cancer HeLa cells, which were

constructed to express low-levels of TPT1, did only show marginal increase of endogenous

TPT1 after DNA damage and no nuclear translocation or nuclear foci formation was

observed. In breast cancer MCF7 cells with high endogenous TPT1 levels, however, the

persistent activation of γH2AX and prolonged retention of RAD51 foci after TPT1 silencing

was significant 12 h after 10 Gy IR267.

Taken together, it has been shown in the literature that TPT1 knockdown accounts for

persistent γH2AX foci early after low-, and medium-dose IR265, and also has a late effect after

high-dose IR267. However, those studies used either primary or ovarian/breast cancer cells.

Therefore, results obtained in spontaneously immortalized breast epithelial cells (MCF10A),

SV40-immortalized ADP and the TERT-immortalized BJ5TA (and especially, the additional RS

MC3 TERT cells) might not be directly comparable. However, the results in the TNBC cell

lines obtained in this thesis account for a strong variability of TPT1 levels and subcellar

localization.

5.1.3 No evidence for an effect of TPT1 on foci formation and resolution after

irradiation

Zhang et al. have shown formation of nuclear TPT1 foci after IR and reported a dramatic

effect of TPT1 knockdown on retention of γH2AX foci at 3 and 6 h after 50 cGy of irradiation

in wildtype primary cells, strongly supporting a role of TPT1 in DNA repair265. Very recently, a

proteomics study using HeLa cells identified several DNA repair proteins as part of the TPT1

interactome and detected an effect of TPT1 silencing on the efficiency of HR in breast cancer

MCF7 cells267. However, immunostainings by Li et al.267 indicated that TPT1 was a

predominantly cytoplasmic protein which did not localize to the nucleus after induction of

DNA DSBs by neocarzinostatin in this study, which is not consistent with data shown by

Zhang et al.265. Furthermore, Li et al. did not detect foci formation of TPT1 but rather

cytoplasmic foci which appeared thoughout the cell and did not change upon DNA damage

in HeLa cells, which they used for identification of the TPT1 interactome. However, these

cytoplasmic foci were more prominent than the foci-like structures seen in this thesis. In

MCF7 cells, which have a high endogenous TPT1 level, TPT1 depletion lead to the prolonged

retention of H2AX and RAD51 foci 12 h after 10 Gy IR and several DNA repair proteins such

as ATR and DNA-PKcs were identified as part of the TPT1 interactome in these cells.

However, there was a large discrepancy between TPT1 binding partners identified in that

study compared to the preceding study, which also utilized cells of cervical cancer origin

(HeLa)266. Furthermore, Li et al.267 found an effect of TPT1 on RAD51 stabilization during

normal cell culture conditions, however, not after IR. These results might indicate a

differential effect of TPT1 in unirradiated and irradiated cells, as was also reported by Zhang

et al.265.

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Zhang et al observed a highly significant effect of TPT1 knockdown on retention of H2AX foci

6 h after low-dose IR with 50 cGy and also highly significant effects of TPT1 silencing on

clonogenic survival after 2 and 4 Gy. Interestingly, the pure knockdown of TPT1 even in

unirradiated condition resulted in significant impairment of survival and an enhanced basal

micronuclei level, indicating effects on DNA repair capacity265. As presented here, a

significant reduction of γH2AX levels after silencing was detected in unirradiated ADP cells,

however, numbers of γH2AX foci in silenced MCF10A cells tended to be higher in all

treatments and time-points investigated. However, none of these changes were statistically

evaluable as knockdown of TPT1 48 h prior to IR with 1 Gy did not result in significant

changes of γH2AX and 53BP1 foci numbers per positive nucleus at 1 h, 6 h, 24 h or 48 h after

IR in ADP and MCF10A cells. In agreement with these observations, there was no evidence

for formation of nuclear TPT1 foci or colocalization with γH2AX in ADP cells. For comparison,

colocalization between γH2AX and 53BP1 can be up to 100 %568 569.

Although the presented results on ADP fibroblasts and MCF10A breast epithelial cells were

largely similar, a delay in foci disappearance after TPT1 silencing in ADP compared to

MCF10A cells was detected. A possible reason for the variability could be the

immortalization status of these cells. TPT1 is a known interactor and target of TP53, which

could be affected due to the large T transformation of the ADP cells264 269 570, while MCF10A

are spontaneously immortalized cells526. Another possible explanation why TPT1 depletion

did not result in decreased γH2AX levels after IR might be that other kinases, which are

involved in DNA repair like ATR or DNA-PKcs, have increased activity due to the elevated

genomic instability of immortalized cells. This is a known side-effect of immortalization and

has been described for several cell lines, for example also breast epithelial cells571. Although

MCF10A cells were originally characterized to possess minimal genetic alterations526 572,

these could have accumulated by subsequent passaging. Especially the SV40 immortalized

skin fibroblasts ADP show increased genome destabilization due to large T, a known

phenomenon573, and elevated background level of DNA repair compared to primary cells.

Therefore, these cells might compensate the effect of TPT1 knockdown on DSB repair. A

hypothetic impairment of ATM activity by TPT1 depletion may be offset by ATR or DNA-PK,

as these kinases can also phosphorylate KAP1 on Ser824 in the course of the early DNA

damage reponse. However, the ATM kinase is believed to be dominant in this context206.

This possibility can be considered as unlikely, because ATM is known to be an important

mediator of the DDR, in particular at early time points after DNA damage562, while ATR is

believed to become important at later stages to maintain these pathways121 and is probably

not involved in early time points like 30 min after IR. Further investigations could address the

question whether the involvement of TPT1 in the DNA damage response can be explained by

ATM interaction/activation only, or if it also plays a role in ATR-mediated repair of DNA

damage.

5.1.4 No evidence for elevation of TPT1 levels in breast cancer cell lines

TPT1 is involved in tumor-reversion260 557, is upregulated in several tumors, may play a role in

the tumorigenesis and development of BC and could be an important prognostic factor for

this malignancy268. TPT1 expression levels tend to be higher in tumors, although this is not a

general observation259 and its downregulation is correlated with tumor reversion in the

majority of cases259 558. TPT1 has been described as biomarker for BC559 and correlation of

expression with clinical parameters of aggressive disease is high in several cancers including

breast and ovarian cancer263 269 560. A positive correlation of TPT1 overexpression with tumor

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size, clinical stage, lymph node metastasis and histological grade of BC is known268 and the

high TPT1 activity in some cancer types, which contributes to oncogenesis, can result from a

mutation in TP53269. Because TPT1 levels correlate with mutational inactivation of TP53 in

BCs, it is likely that mutations in TP53, and not necessarily in TPT1 itself, result in changes of

TPT1 expression in BC patients269. As TCTP is a negative transcriptional target of P53, it has

been suggested that in those tumors where P53 is primarily inactivated by mutation, altered

TCTP activity might contribute to tumorigenesis269.

In this thesis, no differences in TPT1 levels in whole cell extracts of triple negative BC cell

lines HCC1937 and HCC1395 30 min after low and high dose IR compared to breast epithelial

cells MCF10A and also in WT cells HA325, HA169 and HA256477 was detected by western

blot. Moreover, no increase of the TPT1 level was found in whole cell extracts of MCF10A

cells 30 min after 20 Gy IR (data not shown). These data might indicate the heterogeneity of

TPT1 functions in cells of different origin. As mentioned above, the high TPT1 activity in

some cancer types, which contributes to oncogenesis, can result from a mutation in TP53269.

Although HCC1937 possesses a nonsense mutation in TP53, it is located outside the central

DNA-binding core, and HCC1395 is known to have a missense mutation in TP53574, which

might not influence the effect of TP53 on TPT1. This could explain the findings that the basal

TPT1 level is not higher in those two TNBC cell lines compared to MCF10A.

Li et al. concluded that TPT1 expression might correlate with efficient HR repair267. However,

the relation between high endogenous TPT1 level in cancer tissues and cells (as also shown

for the breast cancer cell line MCF7 by Li et al.) and its protective role in DNA repair is

undefined. In this thesis, no differences between the endogenous TPT1 levels of TNBC cell

lines between HCC1937, HCC1395, HCC38 were detected compared to each other as well as

in comparison to the control MCF10A, although all three TNBC lines are deficient in BRCA1

and, by inference, HR repair. The question remains why TPT1 has been reported as highly

upregulated tumor marker by a certain number of publications if it is supposed to be a

protective factor against DNA damage. One possible explanation could be that genetically

instable tumor cells compensate for the decreased DNA repair capacity by upregulation of

TPT1. Li et al. found that TPT1 only affected stabilization of RAD51 under normal culture

conditions and not after 10 Gy IR, which might indicate differential effects of TPT1 in

unirradiated and irradiated cultures, as was also hypothesized by Zhang et al. in an earlier

work265. This group observed that downregulation of ATM in unirradiated primary cells

resulted in increased levels of TPT1 and suggested differential effects of ATM on TPT1 in

irradiated and non-irradiated samples265. In conformity with these findings, our data on

unirradiated LCLs with ATM mutations (Figure 9) also support the role of ATM on TPT1-

upregulation in unirradiated samples. Interestingly, this seems to depend on the

manifestation of the ATM mutation, as has been shown by our group477, and may be due to

a mutual cellular function of these proteins other than DNA repair.

5.1.5 The effect of TPT1 on DNA damage sensing and repair might depend on cell

type

It is well known that the level of TPT1 mRNA varies in cell type, developmental stage and in

response to extracellular stimuli258. The role of TPT1 in apoptosis and cancer development

has been recurrently described in the literature, however, its precise involvement in both

processes remains complex, as a TP53-dependent induction of TPT1 can reduce oxidative

stress, apoptosis and promote cell survival after hydrogen peroxide treatment575 on the one

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hand. On the other hand, elevated levels of TPT1 correlate with cancer development258,263.

For example, its expression can be increased dramatically during oxidative stress563, although

the findings of this thesis do not confirm an induction after IR as oxidative stressor.

Furthermore, expression of TPT1 is upregulated upon cell cycle entry but progression of such

is delayed due to TPT1 upregulation, which is an example of the complexity of TPT1

regulation576. Concerning TPT1’s function as a growth-regulating protein, diverging data has

been published263. One group proposed the stimulation of GDP/GTP exchange of Ras

homologue enriched in brain (Rheb) by TPT1 and its function in mTOR (mammalian target of

Rapamycin) signaling in Drosophila577. But other studies have reported that TPT1 does not

act as nucleotide exchange factor for Rheb in two mammalian cell lines as well as in

Drosophila cells578, nor as a regulator in mTOR signaling in mammalian cell lines579. This may

partly be due to different functions of human and Drosophila TPT1, although another

publication provides evidence that TPT1’s involvement in DNA repair is similar in Drosophila

and human cell systems265 556.

Additional evidence for a less generalized function of TPT1 is provided by different

observations of its role in cell growth and apoptosis regulation. While Gnanasekar et al.

showed that TPT1 knockdown in human prostate cancer cells causes apoptosis and inhibits

cell growth580, Zhang et al. did not find alterations of cloning efficiency in AG1522 WT cells

up to 72 h after TPT1 knockdown265. Taken together, these data suggest that the effects of

TPT1 are diverse and may depend on cell type and cellular status. To provide a cellular

system that is better comparable to the wildtype primary cells investigated by Zhang et al.,

the TPT1 knockdown and subsequent assays should be performed in primary cultures, too.

Furthermore, not only the different observations regarding nuclear translocation of TPT1

and formation/absence of nuclear TPT1 foci in primary fibroblasts265 versus cancer cell

lines267 needs to be considered. Although most action of DNA repair signaling is restricted to

the nucleus, nuclear translocation or foci formation per se is not a sufficient criterion to draw

conclusions on functions of this protein in ATM signaling and/or RS. Cytoplasmic proteins like

HERC2 are also strong regulators of the DDR. But more importantly, two pulldown

approaches identified many different potential TPT1 interactors, although the same cell lines

were used (HeLa)266,267. Therefore, not only cell-type specific but also environmental effects

need to be taken into consideration when comparing functions of TPT1 in cellular systems.

In summary, various lines of evidence have been presented in this thesis, from which one

can conclude that TPT1, an important biomarker for different cancers, may have subtle

effects on the course of DNA double strand break repair but does not considerably affect

ATM signaling.

5.2 Exome sequencing as tool to identify the genetic background of RS

Cancer is considered to be among the most complex of all human diseases581 and also

radiotherapy-induced changes in tissues during cancer treatment are of very complex nature

(see sections 2.3–2.4). In this work, 19 RS cancer patients were analyzed of which 16 had

previously been graded at least with RTOG 3 in either acute or late effects or even both. One

exception were three chemoradiosensitive patients, which are considered separately here,

because it is not known whether the observed side-effects might have solely been

attributable to the chemotherapy treatment and information on RTOG classification is not

entirely available.

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Up to 2009, already about 60 studies have been published which addressed the relationship

between sequence variations and risk of radiotoxicity, which partly lacked reproducibility

due to several reasons439. The majority of studies was performed with breast cancer

patients, followed by prostate cancer patients, and clinical endpoints (whether analyzing

early or late responses) were variable. Clearly most studies involved genes of DNA repair

pathways, followed by ROS scavenging and fibrosis/endothelial cell damage, but inability of

reproducing these data was very prevalent439.

It is known that extreme radiosensitivity can be genetically determined, as many

connections between mutations in certain genes and radiosensitivity have been observed,

the most prominent example being ataxia-telangiectasia (as summarized in subsection

2.3.5). Therefore, it was tempting to investigate whether normal tissue reactions in patients

with no known radiotoxicity syndromes can be assigned to mutations in certain genes, too.

Exome sequencing had successfully identified new Mendelian disease genes in up to 60 % of

published disease gene identification projects in the last years478. Is is especially of great

profit for identification of rare monogenic diseases with a well-phenotyped patient and

family member cohort, which allows conclusion on inheritability. However, clinical

radiosensitivity is possibly not a monogenetic disease and no material from family members

of patients was available in this study. With this approach, some candidate genes were

identified that are mutated in more than one patient, see Supplementary table S-4. Partly

not considered were mutations, which were identical in more than two patients, as they

were suggested to be false positives, given in Supplementary table S-5. Mutations, that

affected the same region of the gene, however, were chosen for validation sequencing.

Genes, that were additionally found mutated in one of the two controls, were not analyzed

further (CD44, CRIPAK, FAT1, GPRIN1, KIR3DL1, KRTAP5-5, LOC283710, LRTOMT, SCN9A).

5.2.1 Annotation by GeneCards reveals strong inter-individual variability in RS

patients

As there was no gene identified, that occurred with mutations in the majority of patients at

once, a global approach was undertaken to analyze the genetic background of the disease in

order to identify pathways, which might be enriched and possibly not visible at first glance.

Firstly, genes were annotated by using the GeneCards database (subsection 3.3.8.1), which

can be used to collect data on the biomedical information about genes, proteins, and

pathways/diseases520-522.

For assignment of the genes to a certain category, including molecular pathways or diseases,

the KEGG530 and Biocarta531-grouping was used as orientation, as both systems represent

well established bioinformatic tools for categorizing cellular processes. The category “skin diseases” was included, as acute side-effects prevalently affect the skin of the RS

patients374,517-519.

Annotation using the GeneCards database revealed strong inter-individual variability

between RS patient groups, and also between the patients within each group. Possible

reasons for these differences could be that, although patients were grouped, only the 11

breast cancer patients constitute a collection, which is potentially large enough to perform

comparisons between patients. Even though they all suffered from BC, the manifestation of

their RS (and most likely also their tumors) was different. As summarized in Table 22,

patients with RTOG grade 3 at acute, late and also both time points of side-effect occurrence

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were present within the largest group of RS BC patients. Also, the type of side-effect and

localization in the body was different, and ranged from skin fibrosis to breast edema and

lung complications. This strong variability between RS patients is a well-known problem,

which is most likely one of the reasons why so many preceding studies did not converge, as

RS itself is a heterogenous implication and also a rare event.

Table 22 Clinical data on RS BC patients showing variability of side-effect manifestation

Sample Irradiated area Side-effect in

organ/tissue

Acute tissue

reaction RTOG

grade

Late tissue

reaction RTOG

grade

HA210 Breast Skin 3 1



HA213 Thoracic wall Skin 3 Expired

HA214 Thoracic wall Skin, lung 1, 3 –, 3

HA215 Thoracic wall Skin, subcut.

tissue, lung

2, –, 3 2, 2, 2

MC1 Breast Breast edema

and fribosis

2 3

MC2 Breast Breast edema

and fribosis

1 3

MC3 Thoracic wall,

internal

mammary &

supraclav. nodes

Breast edema,

lung, skin

2, 0, 2 0, 2, 3

MC7 Breast Breast edema,

lung, skin

2, 0, 2 3, 0, 2

MC10 Breast Breast edema,

lung, skin

- 3

The pathway analyses included all 315 mutations (also from the two BC controls MC4 and

MC6) that were successfully validated through Sanger sequencing. For 22 mutations, the

validation procedure was not successful due to technical problems, for example poly-A

regions, C/G-rich regions, or highly repetitive sequences. These mutations were nevertheless

included into the final gene list, as no proof of false-positive hits by exome sequencing could

be furnished.

The categories “Cancer”, “DNA repair” and “Immune System” were of particular interest

based on the background of previous studies, as well as on the observation that RS patients

often suffer from immunological side-effects (see subsection 2.3.3). It was investigated

whether there were differences in the representation of these categories between the three

RS patient cohorts. As no significant differences between groups were observed, and all RS

patients seemed to associate somehow to these clusters, these categories were considered

priority for further investigations.

5.2.2 Mutations in Cancer and DNA repair genes correlate with individual RS

As the GeneCards annotation did not show a category or pathway that is highly represented

in RS patients, the Ingenuity Pathway Analysis was accessed. This program is equipped with a

considerable database, which was established by a large group of scientists utilizing

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published information on gene functions, canonical pathways, diseases and many more.

Furthermore, it is able to draw conclusions about signifance levels of overlap between the

analysis dataset and a reference dataset, which in this thesis was chosen to be the Ingenuity

Knowledge Base (see subsections 3.3.1 and 3.3.8.2). Also, the possibility, that categories for

GeneCards annotation might not have been chosen in the appropriate way to find out

enrichments of impaired gene functions in RS patients, was considered.

Core analyses with the three patient groups in separate analyses as well as one combined

analysis was performed and showed strong association with cancer. Furthermore, “DNA replication, recombination and repair” was one of the top networks by considering the complete RS patient gene list. Interestingly, IPA upstream analysis identified SMARCA4 as

upstream regulator of a certain number of genes in RS patients that were not previously

associated to DNA repair, however, all related to the “Carcinoma” category in IPA.

SMARCA4 itself is implicated in cancer and binds BRCA1541,542,582 and by using IPA upstream

network pathdesigner, it was proposed to regulate certain already known cancer-associated

genes such as MICB583-587, MICA

588, KCNQ3,583,589-592, MUC20

584,588,593, ZNF141592,

TNFRSF10A594,595, STIM1

596,597, TNFRSF9598

, SPHK1599, NUSAP1

583,584,592,600-602. Some of these

genes are also implicated in immune system , for example MICA603, MICB

604, STIM1605,

SPHK1606, TNFRSF9

607-610, TNFRSF10A

607. However, it needs to be stated at this point that

MICA and MICB are highly polymorphic, similar to the HLA-cluster603.

For example the genes of the TNF (tumor necrosis factor) superfamily members TNFRSF9

and TNFRSF10A are possible candidates for promotion of RS. TNFRSF9 may have a role in

activation-induced cell death611, has been described as potential clinical target for cancer

and autoimmune disease612-614 and interacts with IRAK2615, which was also found mutated in

another RS patient (HA195, squamous cell carcinoma of external ear). Furthermore,

evidence for an association between TNFRSF9 and MICA (which was found mutated in

patients MC3 and the chemoradiosensitive prostate cancer patient HA224) exists, as they

share association with TNF616-618, that can cause upregulation of MICA619. Even stronger

evidence for a role in RS exists for TNFRSF10A, as another TRAIL (TNF-Related Apoptosis

Inducing Ligand) family member TNFRSF10 has recently been identified to predict radiation-

induced acute and subacute dermatitis550. Furthermore, the two TRAIL family members are

known to interact, and TNFRSF10A has been shown to control sensitivity to TRAIL-induced

apoptosis, and also its interaction with TP53 is published620. It has been identified in the RS

BC patient HA213 in the course of this project. TNFRSF10A as well as TNFRSF9 should be

considered in further functional studies, although they do not belong to the DNA damage

response group of proteins to current knowledge. Furthermore, all of these genes were

identified as part of the “Skin lesion”, and partially overlapping “Death of epithelial cells”

implication by IPA: SMARCA4591 621-623, MUC20584, TNFRSF10A624,595 TNFRSF9625, KCNQ3591,

NUSAP1584, STIM1626 MICB584,586, MICA627 SPHK1 via SMARCA4621,591, ZNF141 via ER628). The

hypothesis, that – at least some – causes of acute reactions could be (partially) due to

defective wound healing for instance. However, it needs to be remembered that not all

adverse effects focus on skin reactions, as some patients also suffer from inflictions of lungs

or hormone system (subsection 2.3.3 and Supplementary table S-1).

The above described genes might all play a role in one pathway, which is regulated by

SMARCA4 that could itself be related to RS. If this hypothesis is true, then it would not be

surprising that findings in individual RS patients are so different from each other. Each

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patient could show impairment in only one of the steps, which might be different in each

individual patient but results in comparable RS. It would be interesting to investigate

SMARCA4 itself, but also its targets, with regard to the type and time point of manifestation

of side-effects.

As “Cancer” was identified to be highly associated with radiosensitivity patients, and an

association between DNA repair as well as cancer with RS is known, “Cancer”, Immune

System” and “DNA repair” furthermore seemed interesting candidates for RS

biomarkers/prediction. In order to test whether cancer is a feature of RS or possibly

introduces bias into the RS dataset due to redundancy, comparative analyses with BC

patients without RS were performed.

5.2.3 Association of cancer and DNA damage response genes in RS patients by IPA

The IPA analysis revealed strong association of the “Cancer” category within the “Diseases

and Disorders” section in all three BC groups. Strikingly, the category “Hereditary Disorder”, which is mainly attributed to genes of breast cancer susceptibility like BRCA2 and NBN (p-

value of overlap calculated by Fisher’s Exact Test in IPA: 2.65E-04) in Fam BC patients, was

only identified as subgroup in these familial patients and not in RS or non-familial BC

patients. However, the “Hereditary Disorder” category also came up in RS patients with

other cancers (hypopharynx, squamous epithelium carcinoma of left tonsil, keratinizing

squamous cell carcinoma of the base of the tongue, squamous cell carcinoma of external

ear, rectum carcinoma), involving genes attributed to hereditary prostate cancer such as

EHBP1 and MSR1 (p-value of overlap calculated by Fisher’s Exact Test in IPA: 4.42E-04).

MSR1 is additionally known to relate to esophageal adenocarcinoma/Barretts Syndrome629.

From these findings one can conclude that IPA is able to identify the genetic predisposition

underlying certain diseases and also estimate the strength of this association, as it is well

known that BRCA2 and NBN strongly account for Fam BC (subsection 2.2.1). As it utilizes

published data that has been manually attributed to certain pathways or diseases, IPA can

only identify connections between genes with known functions and/or pathway annotations.

As RS is not known as a “disease” or “disorder” so far, and is also not attributed to a defined pathway to current knowledge, IPA is not able to draw such conclusions per se. As

GeneCards and IPA both rely to a great extent on pubmed entries, it is not surprising that

both tools identified enrichments in DNA repair genes but it is noteworthy that such

mutations accumulated in the RS BC group in comparison to the BC group.

However, not all RS patients have shown mutations in genes related to DNA repair. Exome

sequencing of breast cancer patients HA214 and HA215 did not reveal mutations in DNA

repair genes, which could be due to the following reasons. Firstly, although being a very

sophisticated method, some alterations in exons might be missed by the technique due to

reduced coverage in regions with low or high GC content. However, Illumina platforms (one

of which was applied here) have been shown to perform comparatively well630. Another

possible reason for missing variants could be mistakes in the reference genome, to which the

exome sequencing results are aligned. It has already been suggested almost ten years ago,

that rare or erroneous alleles may have been incorporated into the NCBI human genome

sequence631, but the human reference sequence has been continuously improved since

then632, and an increasing number of common SNPs is consecutively identified. It needs to

be further considered that exome sequencing only covers variations in coding regions of the

genome which constitute only ~5 % of the entire genetic material. Regulatory regions or loci

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without known function could exert an effect on radiotoxicity reactions, but are missed by

the exome sequencing approach and would only be covered by time consuming and cost-

intensive whole genome sequencing.

Additionally, exome data from the two control groups (BC and Fam BC) was not subjected to

validation sequencing to the same extent as RS data, as data was retrieved from other

ongoing projects in our lab. It might therefore still include a higher number of false-positives

compared to respective RS data. However, this obviously did not dilute the observed

enrichment of DNA repair gene mutations in the RS BC group and therefore might be

unlikely to mask other associations.

Occurrence of mutations solely in DNA repair genes has not been shown as prerequisite for

RS, also not in this study. Therefore, it is plausible, that mutations in genes associated

primarily with cancer or immune system (or also other functions) could account for RS in the

patients HA214 and HA215. HA214 revealed a truncating mutation in the cancer-associated

genes DNMT3A (DNA (Cytosine-5-)-Methyltransferase 3 Alpha)633 and CDKL2 (Cyclin-

Dependent Kinase-Like 2 (CDC2-Related Kinase))634. The latter was in addition identified in

HA173 and HA225, with the identical variant rs56229013, which could indicate a common

SNP. Furthermore, the immune system-related genes KIR3DL1 (killer cell immunoglobulin-

like receptor, three domains, long cytoplasmic tail, 1)635 and the apoptosis-associated gene

MAPK10 (mitogen-activated protein kinase 10)636 that is also associated with sensitivity to

chemotherapy637 were identified in patient HA214. Cell death pathways have been

connected to RS before (see section 2.3, precisely subsections 2.3.3 and 2.3.6) and recent

findings support this theory638. Interestingly, also a variety of cell cycle-associated genes

such as AURKC (Aurora Kinase C)639, or CRNKL1 (Crooked Neck Pre-MRNA Intronic

Factor 1)640, were identified which could potentially relate to RS641. Furthermore, the skin-

disease-related gene PSORS1C1 (Psoriasis Susceptibility 1 Candidate 1)642 was identified in

this patient. Therefore, there is evidence for a number of possible candidates that might

cause the RS reactions in patient HA214. It is furthermore conceivable that although

mutations in DNA repair genes are present in certain RS patients, additional mutations in

other functional categories like cancer, immune system, cell cycle, apoptosis or skin diseases

additionally support development of adverse effects.

In contrast to that, patient HA215 only showed a fraction of mutations in the categories

described above as solely NLRC3 (NLR Family, CARD Domain Containing 3), which is involved

in immunological processes643 and the cancer-related STIM1 (Stromal Interaction

Molecule 1)596,597 gene were identified. STIM1, however, might be part of a pathway

addressed by SMARCA4, which could itself play a role in RS apart from engagement in the

DNA damage response (see subsection 5.2.1).

5.2.4 Cancer and DNA damage response genes associate to clinical RS and not

solely to cancer malady

The GeneCards annotation of truncating mutations in genes identified by exome sequencing

in all three RS groups showed a high number of DNA repair genes in the RS group and by

comparison with RS BC patients, BC patients without RS seemed to encompass less

mutations in DNA repair genes. Interestingly, this difference was only significant by

comparison of RS BC with BC patients, not with Fam BC patients. Fam BC is characterized by

a strong genetic predisposition for the disease and a certain number of breast cancer

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susceptibility genes has already been characterized (see subsection 2.2.1). A possible

association between RS and Fam BC is not known, and some Fam BC genes have already

been investigated in the RS context. For example BRCA2, of which a truncating mutation was

identified in one patient of our Fam BC group with no known RS background. This gene has

been described as likely not relevant in the radiotoxicity context by several previous

studies644-648. In contrast to that, Foray et al. found that heterozygous BRCA1 and BRCA2

mutations caused enhanced cellular radiosensitivity with an impaired proliferative capacity

after irradiation317. Similarly, the heterozygosity for NBN mutation c.657del5 in one of the

FamBC patients has been associated with increased chromosomal radiosensitivity in a

blinded study649 although the heterozygotes are not known to exhibit clinical

radiosensitivity, by contrast with homozygous NBS patients.

However, little evidence of connections between RS and familial cancer does not imply that

underlying pathways, which might be responsible for RS as well as Fam BC, could share some

components. One candidate pathway would be the FA pathway of crosslink-repair proteins

that accounts for hereditary cancer susceptibility, which has already been known for more

than a decade650. Especially FANCO/RAD51C, which has been identified as mutated in the

patient MC3 by exome sequencing with likely functional consequences (Supplementary

figure S-25), has already been linked to breast and ovarian cancer susceptibility (subsection

1.4.1). It is likely responsible for the additional development of ovarian cancer in the MC3

patient as secondary malignancy. The FANCL variant, which was identified in patient MC7,

however, was not associated with BC susceptibility in another project of our group551 and is

predicted to cause an alternative carboxy-terminus rather than actually truncating the

protein (Supplementary figure S-24). For association investigations between mutated genes

in the MC7 patient with its clinical and cellular RS, the ABL1 mutation should be considered,

which has been predicted to have a strong effect on the size of the protein and was also

shown to result in visibly reduced ABL1 levels in TERT-immortalized cells of this patient,

Supplementary figure S-24.

In contrast to GeneCards and IPA, the Reactome browser tool could only relate a small

number of genes to DNA repair and cancer in all categories. It missed some clearly DNA

damage-associated genes like ANKLE1651, EXO5 (subsection 1.1.1.1) HELB (subsection 1.1.2),

NEK4 (section 1.1.2), NPAT (section 1.3), RBBP6 (section 1.2) and RINT1 (subsection 1.3.2).

As this results in covering only approximately 65 % of the genes found by GeneCards in this

category, it is plausible that no statistically significant differences could be detected. On the

contrary, Reactome identified a large number of genes related to the immune system

category. This number was comparable to the other two tools (GeneCards= 47, IPA= 43,

Reactome= 35), but no significant differences between the three groups were found,

consistent with GeneCards and IPA analyses. From these findings, one could conclude that

Reactome is probably not suitable for addressing the DDR pathway or cancer-related genes,

but is well suitable for annotation of immunological genes. This is surprising, however, as

Reactome is known to be capable of discovering unexpected functional relationships

regarding somatic mutation catalogues from tumor cells492. However, the focus seems to lie

more on DNA replication and not on DNA repair, and superpathways such as “signaling” and

“immune function” could be given priority. Nevertheless, at this point, it needs to be

emphasized that 33 patients in total constitute three comparatively small groups, rendering

it difficult to draw conclusions in concern of statistical power. Furthermore, the comparison

groups included primarily selected cancer patients with unusual course and aspects of their

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At first glance, it is difficult to draw any conclusions whether genes found in RS patients and

non RS patients participate solely in exclusive pathways. “ATM signaling”, “Repair of DNA” and “DNA damage response of cells” are not the only repair pathways identified by IPA.

“Mismatch repair” and “Hereditary BC signaling” strongly relate to BC or Fam BC patients,

respectively. For BC patients, MSH6 is clearly associated with mismatch repair, whereas

FIGNL1 (as its name as RAD51-binding protein already suggests), is involved in HR (section

1.1.2). Both genes were classified to the “Repair of DNA” category by IPA, together with the two FA-related genes RAD51C and FANCL in RS BC patients, which are involved in ICL repair

and HR (section 1.4). ABL1, however, (besides FANCL) was additionally classified as belonging

to the “DNA damage response of cells” pathway by IPA, which seems to include more central

and superior DNA repair mechanisms. However, it is difficult to judge which indications were

followed by IPA professionals, who established these two categories, as only high-level

categories (in this case “DNA Replication, Recombination and Repair”) are described in more

detail535. Furthermore – like most classifications performed by humans – also these

definitions of and assignments to functional classes are of subjective nature. Similarly, the

choice of categories for GeneCards annotation was, albeit orientated on KEGG and Biocarta

pathways, personal choice.

Genes (or gene products) that met requirements for classification in the sub-pathway “DNA damage response of cells” (as will be indicated by response) are classified according to the

following references (overview given in Supplementary table S-10). NBN and ABL1 were

potentially chosen as part of “DNA damage response of cells” as they were found to be “linked to the cellular DNA damage response”653 and the “apoptotic response to DNA

damage”654, respectively. FANCL was likely assigned to the “DNA damage response of cells” as it belongs to the FA-proteins that “fall into a common pathway that is activated in response to DNA damage”655,656. HELB “accumulates on chromatin in response to genotoxic

stress”89,657 and “HERC2 is a DNA damage-dependent target modified in response to

DSBs”185,658. NEK4 was likely classified as part of the DNA damage response as it “regulates entry into replicative senescence and the response to DNA damage in human fibroblasts”72.

RBBP6 is associated with MCM10106, which is “suggested to function in DNA repair in

association with TOPBP1”106 that is moreover “associated with DNA replication, checkpoint

response and homologous recombination”659. NBN, ABL1 and FANCL were additionally found

in the category “Repair of DNA” (which is indicated by repair). “Human NBN is involved in

double-stranded DNA break repair of DNA”653, is "necessary for non-homologous end joining

double-stranded DNA break repair of deoxyribonucleic acid"660 and was described as being

"necessary for repair of DNA"661. Furthermore, previous findings indicated that "mutant NBN

protein decreases double-stranded DNA break repair"662. ABL1 is involved in mismatch

repair as “cells are unable to carry out mismatch repair in which the nuclear enzyme c-Abl

tyrosine kinase is not activated”215, FANCL is involved in repair of DNA as "the Fanconi

anemia pathway is required for the efficient repair of damaged DNA"655 and RAD51C is

involved in repair of DNA as “human RAD51C participates in branch migration and Holliday

junction resolution and thus is important for processing HR intermediates late in the DNA

repair process”663. TDG was likely characterized as part of the “repair of DNA” subpathway

as it “excises T from G-T mispairs and is thought to initiate base excision repair664, is a “repair

enzyme”665 and belongs to a “family of enzymes that use a base-flipping mechanism to

locate damaged bases in dsDNA and initiate base replacement through the DNA base-

excision repair pathway37 666 667.

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BRCA2 is a well known DNA repair gene, supported by the findings that “reduced ligation

during DNA base excision repair was supported by BRCA2 mutant cells”668, that “DNA repair

defects in BRCA2-deficient cells”669 occur, that “a lack of functional BRCA1 and BRCA2 led to

defective repair of DNA double-strand breaks317, and that “BRCA2 plays a role in replication-

coupled DNA interstrand crosslink repair”670.

NEIL1, which was identified in both RS BC and Fam BC patients was classified by IPA as

belonging to the “repair of DNA” subpathway according to the following evidence: “NEIL1 protein initiates oxidized DNA base excision repair”671, “Cockayne syndrome group B protein stimulates repair of formamidopyrimidines by NEIL1 DNA glycosylase”672, “NEIL1 Is Required for Forming BERosome Repair Complex“673 and “the human Werner syndrome protein

stimulates repair of oxidative DNA base damage by the DNA glycosylase NEIL1”674.

Interestingly, Greve et al.449 have previously identified asscociations of HIST1H4H and

FAM186B with RS, whereas the related genes HIST1H4B and FAM186A were found in Fam

BC and BC patients in the course of this thesis. Therefore, it needs to be stressed that apart

from NEIL1, which was identified in RS and non RS patients in parallel, a certain amount of

genes might be connected with cancer as well as RS manifestation.

DNA repair genes from the BC patients included FIGNL1, which “is required for efficient homologous recombination repair”76 and the mismatch repair gene MSH6, which “regulates human mismatch repair”675, forms “specific mispair-binding complexes”676, and is “the major mismatch recognition factor”677. Furthermore, ”loss of MSH6 is associated with an icrease in

frameshift mutagenesis”678 and “MSH3 and MSH6 are partially redundant for mismatch

repair”679.

The “response” to DNA damage as classified by IPA could also possibly include checkpoint

control or cell death signaling apart from DNA repair. However, this is not further specified

by IPA (personal communication with Dr. Jasmin Droege, Senior Scientist, Advanced

Genomics Support). Merging the findings in the subcategory with identified diseases and

disorders revealed that – apart from the well known role of ABL1 in cell death (see section

1.3) – also prominent roles of RAD51C680, FANCL681, RBBP6682 and NEK4683 in cell death

mechanisms were found. However, IPA also identified functions for BRCA2684-687 in cell

death, which was not attributed to the “DNA damage response of cells” subpathway. Thus,

these findings render it unlikely that cell death function alone as additional feature qualifies

for assignment of genes into this category.

Furthermore, especially the results in the DNA repair subcategory need to be interpreted

with caution, as filtering the genes for DNA repair according to GeneCards annotation

introduces bias to the dataset, because the focus is on certain characteristics. The number of

molecules that are submitted to an analysis (i. e. the analysis-ready molecules) will influence

the p-value of overlap. In this case, IPA recommends using the original dataset as reference

data (personal communication with Dr. Jasmin Droege, Senior Scientist, Advanced Genomics

Support). However, these analyses most likely failed due to the limited number of total

molecules in the exome sequencing results. Also, it should be considered, that the Ingenuity

Knowledge Base expands and changes continuously, as new findings get published and

previous findings might have been corrected or revised. Therefore, it would be reasonable to

perform the analysis again before deciding on focus molecules for further studies.

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Interestingly, linear regression of numbers of genes in each subpathway with according p-

values showed that – although the two parameters correlate well – also the strength of

association and not only bare number of involved genes seems to influence the p-value. An

equal number of genes was identified in “cancer of cells” as well as “repair of DNA” for Fam BC and BC patients and Fam BC and RS BC patients, respectively. In both cases, the Fam BC

group showed the stronger association with p-values of overlap, indicating that it

encompasses genes, that have a larger impact on these functions. Still, RS BC could be

interpreted as possessing the strongest relationship to DNA repair, as the additional and

exclusive category “DNA damage response of cells” shows prominent results in both number of genes and p-value. The resulting behaviour, namely the proportionality to the number of

genes, is expected, and indicates that the applied analysis has been performed in a

reasonable way by considering both quality and quantity findings.

Moreover, repair of DNA naturally also occurs as response to damage, so other than

qualifying the actual mode of action of the proteins in either “responding” to DNA damage or “repairing” it, it is probably more appropriate to refer to the frequency of occurrence of

mutations in DNA repair genes, meaning the quantity. Considerably, the cell is likely to be

more vulnerable to damage if mutations in DNA repair genes occur in more than one gene,

which is for example the case for MC3 and MC7 patients, as will be discussed in the

following section.

As this thesis originally focused on the approach to identify biomarkers of RS, these could be

of functional nature and not necessarily related to single variants easily identified through

PCR amplification of the respective amplicons in DNA extracted from blood lymphocytes

prior to radiation treatment. Also, biomarkers correlating to cellular RS were – and still are –

of great interest, as they relate to the actual functional background of the adverse effects

and could cover more than one potentially lethal variant impact. Therefore, ATM signaling

and cellular colony formation was investigated in immortalized cellular models of RS BC

patient fibroblasts MC1, MC3 and MC7.

5.3 Functional studies in cells from radiosensitive patients

Cells of patients MC1, MC3 and MC7 were immortalized with TERT, in order to firstly address

ex vivo radiosensitivity reactions in the context of cellular RS assays and secondly, investigate

possible associations between mutated genes and their translation to functional impact. By

this procedure, permanent fibroblast cell lines were successfully generated for functional

studies, and MC3 and MC7 retained their TERT expression over time. Although they had

initially taken up and showed immunoreactivity of TERT, MC1 cells had lost TERT again

during subsequent passaging. Their hygromycin B resistance, however, was still given, as

cells grew well under continuous selection pressure. These cells might have silenced the

TERT gene while still maintaining expression of the hygromycin B resistance gene.

Otherwise, they would not have been capable of withstanding the selection.

A possible explanation for the silencing could be a spontaneous immortalization of these

cells independent of TERT, which can occur in cells that are subjected to extended passaging,

and is a rare – but still well documented – event688. Obviously, spontaneous immortalization

can also induce TERT expression689, but this is not the only possible underlying mechanism

and the molecular implications are not entirely understood. In contrast to immortalization

with viral oncogenes (SV40 large T, and in this work also EBV), spontaneously immortalized

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cells often retain normal checkpoint behaviour and a diploid karyotype689. In order to initiate

immortalization, the M1 (mortality stage 1: senescence) and M2 (mortality stage 2: crisis)

cell cycle checkpoint gates need to be abrogated689,690. M1 can be circumvented by the SV40

large T antigen (which applies to the ADP cells) that targets the p53 DNA damage pathway

and is bypassed by viral oncogenes. For completion of immortalization, however, also the

second gate M2 must be skipped. This enables to avoid crisis, which normally causes

shortening of telomeres until initiation of cell death689.

RAD51 foci counting in primary and in TERT immortalized fibroblasts of the same patients

revealed prominent differences in the background levels of RAD51 foci (subsection 4.4.3.).

Moreover, these levels tended to be higher in all immortalized cells including the SV40

immortalized ADPs and the TERT immortalized control BJ5TA. These findings may indicate a

considerable influence of both immortalization procedures on DNA damage repair pathways,

which occurs independent of irradiation. These results need to be considered when

extrapolating/tracing back effects in immortalized cells to their biological origins and stress

that a direct side-by-side comparison of primary and immortalized cells is not always

possible. Therefore, these findings might be important when considering immortalized cells

rather than primary cells for functional radiobiology assays.

Regarding the history of characterization of cellular RS, many published findings indicate that

EBV (also a viral oncogene) immortalization of lymphocytes of patients might introduce bias

into experimental results due to their increase of genomic instability (section 2.4). Although

some studies stressed the great potential of patient-derived LCLs as cellular RS tools,

cumulating evidence suggests that primary fibroblasts of those patients should be prioritized

(section 2.4). Previous studies in lymphocytes, LCLs and also primary fibroblasts of some of

the patients analyzed in this work, have addressed chromosomal RS by means of

acentric/dicentric fragments and reciprocal translocations and also colony surival and

received reasonable correlations between clinical RS, chromosomal RS and cellular RS,

however, differences between patients were also prominent460 507.

Interestingly, not only RS BC patients, but also some fibroblasts derived from healthy

individuals showed elevated cellular RS425,507. Assuming clinical RS correlates with cellular RS

(which was not always the case in the literature), this indicates that RS reactions might also

affect humans without known cancer malady. In these assays, the known clinical RS

correlated well with cellular RS. Therefore, it should be taken into consideration that healthy

individuals might also carry mutations which predispose to RS independent of cancer. In

future studies, these healthy individuals should also be further analyzed by exome

sequencing to investigate, whether they share some of the mutations of RS patients which

have not (yet) been assigned to the cancer phenotype, which could include skin reactions for

instance.

5.3.1 Early ATM signaling is functional in TERT immortalized fibroblasts of RS BC

patients

As well described in the literature, ATM signaling can be predictive of clinical as well as

cellular RS to a great extent (see section 2.4). Therefore, in this thesis the hypothesis was

followed that clinical RS may be correlated to dysfunction of ATM signaling in RS patients

(Figure 11).

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Addressing the two well-established DNA damage markers and ATM targets CHEK2 and KAP1

is a sophisticated technique to investigate the specific phosphorylation ability of ATM in cells

with a mutational background in DNA DSB repair. Phosphorylated forms of the two proteins

could be easily detected in all three cultures at a level similar to the control, however, subtle

differences were observed regarding cells from patients MC1 and MC7 (subsection 4.4.1).

MC7 TERT showed a significant elevation of p-CHEK2 levels between 0 Gy and 1.5 Gy,

indicating rapid signaling between ATM and CHEK2 already after lower IR doses in these

cells. MC1 TERT showed a comparatively lower immunoreactivity of p-CHEK2 at 6 Gy, which

was borderline significant compared to BJ5TA and might indicate a slight delay in

phosphorylation activity of ATM at high IR doses. Interestingly, significantly lower

immunoreactivity of p-KAP1 after 1.5 Gy compared to BJ5TA was observed in MC7 TERT

cells, while it was considerably higher in MC1 TERT compared to MC7 TERT. These findings

might indicate differential effects of ATM on the two target proteins in RS cells. MC1 cells

carry a truncating mutation in HERC2, which is normally targeted by ATM upon DNA

damage691,692. Protein formation and most likely also function is predicted to be completely

abrogated regarding one of the two alleles in these cells. This might have a prominent effect

on repair capacity in the context of coordinating the ubiquitin-dependent assembly of DNA

repair factors at lesions693. Interestingly, KAP1 phosphorylation is comparatively strong after

1.5 Gy, whereas CHEK2-phosphorylation after 6 Gy is diminished. Interaction partners of

HERC2 are currently poorly defined and therefore, these effects are difficult to explain.

However, binding between HERC2 and MDC1 (mediator of DNA damage checkpoint protein

1) has been described694, and MDC1 is known to interact with CHEK2695. Therefore, an

influence of reduced HERC2 activity could lead to a secondary inhibitory effect on CHEK2 –

and therefore possibly also on – p-CHEK2 levels.

In the patient MC7, truncating or splice site mutations in ABL1 (which was shown to reduce

protein levels by approximately 50 %), NPAT and FANCL were detected. However, both the

NPAT and FANCL variants were predicted to be likely silent or leaky and might confer only

subtle effects regarding protein functions. ABL1 is a central component of the DNA damage

response (see subsection 1.3.2). The differential effects of ATM on CHEK2 (resulting in

elevated levels), and on KAP1 (resulting in lower levels) after IR with 1.5 Gy could result from

potential interactions of these proteins, which are currently not known. ABL1 is an important

kinase in the DDR and targets plenty of downstream molecules, similarly to ATM and CHEK2.

ATM205,206,527,528 and CHEK2696,697 both are known to phosphorylate KAP1 on specific serine

residues. ABL1 could share this target, which would be phosphorylated to a lower extent if

ABL1 levels are depleted. However, this would insist that ABL1 also specifically

phosphorylates KAP1 at Ser824, which is unlikely, as it is a known target of ATM528. The

ATM-CHEK2 signaling possibily compensates this effect, which would result in

simultaneously higher CHEK2-levels. However, it needs to be emphazised at this point that

these changes are poorly significant and also were not detected at 6 Gy with the given

antibodies. Therefore, these results need to be confirmed in extended follow-up

experiments to clarify an effect of HERC2 and ABL1 mutations on ATM-dependent

phosphorylation of KAP1 and CHEK2.

https://reports.ingenuity.com/rs/nodeview/nodeview.jsp?analysisid=-1&nodeName=ING:3ui3

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5.3.2 Repair up to 48 h after IR is efficient in TERT immortalized fibroblasts of RS

BC patients

The assessment of DNA DSB repair foci kinetics is one of the most widely used assays to

determine functionality of the DNA damage response and also radiosensitivity reactions. The

clinical application of ionizing radiation both affects diagnostic as well as curative exposure.

The radiation dose during, for example mammography or diagnostic CT (computed

tomography), is considerably lower compared to RT (radiotherapy), however, it still affects

chromosomal RS. A previous study in our lab addressing foci kinetics after IR revealed that

especially repeated CT scans correlate with elevated levels of γH2AX and 53BP1 foci in cells

of different origin326. This memory effect was especially pronounced in the TNBC cell lines

HCC1937 and HCC1395, which are known to possess mutations in BRCA1 and TP53; and

BRCA1, CDKN2A, PTEN (Phosphatase and tensin homolog), TP53487 488 and NBN

419,

respectively. Interestingly, cells mutated in BRCA1 (HCC1937) and ATM (HA56) showed

stronger elevation of foci levels 30 min after IR compared to HCC1395. The latter cell line,

however, displayed persistence of elevated foci numbers after longer time periods,

indicating a cumulative effect of mutations in DNA repair genes exceeding early time points

of repair. These results already showed differential effects of IR on chromosomal/cellular RS

responses in radiosensitive breast cancer cell lines and furthermore emphazised that

individual RS might not only apply to conventional radiotherapy, but should also be

considered in the context of low-IR diagnostic procedures.

As formation and resolution of repair foci has been repeatedly applied for characterization

of RS (subsection 2.4 and determination of RS in TNBC326) and early ATM signaling 30 min

after IR revealed only subtle differences between RS cells and the control, numbers of γH2AX

and 53BP1 foci were counted at timepoints extending to 48 h after IR. Although foci

formation and resolution was significant in all tested cell lines, subtle differences between

the RS cultures were monitored (subsection 4.4.2). Interestingly, MC3 TERT and MC7 TERT

cells showed evidence for similar patterns of repair, peaking at 1 h and completion at 24 h,

which is the usual course of these events449. Foci numbers in these two cultures returned

even faster to the zero level after 24 h than the control BJ5TA, though this difference was

not significant. By comparison, MC1 TERT cells showed extended detection of foci after

repair is usually completed, resulting in a non significant drop from 6 h to 24 h. Only in these

cells, a delay in foci resolution could be observed, which results in significant decline of foci

numbers between 24 and 48 h after radiation exposure. This delay may be attributed to the

HERC2 mutation in these cells, as H2AX is known to be the main target of this ligase692. By

interaction with the E3 ubiquitin ligase RNF8 (Ring Finger Protein 8), it coordinates the

ubiquitin-dependent assembly of DNA repair factors on the damaged sites693. As it

furthermore regulates the retention of repair proteins at these sites, it is plausible that a

reduced action of HERC2 in MC1 cells is the cause for the delay in γH2AX foci resolution.

Furthermore, also 53BP1 resolution is likely affected, as 53BP1 is attracted by ubiquitylated

histones691. Moreover, the HERC2-MDC1 interaction694, which could be impaired in the

patient MC1, might execute a secondary effect on the function of MDC1 as platform for

recruitment of other DDR proteins and as a cornerstone for phosphorylation and

ubiquitylation crosstalk in DNA repair694. The direct binding of MDC1 to γH2AX698 and

support of its signal amplification ensures maintainance of damage signaling166 in order to

recruit and retain mediator proteins like 53BP1 at IR-induced foci, which could be impaired

by HERC2 disability. Comparative IPA analyses furthermore did not identify a strong

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association of genes from RS BC patients with “formation of nuclear foci” (subsection 4.2.3.2), which supports the findings in our TERT immortalized RS BC cells.

5.3.3 Mutational background of MC3 and MC7 correlates with RAD51 foci

formation defects

Some of the classical features of FA are missing in patients with FANCO, FANCR and FANCS

mutations, which accounts for the designation of these genes as FA-like genes. As FA genes

play a crucial role in repair of ICLs, disability could assault genomic integrity through DNA

breakage and chromosomal rearrangements (section 1.4). As patients MC3 and MC7 both

showed mutations in FA/FA-like genes, RAD51/FANCR foci formation was investigated in

MC3 (RAD51C/FANCO mutation) and MC7 (FANCL mutation, also ABL1 mutation) primary

cells in a previous side-project507 prior to immortalization of these cells. The studies on

primary cells indicated a significant impairment of RAD51 foci formation in MC3 cells

compared to ADP as control. RAD51 foci formation in MC7 was also reduced, but not

significantly. To check whether the TERT immortalization could influence DNA repair capacity

of these cultures, this experiment was repeated with the immortalized cell lines. As MC1 had

shown significant impairment in γH2AX and 53BP1 foci resolution after IR, it was included in

the experiment. BJ5TA was used as TERT-immortalized control.

Interestingly, results in primary cells could not be inferred to the respective immortalized

cultures. Whereas only the primary MC3 exhibited poor increase in foci-positive cells after

IR, none of the RS TERT cells showed a significant increment in foci-positive cells after IR

either. The failure of MC3 and MC7 (TERT) cells to form RAD51 foci after IR could be related

to their respective mutations in RAD51C and FANCL or ABL1. ATM kinase function appeared

normal in these cells (also TP53-phosphorylation in MC3147 507 699), consistent with the roles

of RAD51C, FANCL and ABL1 in homologous recombination repair downstream of ATM.

Although RAD51C has been reported to be involved in the crucial step of checkpoint

activation by mediating the phosphorylation of CHEK2 by ATM700, no significant changes in

p-CHEK2 levels were observed in MC3 TERT cells (subsection 4.4.1). Either RAD51C does not

interact with ATM signaling in these cells, or the haploinsufficiency can be compensated for.

It has been reported that RAD51C localizes to the sites of DNA damage before and

independent of RAD51, supporting a role of RAD51C in the early stages of homologous

recombination repair700.

FANCL might exert less influence on IR-induced RAD51 foci as it, firstly, is not confirmed to

impact protein function222 in patient MC7. Secondly, it is a protein of the FA core complex at

the edge of crosslink repair upstream of HR and thus may execute less influence on ionizing

radiation sensitivity. ABL1 on the contrary is phosphorylated by ATM (subsection 1.3.2) and

known to phosphorylate RAD51137 218 besides ATM after IR. Thus, it likely promotes

activation of the RAD51 complex and inhibits the DNA strand exchange activity of the RAD51

recombinase (subsection 1.3.2), supporting the implication of ABL1 in the RS context581.

Interestingly, severe radiosensitivity of this FANCO mutation carrier was previously

confirmed by both chromosomal and cellular radiosensitivity assays507. Lymphocytes of this

patient showed an increased number of extra acentric fragments as well as dicentric

chromosomes, which indicates defective DNA DSB repair425.

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On the contrary, lymphocytes from the patient MC7 have shown normal levels of dicentric

chromosomes and extra acentric fragments per cell, but colony survival has not previously

been investigated with primary MC7 cells. In addition, RAD51C dysfunction induces the

formation of centrosome aberrations700, an important cause of chromosomal instability,

which might lead to the high yield of chromosomal aberrations in MC3 primary lymphocytes.

It needs to be emphasized that results of RAD51 foci formation, although they were different

in primary compared to immortalized cells, indicate impaired RAD51 foci formation in both

patients. Influence of FA-proteins on RAD51 foci formation has initially been described for

FANCD1/BRCA2-deficient cells650. These findings have been extended to FANCO-deficiency

as FA-like disorder, as deletion of RAD51C correlated with RAD51 foci formation

impairment701,76,702,703.

Therefore, results in MC3 primary cells are consistent with the literature. It would be

interesting to include BRCA2-deficient cells into the analysis and check whether the effects

are similar to further characterize the RS in the MC3 patient.

MC1 TERT cells showed a strong elevation of RAD51 foci positive cells after IR and

comparably low basal RAD51 levels. This could be due to the following reasons. Firstly, MC1

cells are known to be mutated in the ubiquitin ligase HERC2, which coordinates the

ubiquitin-dependent assembly of DNA repair factors by interplay with the E3 ubiquitin ligase

RNF8693. RNF8 is known to enhance polymerization of RAD51 at IR-induced DSB sites and

showed correlation between cellular survival and RAD51 foci development at DSB sites704. As

a direct influence of HERC2 on RAD51 foci formation is currently not known, it is possible

that RNF8 is still capable of signal transduction leading to RAD51 foci formation without

prior interaction with HERC2. Importantly, HERC2 targets BRCA1 for degradation705 and loss

of HERC2 has been associated with higher DNA repair capacity706, perhaps explaining the

better RAD51 damage response in MC1. Secondly, MC1 TERT cells showed loss of TERT

immunoreactivity after extended culture, although it was confirmed to have been

introduced into these cells during immortalization. Therefore, in this point, it should be

considered that MC1 TERT cells have undergone spontaneous immortalization (section 5.3).

This could account for the low basal RAD51 level of these cells in comparison to the other

immortalized cultures.

Further experiments are required to directly compare the effect of the immortalization

protocols as one would need to transform the same primary cells for a side-by-side

comparison. Additionally, the evaluation of RAD51 foci is difficult, as the RAD51 antibody

additionally stains the cytoplasmic forms of RAD51 other than the restricted staining of

chromatin bound γH2AX and 53BP1. A preextraction according to the TPT1 protocol could be

reasonable (subsection 3.2.9). Moreover, countings in primary and immortalized cells would

need to be assessed in parallel by the same observer, as judgement of foci formation can be

subjective. As primary cell material is always limited, this might be difficult to realize in a

number of experiments which would meet criteria for extended statistical analysis.

Alternatively, ADP cells, which are the only readily available cells used in the first

experiment, should also be included in experiments with TERT cells, to provide the possibility

of investigation of possible variations between counting techniques. A possible effect of the

immortalization on the basic level of especially MC3 cells could be the strong impact of

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introduction of additional threat by TERT, which might have added on to the high genomic

instability in primary cells of these patients.

Both γH2AX and RAD51 foci are two key markers of DNA damage signaling and HR repair

processes, however, addressing some different substrates and partially functional

redundancy of the two pathways is known. As ATM signaling appeared comparatively

normal in all RS BC TERT cells up to 48 h after IR, it was tempting to investigate whether RS-

related effects might manifest at later time points following repair signaling. Therefore,

colony survival as the gold standard of radiooncology assays508 was established for the three

cultures in comparison to the wildtype cells BJ5TA. As the mutation in ABL1 could lead to

apoptosis induction in MC7 cells (subsection 1.3.2), this cellular RS endpoint might be

especially interesting to draw the connection to clinical RS of this patient.

5.3.4 Cellular RS is associated with clinical RS according to colony survival

Chromosomal radiosensitivity has been evaluated as a method to predict radiation side-

effects707, however, previous studies conducted with lymphocytes of patients MC1, MC3 and

MC7 only assigned strongly defective DNA repair to MC3 and partially to MC1, not to

MC7507,425. Therefore one can conclude that chromosomal radiosensitivity as assessed by

chromosomal aberrations cannot solely account for predicting radiation side-effects

involving cell death of the irradiated area. Furthermore, as described in subsections 5.3.1-

5.3.3, recognition and repair of DSBs seems to be comparatively normal in all cultures,

despite subtle differences between patient cells and effects on repair proteins. Therefore, it

was hypothesized that RS may manifest at later timepoints after IR through cellular survival

mechanisms.

To assess long-term effects of IR in the RS cultures, colony survival was established and

commonly used doses ranging from 2 to 8 Gy508 were applied to the cells, and representative

data after 4 Gy as intermediate dose is described in more detail in this thesis. Commonly,

cells need to be seeded in higher densities when preparing for IR, as it can be assumed that –

even in the wildtype control – a great number of cells will not survive the treatment. Cell

death is difficult to assess and the read-out of the CSA assay only provides information about

the surviving fraction. Therefore it cannot distinguish between different forms of cell death

(subsection 2.3.6).

It was very difficult to receive colonies from all the RS cultures, especially MC3 TERT and

MC7 TERT, while the control cells grew well under all tested conditions (subsection 4.4.4).

Whereas MC1 and MC7 cells grew colonies in the unirradiated condition, MC3 TERT cells

preferentially assembled at the edges of the flasks, probably to avoid stress by gaseous

exchange or to use the walls of the plastic for additional support of adhesion and close

assembly for effective communication. Following IR, only MC1 TERT cells showed colony

formation comparable to the control, but still drastically reduced considering the higher cell

number which was required for initial plating. MC3 TERT cells only showed a focus point of

closely assembled cells, which could barely be considered a colony. Strikingly, MC7 TERT

cells failed colony formation in all tested applications.

Possible reasons for the differences in colony forming capacity between the RS cultures

could be their diverse genetic background. As already discussed in the preceding

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subsections, cells of patient MC1 could have acquired RS due to their mutation in HERC2.

This ubiquitin ligase vigorously interacts with the ubiquitin ligase RNF8 (subsections 5.3.1-

5.3.3), which catalyzes nonproteolytic ubiquitylation of H2A-type histones via crosstalk with

RNF168708,658. The latter has been associated with RIDDLE (radiosensitivity,

immunodeficiency, dysmorphic features and learning difficulties) syndrome that shares

some characteristics with other RS syndromes (e. g. A-T). These are for example mental

retardation, microcephaly and other neurological defects709,710. The potentially reduced

activity of HERC2 could not only account for prolonged foci retention after IR, but also impair

action of RNF8, that could lead to RS-associated complications, as has been described for

RIDDLE syndrome710. However, the functional relationship between these proteins may not

be sufficiently impaired in the MC1 cells, as failure of 53BP1 foci formation, which is

associated with RIDDLE syndrome, was not observed in these HERC2 heterozygous cells.

Variations in fibroblast radiosensitivity can be due to several reasons. Not only differences in

DNA repair processes, but also changes in cellular differentiation processes or TGFB1 levels

can relate to RS460. Recent evidence suggests an influence of the age of breast cancer

patients with clinical RS on cellular RS by means of chromosome aberrations711. This aspect

should be considered, as patients MC3 and MC7 were 9 years older than patient MC1 at the

time of sampling (MC1= 51, MC3= 60, MC7= 60). Unfortunately, TERT immortalization was

not successful in non-RS BC patients MC4 and MC6, which constitute matched pairs to

patients MC1 and MC3 and would provide a good assay system to investigate age-related

effects on colony survival other than induced by ionizing radiation. However, colony survival

data of MC4 primary cells is available and showed normal IR response, whereas survival

capacity declined dramatically in MC1 and even stronger in MC3 primary fibroblasts460,

which is consistent with data obtained in the TERT immortalized cultures. Primary data on

MC7 are not available, however, MC10 primary fibroblasts (NEIL1 mutation) also showed

extreme cellular RS, although the patient was comparably young (35 years, data provided by

Dr. Margret Rave-Fränk, Göttingen). This indicates that the age of the patients alone cannot

account for occurrence or severity of RS reactions. Interestingly, subgroups between the

patients within one group were also identified by Auer et al.711, pointing to the inter-

individual variations observed in a magnitude of preceding studies (section 2.4), which is

consistent with the differences in mutational background as well as cellular RS observed

between RS patients in the presented thesis.

As also shown in this work, the manifestation of cellular RS can be diverse across clinical

features of RS and impact on DNA damage repair cannot easily be predicted simply by

characterization of mutations in repair genes. Known RS syndromes such as A-T or RAD50-

deficiency already cause defects in initial recognition of lesions, whereas this is not the case

for the cells of RS patients used in this work. It would be interesting to consider comparative

analyses of colony survival between patient cells with for example RAD50 deficiency and the

RS BC cells, in order to investigate whether the effects on long-term survival are similar.

Furthermore, it is already known that DNA repair genes implicated in clinical RS can take

over functions which are not directly associated with repair. For example, this has been

shown in our lab for RAD50, as it exerts a major influence on progression through mitosis712.

It would be interesting to investigate whether the genes identified in this study also impact

cell cycle control apart from DNA repair. This might correlate with failure of survival at later

time points after IR, as cells usually undergo one or two cell cycles before IR-induced cell

death is initiated713.

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A more detailed inspection of the cellular morphology of the cells – especially after IR –

revealed extreme changes in size and a formation of granules in especially MC3 and MC7

patient cells. These were also visible in MC1 and BJ5TA, however, not as prominent. As the

fraction of morphologically altered cells seemed to increase after IR and resembled a

phenotype similar to senescence, β-galactosidase staining after IR was performed

(subsections 4.4.5 and 5.3.5).

5.3.5 RS may manifest downstream of DSB recognition through cellular senescence

Due to the failure of colony formation in two of the three RS cell lines, significant differences

between the three cultures in colony forming capacity cannot be finally determined at the

present state. In general it should be noted that all the three cell cultures were extremely

radiosensitive compared to the control cells as at least twice as many cells needed to be

seeded to ensure survival, although size and growth characteristics in routine cell culture

were similar.

Inspired by the changing morphology of irradiated RS cells, cellular senescence was

examined. The relationship between DNA repair and senescence, and also between IR-

induced senescence and RS, is already known (subsections 2.3.3 and 2.3.6). In a pilot

experiment in which assignment of senescent cells was reviewed by a second observer,

especially MC3 TERT and MC7 TERT cells showed a prominent decline in the proportion of

non-senescent cells after IR (subsection 4.4.5). Cells, which displayed altered morphological

appearance but were not positive for β-galactosidase staining, were excluded from the

counting. This disqualifier resulted in less non-senescent cell numbers, as cells were not

solely assessed for the development of blue color but additionally for their physiological

appearance. These cells could possibly represent pre-senescent or quiescent cells as

senescence-associated-β-galactosidase is not expressed by these sub-populations510. Pre-

senescence has been described by similar morphological criteria as observed here in non-β-

galactosidase-positive cells714 and further discrimination of pre-senescence and senescence

by for example increased resistance of senescent cells to apoptotic death715 could

characterize the two populations. Distinction between quiescent and proliferative cells could

be achieved by application of the quiescence marker Chromatin Assembly Factor-1716.

As MC3 TERT cells showed the stongest decline in the fraction of non-senescent cells already

24 h after IR compared to BJ5TA, and also TERT-levels in the two cell lines were similar

(subsections 4.3.1 and 4.4.5), this cell line was included in further experiments. In order to

exclude effects of replicative-senescence due to TERT-loss and a possible influence of the

different growth medium used for MC3 TERT cells, several tests were performed in side-by-

side comparisons. As none of the observed changes were significant, cells were grown in

their normal culture medium throughout the whole assay, supplemented with hygromycin B.

Differences between MC3 TERT and BJ5TA were significant at 48 h, 7 d and 9 d after IR.

Fitting of the data with a one phase model showed that both cultures followed exponential

decay according to the residual number of non-senescent cells, similar to radioactive decay,

as expected for the considered system. A higher quality of the fit was obtained for MC3 TERT

and could indicate that senescence is initiated after a certain threshold of DNA damage is

reached, which might spread to neighbouring cells by release of senescence-stimulating

factors into the medium, which again triggers senescence. As senescence is a permanent

state, cells cannot retain proliferative potential to counteract these changes (subsection

2.3.6). At this point, however, it needs to be considered that the fit is based on only four

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timepoints (24 h, 48 h, 7 d and 9 d) which might not suffice to draw conclusions at the

present stage. A possible explanation for the comparatively strong decline of non-senescent

cells in BJ5TA could be the starting colony formation as early as 7 d after IR. Due to colony

development, which is missing in MC3 TERT, BJ5TA grew in close assembly and confluency

conditions were no longer entirely similar to non-colony-forming MC3 TERT cells. Therefore,

evaluation of timepoints longer than 7–9 d would not result in comparable conditions

between the two cultures and additional functional endpoints should range from 72 h to 6 d

after IR.

Recently, a data-mining approach aiming at classification of DNA repair genes according to

their involvement in aging/senescence has been made, which also utilized IPA717. Freitas et

al.717 have associated NEIL1 to aging pathways, which was identified in one RS BC (MC10)

and one Fam BC patient in the presented work. Furthermore, NEK4 has been related to

senescence72, which was found mutated in an RS BC patient. Moreover, RAD51C718 and

FANCL719 were related to senescence/aging pathways and also ABL1 was classified as

senescence-associated by utilizing the GenAge database720. Some genes documented by this

database included findings that were related to variants identified in this thesis. For example

KCNA3 (Potassium Voltage-Gated Channel Subfamily A Member 3) was assigned to be

involved in aging processes, which is related to the SMARCA4 target KCNQ3 (subsection

4.2.3.1). Also some of the major players in DNA repair were part of this database like ATM,

CHEK2, H2AX, and interestingly also BRCA1721. Besides being attributed to aging, BRCA1 has

also been suggested to be implicated in RS317. A recent publication by Kural et al.555

addressed identification of aging-related pathways and found AURKB (Aurora kinase B),

which is an important paralog of AURKC (Aurora kinase C) that was identified in an RS BC

patient in this study. Comparisons of hits from Kural et al.555 with genes identified in BC, Fam

BC and the complete collection of RS patients identified no overlap in the BC group but,

interestingly, BRCA2 in Fam BC and AKR1C2 (Aldo-Keto Reductase Family 1 Member C2) and

DHCR7 (7-Dehydrocholesterol Reductase) in the RS cohort were found, respectively. The

latter genes have not yet been investigated in more detail due to lack of assignment to any

of the initially prioritized categories. Furthermore, a mutation in PTTG2 (Pituitary Tumor-

Transforming 2) was identified in two RS patients which is related to cell adhesion and

apoptosis in a TP53-, and TP21-dependent manner113. Both proteins are known to be

involved in RS 722 and also senescence723,724.

Interestingly, Kural et al. also showed evidence for association of certain metabolism

pathways with aging, for example fatty acid metabolism555. Furthermore, the parkin-

associated pathway, aurora B cell cycle regulation and the caspase network were identified.

By comparison with IPA core analyses results of RS patients, some similarities between these

pathways and IPA hits were present. For example, IPA identified “lipid metabolism” (p-value

of overlap range: 4.32E-02-5.84E-04) and “L-Dopa degradation” (p-value of overlap: 3.9E-02),

however, the latter was also enriched in BC patients. It might be interesting to analyze IPA

results further in regard to overlap of genes or pathways/functions with aging-related

molecules. Also, more aging databases could be searched for genes, which were found to

possess truncating mutations in RS patients.

Furthermore, studies on the association between telomere length and radiosensitivity have

been conducted, which seems to be a promising biomarker for identification of

subpopulations at risk of developing late side-effects725,726. However, the IPA category

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“elongation of telomeres” was not found significantly enriched in RS BC patients but

occurred in BC and Fam BC patients, which suggests that the association between telomere

length and RS is probably of minor relevance in these patients.

The principle goal of radiotherapy is depriving cancer cells of their cell division potential,

therefore it is plausible that senescence apart from apoptosis is a possible outcome of

radiation therapy for both cancer and normal tissues. Regarding results of the IPA analysis,

neither cell death nor senescence were part of the priority findings according to p-value of

overlap. Most cell death pathways after IR are a consequence of mitotic catastrophe and

hence not directly triggered by the initial cellular response to IR713. Furthermore, senescence

has also been described as form of cell death which occurs after accumulation of DNA

damage (subsection 2.3.6). Therefore, it is plausible that not only genes that are exclusively

or directly related to the aging process could account for IR-induced senescence in RS BC

patients, but loss of replicative potential might occur as a secondary consequence of high

amounts of unrepaired damage. Figure 37 shows a possible course of events starting with

radiotherapy treatment and terminating in IR-induced side-effects like immunological

complications. From the data provided in this thesis, one could assume that accumulation of

DNA damage due to impaired repair mechanisms in RS patients triggers initation of

senescence, which activates the senescence-associated secretory phenotype (SASP) resulting

in secretion of cytokines and other proinflammatory substances into the irradiated tissues

which finally manifests in adverse reactions.

Additionally, vice versa, defects in immunological functions, which might be inherent in RS

patients, can result in failure of senescent cell-clearance from the body727. Therefore, both

mechanisms might promote the maintainance of the other. Comparative IPA analyses have

shown that especially inflicted genes of RS BC patients were strongly associated with cancer-

related or cancer-promoting mechanisms (subsection 4.2.3.2). In support of this hypothesis,

several lines of evidence indicate the tumor-promoting effect of senescence728-730 and also

underline accumulating DNA damage as cause for the SASP related to inflammation731,732.

Figure 37 Proposed model of RS as consequence of DNA repair defects and senescence

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MC3 TERT cells have been correlated with impaired RAD51 foci formation at 4 h after IR

(subsection 4.4.3), and showed a prominent decline in γH2AX and 53BP1 foci numbers

between 6 h and 24 h, leading to foci levels at 48 h, which were lower compared to the

unirradiated state. Therefore, the RAD51C mutation likely exerts differential effects on

repair, which might lead to accumulation of residual damage at 24 h after IR. This might be

correlated with loss of repair capacity at 24 h due to early abrogation of signal maintainance

between 6 and 24 h after IR, consistent with early initiation of senescence. Reduction of

RAD51 foci formation by the RAD51C mutation at 4 h after IR could promote the

accumulation of damage by time. This theory is supported by the fact that RAD51C has

indeed been related to the senescence response after IR718.

MC7 TERT cells also showed significant differences between non-senescent cells after IR

compared to BJ5TA. Moreover, ATM signaling was similar to MC3 TERT cells, as recognition

and initiation of repair signaling early after IR was functional but foci numbers declined

rapidly between 6 and 24 h, which might also indicate incomplete repair in these cells.

Similarly to MC3 primary cells, RAD51 foci formation was impaired in MC7 TERT cells. As

both FANCL and ABL1 mutations were described in the context of aging, either (or both, if

function of FANCL is impaired) mutation likely promotes senescence. Interestingly, the

decline in non-senescent cells of MC7 was not as prominent as MC3 at 24 h after IR, which

might indicate a slight delay in initiation of senescence in these cells.

As shown in Figure 38, in contrast to RAD51C (as part of the RAD51 recombinase complex)

and ABL1 (c-Abl), HERC2 functions upstream of the MRN complex and likely exerts a stronger

influence on early time points after IR, consistent with results obtained in MC1 cells

(subsections 4.4.1 and 4.4.2). However, an effect on IR-induced senescence cannot be

excluded at present, as also MC1 TERT cells showed significant decrease in non-senescent

cells 7 d after IR compared to BJ5TA, but this was no longer significant after normalization to

unirradiated controls. In contrast to the other genes, ABL1 has also been associated with

apoptosis (subsection 1.3.2), which is shown in Figure 38. As apoptosis represents an early

form of cell death following IR713, clearance of cells at early timepoints like 24 h could have

already been executed by apoptosis, followed by senescence at 48 h. This could explain the

complete loss of colony forming capacity due to severe reduction in cell numbers early after

IR in MC7 TERT cells and also the later observed initiation of senescence compared to MC3

TERT. Figure 38 was adapted from Figure 3 and proteins and pathways that were addressed

in the course of this study were marked by colored circles.

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5.4 Impact of the DNA damage response on clinical and cellular RS

This thesis focused on characterization of radiosensitivity on the genetic, functional and

cellular level. In the course of the candidate gene approach, TPT1 was silenced and its effect

on ATM signaling was investigated. As no statistically significant changes following

downregulation of TPT1 were observed, it was no longer considered as possible biomarker

of RS. However, as cellular RS assays with patient cells have shown, future studies could

address the question whether TPT1 might also exert late effects on ionizing radiation

sensitivity that might not be observed at early time points after IR. Not only cell-type but

also environmental influences of TPT1 functions are likely to occur as TPT1 is subject to

intense regulation with underlying mechanisms that are incompletely understood (sections

1.5 and 5.1).

It is well known that extreme radiosensitivity can be genetically determined (subsection

2.3.5), therefore it was tempting to investigate whether normal tissue reactions in patients

with no known radiotoxicity syndromes can also be assigned to mutations in certain genes.

Results of exome sequencing showed strong inter-individual differences, consistent with

observed patient-to-patient variabilities across preceding studies that utilized other

approaches (section 2.4). At this point it needs to be emphasized that RS itself is a

heterogenous disease and therefore, it is not surprising that this approach did not result in

monogenetic findings. Furthermore, the patient cohort was also heterogenous, as samples

were collected at different hospitals over a time period of two decades and naturally, type

and clinical stage of cancers, age of the patients and in particular characteristics of side-

effects were different.

It should be remembered, that most of the mutations identified by exome sequencing are of

heterozygous nature. Therefore, expected influences on ATM signaling or other cellular

functions might be compensated by the wildtype allele and therefore show reduced

functional impact. Also, IPA only assesses the gene itself, not the effect of the variant. As not

all mutations found by exome sequencing were manually tested for their impact, a

considerable number of functionally silent mutations could be among the list.

Due to the lack of reproducibility of data gathered during the last decades, reasons why

normal tissue responses could not be reliably related to individual radiosensitivity over such

a long time period were already proposed over a decade ago431. Dikomey et al. criticized that

patients, who differed too much from each other in clinical aspects, were compared side-by-

side431. This was also pointed out by Andreassen et al., who addressed the problem that

previous studies often claimed to have presented a true association of candidate genes with

RS, while the probability of detecting false positives was extremely high429. Often SNPs are

located in non-coding areas without any obvious function733. This possibility is narrowed by

exome sequencing as only coding areas or splice sites (as the only intronic regions) are

addressed, however, also resulting in potential skipping of important regulatory regions.

Furthermore, Dikomey et al. proposed that according to a mathematical model, all irradiated

patients are at risk of developing severe side-effects correlating with time that has passed

after IR431. Therefore, future studies should focus on collection of patient material at defined

time points also years after IR and comparisons should only be made between patients with

similar clinical background. Nevertheless, unknown epigenetic factors could still influence RS

reactions in a way which is barely predictable, especially if timepoints expand over years.

https://www.dict.cc/englisch-deutsch/criticized.html

146

Exome sequencing was performed in three consecutive steps and data was not received for

all patients at once. Prioritization of mutations for validation sequencing was not only

performed according to GeneCards and IPA annotation results, but also depending on

double or even triple hits in different patients. Therefore, genes that did not necessarily

meet criteria for prioritization due to their functions were included in the validation

sequencing project simply because they seemed to be prominent among RS patients. Vice

versa, mutations, which had occurred in more than one patient in the exact same position,

but were subjected to validation as the data was not available in parallel, eventually were

confirmed. These findings should be considered for choosing genes that would not normally

meet requirements for validation sequencing. Future studies could concentrate on

functional characterization of these loci.

147

6 Conclusions and perspectives As a common theme in the course of this thesis, the relationship between ATM signaling and

adverse effects of radiation therapy was investigated. By using a candidate gene approach

that addressed TPT1 on the one hand, and mutational effects of genes in RS patients located

at different mechanistic levels in the DDR on the other hand, ATM signaling was assessed at

the functional and cellular level. The findings of this thesis showed that early ATM signaling

might not necessarily relate to RS. On the contrary, effects on cellular survival and

senescence exceeding timepoints of 48 h after IR were visible in RS cultures and could be a

late consequence of unrepaired DNA damage. Literature findings suggest that fibroblast

radiation sensitivity does not correlate with acute, but rather correlates with late effects461,

which was observed in these particular cells and applies to the manifestation of side-effects

in the majority of RS patients in the presented study.

Using annotation with GeneCards and IPA, ATM signaling was shown to be enriched in RS

individuals with BC compared to non-RS BC and Fam BC patients and also cancer proneness

related to the RS phenotype. The hypothesis that RS patients suffer from residual unrepaired

DNA lesions that in turn trigger senescence, which consecutively promotes immunological

responses, was found to be plausible in cells of patient MC3. These cells were furthermore

shown to be impaired in RAD51 foci formation likely due to their RAD51C mutation, which is

consistent with unrepaired damage and high yields of dicentric chromosomes and extra

acentric fragments per cell (as shown on blood lymphocytes in previous studies425,507).

Formation of dicentric chromosomes prevents accurate cell division which can lead to

senescence or death of cells after one or two attempts to proceed through mitoses failed.

MC7 cells, which also showed RAD51 foci impairment likely due to their ABL1 mutation,

could have died of apoptosis as very early IR-consequence, which is consistent with low

yields of dicentrics in lymphocytes of this patient425,507. In both cell lines, failure of colony

survival correlated with cell death after IR. MC1 cells on the contrary might escape from

definite IR-induced cell death as the HERC2 mutation likely affects delay of early recognition

of DSBs and retention of repair foci, but is comparable to the control in RAD51 foci and

senescence assays. Perhaps consistent with these observations, side-effects in patients MC3

and MC7 were not localized to the site of direct IR exposure, as was observed for the MC1

patient, but spread to other regions of the body (Supplementary table S-1). This could be

due to the secretion of inflammatory cytokines by senescent cells arising from damaged

tissue in MC3 and MC7 which might cause overall tissue dysfunction456. It would be

interesting to assess whether senescence-associated soluble factors could induce cell cycle

arrest in control cells and render them senescent, for example by transferring medium from

irradiated MC3 TERT cells to BJ5TA. Furthermore, IR-induced senescence should be validated

by a second protocol, for example by assessment of the senescence markers TP21, TP16 or

senescence-associated heterochromatic foci formation among other methods734.

Figure 39A shows a simplified mechanism that could reflect the relationship between DNA

damage as initially caused by IR-induced ROS, and the cell fate depending on residual

damage residing in the DNA of the particular cell. The final descision whether the cell

survives or dies is well known to be correlated with the amount of damage that has

accumulated in this cell. In the control cells BJ5TA (left-hand side of Figure 39A), which are

radioresistant, primary damage by ROS can be repaired and the cell survives and continues

to proliferate. In RS patients MC1, MC3 and MC7 (right-hand side of Figure 39A), primary

148

damage by ROS remains unrepaired or partially unrepaired (MC1), which leads to secondary

damage through initiation of senescence. This in turn might spread to further cells in its

vicinity and transform neighbouring fibroblasts into proinflammatory cells via SASP735. Also,

the similarity between the exponential decay in non-senescent cells in MC3 TERT with the

one-phase model of radioactive decay could indicate a secondary effect by senescence itself

that adds on to the primary cause of damage. The RS BC cells could be correlated to the

amount of remaining damage and likelihood of undergoing cell death by observations in

cellular RS assays in the following order: MC1 < MC3 < MC7.

Figure 39B summarizes the results of this thesis according to the initially addressed question

which stage of the cellular damage response adverse effects in RS patients can likely be

assigned to (see also Figure 10). Further experiments are needed to characterize the IR-

induced cell death mechanisms and differences between the three cultures in more detail.

Figure 39 Possible mechanism of DNA repair defects leading to radiosensitivity

Follow-up studies should clarify the exact nature and possibly synergistic effects of more

than one cell death mechanism initiated by IR in cells of RS patients. Cell death through

apoptosis, senescence, autophagy or necrosis can occur early, or late as consequence of

mitotic catastrophe, following IR (Figure 40). Both chronological events can eventually lead

to failure of clonogenic survival.

149

Figure 40 Early and late forms of cell death leading to failure of clonogenic survival after irradiation Schematic representation of cellular mechanisms following DNA damage, as depicted by black arrow on the left-hand side.

After attempting mitosis, cells can die early by apoptosis, senescence, autophagy or necrosis (subsection 2.3.6). Some cells

might complete mitosis and are able to form colonies in the colonogenic survival assay (right-hand side). However, cells

might also fail subsequent mitoses, undergo mitotic catastrophe and eventually die by apoptosis, senescence, autophagy or

necrosis. Cells undergone mitotic catastrophe/crisis are indicated by enlargement in size and multinucleation,

granularization or shrinkage, depending on the form of initiated cell death (subsection 2.3.6). Source: Wouters BJ. Cell

death after irradiation - how, when and why cells die. Basic Clinical Radiobiology. 4th ed. UK: Hodder Arnold 2009.

If IR-induced senescence actually accounts for the adverse effects in a majority of patients,

antioxidants aiming at suppressing these effects in normal tissues could be applied during

RT, which has already been established in clinical routine456. As effects of senescence in ex

vivo cell culture models were also prominent at 7 d after IR, this treatment would need to be

extended for at least one week after IR exposure. Vice versa, if IR-impact on side-effects due

to senescence also correlates with clearance of cells in the tumor tissue (given that the

genetic background of the tumor has not deviated much from its tissue of origin due to

somatic mutations), senescence-promoting substances could be directly applied into the

tumor to enhance radiosensitization.

Although survival and senescence after IR could only be investigated in three RS BC cell lines

in this thesis, several lines of evidence from exome sequencing results point to the fact that

RS BC patients either exhibit a comparatively high number of DNA repair gene mutations or

mutations in immune system or aging-related genes. Furthermore, genes associated with

cell death like death-inducing ligant variants TNFRSF9 and TNFRSF10A were identified in two

RS patients. The TNF family has been recurrently described in the literature as associated

with RS (see section 2.4), for example fibrogenic cytokines like TGFB1, and could also

account for inappropriate immunological responses in RS patients. Both genes were part of

an upstream regulatory network administered by SMARCA4, which itself has been implicated

in cancer and is known to interact with BRCA1541,542,582. Future studies should address the

effect of TNFRSF9 and TNFRSF10A for RS in these patients, which has been already described

for association of TNFRSF10/TRAIL with radation-induced acute and subacute dermatitis550.

The skin-associated adverse effects in patient HA213 may thus be attributable to its

mutation in TNFRSF10A. Moreover, mutations in genes directly correlated with skin lesions

should also be considered as possible enhancers of adverse effects, especially in patients

with exclusively cutaneous reactions.

150

Altogether, it can be concluded that the genetic signature of RS is as individual and multi-

facetted as the RS phenotype itself. As no clearly RS associated markers were identified in

the course of this work and the common RS biomarkers like CHEK2, KAP1, γH2AX and 53BP1

seemed of minor impact in representing clinical RS in this study, pre-testing of patients could

be performed by colony survival assays with primary skin fibroblasts.

Interestingly, comparative IPA analyses identified some consensus between Fam BC and RS

BC patients. For example, NEIL1 was mutated in both patients at different positions.

Furthermore, both maladies show high correlation of gene mutations in both DNA repair and

also cancer-related genes (subsection 4.2.3.2.). It would be interesting to investigate

whether genetically determined BC predisposition correlates with risk of late IR effects. DNA

from patients with a strong familial history of BC who additionally suffered from side-effects,

should also be subjected to exome sequencing and results compared to RS BC and Fam BC

patients. Limitations, however, could be the low accessibility of biological material from

patients suffering from both complications, as occurrence of Fam BC as well as RS BC are

rare events. At this point it should be considered, that the RS BC patient MC2, who had a

great grandmother also diagnosed with breast cancer (third-degree relative), shows high

association with cancer genes in IPA (subsection 4.2.3.2.). Technically, although not a

prominent familial BC case as affecting a third-degree relative311, this pedigree can also

increase BC risk, however, low736. The MC2 could be counted to a new goup of “Fam RS BC”

but unfortunately, no viable cells were available from this particular patient.

Finally, to provide more insights into the genetic determinant of RS candidate genes, the

breakthrough technique of genome editing by means of CRISPR/Cas9737 may be applied in

two different approaches. Firstly, mutations in candidate genes, for instance HERC2, RAD51C

and ABL1 could be introduced into BJ5TA cells and the mutant cells investigated in cellular

RS assays. Vice versa, these mutations could be compensated by the CRISPR/Cas9-system737,

which could rescue the RS phenotype of these cells. Late IR-effects like senescence and

colony survival should be investigated. TPT1 mutations could be included in the

CRISPR/Cas9737 manipulation of cells in order to analyze late effects of TPT1 impairment on

colony survival potential, which could not be achieved though siRNA silencing over an

extended time period.

Moreover, cells of the two matched pairs MC4 and MC6 should be again subjected to an

immortalization approach with TERT to achieve BC cell culture models for comparison with

RS BC cells, which could be utilized to test the hypothesis established in this thesis.

Furthermore – if available – fibroblasts should be derived from Fam BC patients in parallel.

However, all these approaches might just aim at identifying the genetic background in

selected patients, not providing a more generalized and global association of a pathway with

clinical RS. Therefore, more studies with material of additional RS patients and – if available

– also their family members should be performed. Future studies could aim at identification

of superior pathways similar to the SMARCA4 pathway shown in this thesis, which might be

more reliable when investigated with a larger data set. If RS genes can be successfully

isolated, correction of mutations in RS genes in healthy tissues whilst increasing

radiosensitition solely in the tumor environment by next-generation gene technology could

save healthy tissues and in parallel exploit cell death capacity pathways solely in the tumor.

If patients are screened for mutations in RS susceptibility genes prior to RT, also non-

reactors could benefit from higher dosage meeting individual requirements in line with

151

personalized therapy. Figure 41 summarizes major findings of this thesis and indicates

possible future studies.

Figure 41 Conclusions and suggestions on follow-up studies

152

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8 Supplementary information Supplementary table S-1 Clinical data of radiosensitive patients and two matched pairs

Sample Gender Type of

tumor Irradiated

area/ treatment

Type, quality, and energy of irradiation

Side effect in organ/tissue

Acute tissue reaction

RTOG grade

Late tissue reaction

RTOG grade

HA210 F Mamma ca Breast P/8 MV/8 MeV Skin 3 1

HA211 F Mamma ca Breast P/8 MV, E/8 MeV Skin 3 1

HA212 F Mamma ca Breast P/5 MV, E/8 MeV Skin 3 2

HA213 F Mamma ca Thoracic wall P/5 MV, E/8 and 12 MeV

Skin 3 Expired

HA214 F Mamma ca Thoracic wall P/5 MV Skin, lung 1, 3 –, 3

HA215 F Mamma ca Thoracic wall P/8 MV, E/8 and

12 MeV

Skin, subcut. tissue, lung 2, –, 3 2, 2, 2

HA216 F Rectum ca Pelvis P/10 MV Lower GI tract 4 –

HA223* F Mamma ca unknown Tamoxifen 3xCMF Plexus palsy 0 3?

HA224* M Prostata ca unknown T16 unknown 1 ?

HA225* F Mamma ca unknown unknown unknown 1 ?

MC1 F Mamma ca Breast 50+12 Breast edema and fribosis

2 3

MC4 F Mamma ca Breast 50+12 -, matched pair to MC1 - -

MC2 F Mamma ca Breast 50+12 Gy Breast edema and fribosis

1 3

MC3 F Mamma ca Thoracic wall, internal

mammary &

supraclav. nodes

50+10 Gy Breast edema, lung, skin 2, 0, 2 0, 2, 3

MC6 F Mamma ca Breast 50+12 Gy

- , matched pair to MC3 - -

MC7 F Mamma ca Breast 50 Gy Breast edema, lung, skin 2, 0, 2 3, 0, 2

MC10 F Mamma ca Breast 50+12 Breast edema, lung, skin - 3

HA150 M Hypopharynx Surgery

V/1992

Co60/12.5 MeV Skin (fibrosis of left neck

with rigid tissue and moderate restriction of

motion & drastic

xerostomia )

Lymphoedem

a grade II

Teleangiectas

ia grade III

HA173 M Squamous

epithelium carcinoma of

left tonsil

Surgery

V/1996

6MeV

Photons/10MeV Electrons

Skin (fibrosis of left neck

with rigid tissue and moderate restriction of

motion & drastic

xerostomia )

Glossitis,

mucositis, xerostomia

grade III

Xerostomia

grade III

HA175 F Keratinizing squamous

cell carcinoma of

the base of

the tongue

Surgery VII/1995

(including neck

dissection)

6MeV Photons/10MeV

Electrons

Connective tissue (myofibrosis), drastic

restriction of motion (grade 3), pharyngeal

telangiectasis (grade 2)

& xerostomia (grade 2)

Mucositis grade II

Fibrosis grade III

HA195 M Squamous

cell carcinoma

external ear

Surgery

X/1990

Co60/12MeV Skin oedema II,

epitheliolysis II mucositis I,

Xerostomia I

Fibrosis grade

III

*Patients with severe chemoradiosensitivity (personal communication Dr. Thilo Dörk-

Bousset/Prof. Dr. Markus Stumm) without detailed clinical documentation.

201

Supplementary figure S-1 No alterations in TPT1 levels after IR in different cell systems and no effect of TPT1

knockdown on p-CHEK2 Ser19 levels after IR

Western blot of ADP and MCF10A whole cell extracts after treatment with TPT1 siRNA (si) or scrambled control

(ctrl) 48 h prior to IR and lysed 30 minutes after 6 Gy IR (panel A). The immunoreactivities of p-CHEK2 (Ser19),

TPT1 and β-actin as loading control are shown. Panel B shows whole cell extracts of ADP cells which were

treated with siRNAs specific for TPT1 (si) or scrambled controls (ctrl) 48–72 h prior to lysis. TPT1 levels in whole

cell extracts from ADP cells (panel C), the triple negative breast cancer cells lines (HCC1937 and HCC1395) and

normal breast epithelial cells (MCF10A) in panel D are shown 30 min after 0.06 Gy, 1 Gy and 6 Gy IR. β-actin

was used as loading control.

203

Supplementary figure S-3 No evidence for colocalization of TPT1 and γH2AX or decreased γH2AX foci

numbers after TPT1 knockdown

Confocal analyses of immunostainings of asynchronous, subconfluent ADP (panel A) and MCF10A (panel B) cells

preextracted with Triton X-100265

and non-preextracted control cells fixed 1 h after IR. Cells were treated with

TPT1-specific siRNAs (TPT1 knockdown) or scrambled controls (negative control). Antibodies against TPT1

(green) (ab133568) and γH2AX (red) were used and nuclei were stained with DAPI (blue). Panels C and D show

immunostainings of asynchronous, subconfluent ADP cells preextracted with Triton X-100265

and non-

preextracted control cells fixed 1 h after no (C) or 1 Gy IR (D). Antibodies against TPT1 (red) (ab37506) and

γH2AX (green) were used and nuclei were stained with DAPI (blue). Scale bar= 25 µm.

204

Supplementary figure S-4 No evidence for nuclear translocation of TPT1 in ADP or colocalization with γH2AX

after IR in HCC1937 cells

Panel A shows immunostainings of asynchronous, subconfluent HCC1937 cells fixed 1 h after no (0 Gy), low

(0.25 Gy) or medium (1 Gy) IR. Antibodies against TPT1 (green) (ab133568) and γH2AX (red) were applied and

nuclei were stained with DAPI (blue). Similar results were obtained in HCC1395 and HCC38 cells. Panel B shows

enlargements of panel A with arrows pointing to the area of possible “foci-like”-structure-forming. Confocal

pictures of translocation analyses in non-preextracted ADP cells stained with TPT1 (ab133568) after 0 Gy and

1 h after 1 Gy irradiation are shown in Panel C. Scale bar= 25 µm.

206

Supplementary figure S-6 Secondary antibody controls for immunostainings

Immunostaining controls with solely secondary antibodies applied to ADP, HCC1937 and MCF10A cells

exemplarily given for co-staining with Alexa Fluor Anti-rabbit IgG 488 in green and Alexa Fluor Anti-mouse IgG

546 in red, as well as co-stainings with FITC-conjugated Anti-mouse IgG antibody in green and Alexa Fluor Anti-

rabbit IgG 546 in red, respectively, in the upper part of the figure. Antibody controls for BJ5TA; MC1 TERT, MC3

TERT and MC7 TERT cells using green Alexa Fluor Anti-rabbit IgG 488 and red Alexa Fluor Anti-mouse IgG 546

are given in the lower panel. Nuclei were stained with DAPI (blue). Scale bar= 25 µm.

207

Supplementary table S-2 Raw data of γH2AX foci after TPT1 knockdown and irradiation

Given are foci/cell counted on different pictures in rows. The average number of cells counted was 100. The

number of counted pictures varied depending on the density and distribution of the cells and the mean over

several individual cells in one photo is shown in one row.

ADP γH2AX first experiment

0 Gy ctrl 0 Gy si 1 Gy 1 h ctrl 1 Gy 1 h si 1 Gy 6 h ctrl 1 Gy 6 h si 1 Gy 24 h ctrl 1 Gy 24 h

si

1 Gy

48 h ctrl

1 Gy 48 h si

13.3 10 36.3 30 25 18.1 18.7 25 10.3 8.5

10.3 8.5 31.3 42.2 20.3 28.8 26 30.5 28 16.5

10.5 14 23.7 21.7 16.5 19.5 25 42 17.7 13

9.2 12.3 26 25.5 16 18.3 17.3 43.5 19.7 9

17.8 13.3 33 29.4 23 18 21.3 25 29 27.5

13.5 13.7 25 27.4 20 16.8 28 17 13 16.5

12.7 24.5 24 37 13.5 18 14 42 32.3 14

14 11.5 37 21.5 14 18.3 19.3 18 28 11.7

22 9.6 29 20.3 17.8 25.7 15.5 19.5 33 16

9.9 8.7 36 32 18.7 24.7 12.7 15.3 23.5 16

15.5 14.5 27 34.5 23.3 29.8 16 15.6 17.3 11.3

19 16.7 39.8 34.3 27 26.5 34 46 9.7 17

17 11.6 27 24 20.3 21.7 19.7 28.8 20.5 31

14 11.5 30.5 24.3 18.3 27 20.8 20.7 15 31

10 13.4 33 18.7 13.7 22.3 15.5 15 8 14.8

13.3 11 27 26.3 22.5 29.6 18.5 27 20.3 27.5

11 17.7 20.7 26 21.2 16 27 27 13.3 13.3

23 15 37 21.5 19.6 17 8 30 11.5 13

12.2 7 25 29 23 18.5 12.3 21.3 19 8.5

10.4 9.5 30.7 28 27.5 20.8 11.5 14.5 11.7 16

16 12 34.3 19.3 16 32 19 20 12.7 12.5

14.5 16 26.8 31 13 11 38 10 26

23.5 7 26.7 21.7 17 18 28.5 15 20

18.5 11.5 32.5 23 15 19.4 31.5 19.7 17

16 17.5 29.3 25.7 26 16.7 22.3 22 15.3

17.6 11.5 23.3 30 16.5 12 25.3 10 28

24.7 16 31.7 35.3 25.8 31.5 40.5 12 16.3

20.3 11 24.7 20.8 13.3 21 28 11.3 21

9.8 14 21.6 22.5 24 10 30 15.6 29.7

17.5 31.3 25.3 14 14 24 22 21.5

12.4 22.2 27.7 18 32 19 7

13.3 20 18.5 46.5 10 23.5

15.3 28.7 31.3 45 22.5 10

15.3 43 28 20

13.5 27 14 14

13.3 29 35 24

20.3 32 23 13.5

15.2 37 23 30.5

15.5 24.3 23.5 16.8

17 29.3 19 12.5

208

37 22.3 36

42 22.3 30

35 16 24.5

30.3 22

27

15.5

ADP γH2AX second experiment

0 Gy ctrl 0 Gy si 1 Gy 1 h

ctrl

1 Gy 1 h si 1 Gy 6 h ctrl 1 Gy 6 h si 1 Gy 24 h ctrl 1 Gy 24 h

si

1 Gy

48 h ctrl

1 Gy 48 h si

11 11 20.7 16 27 21.5 9.5 16 6 11

14.3 11 18.8 37.5 18 21 11.5 25 9 11

10 15.8 23 37 15 15.3 15.5 21 9.3 12

10.4 16.5 15.7 18 21 18.5 21 25 22.5 12

15.7 11.5 26.5 20 19.5 19.5 12.5 22 7 12.3

17 17.5 28.5 17 23.5 22 13 23.3 23 12.5

14.3 7 24 18 26.5 15.5 10 28.5 18.5 13

14.3 7.2 25 26.5 20 18 12.7 24 12 13

13.7 13.3 21.5 13.7 28 13.3 9.3 19.3 24.5 14.5

17 8.6 24.5 28.5 24 18 19.5 32.5 12.5 15.5

14.7 8 28.3 19 20 24.7 14 25.3 18.7 16

17.7 11.7 19.5 17 26 14.3 9 31.5 23 16

16.5 23 29 37 33.5 14.5 10.5 26.3 11 17.5

10.3 9.5 28.5 23.7 23.5 21.7 16.5 16.5 18 18

13.6 16.3 27.5 18 19 24 16.8 20.8 18.7 18.5

14 13 22.7 33 26.7 23.5 15.8 20 10.5 18.5

16.5 9 18 33.5 27 20.5 18.5 25 11.5 18.7

12.5 7.5 15 23.7 24.7 17.5 9.8 24.7 16 19

18.8 15 28 23.3 28 18.3 20.5 21.5 18.3 20

19.5 13 29 19 16.7 20.3 19.3 14.5 17 20

9.8 8 16.3 26 17.3 24.5 16 21 25.5 20.3

18 16 27.3 20.3 17 23.3 11 22 9 20.5

15.3 18.4 20 27 18 15.3 23 20 16.3 21

18 6 18.3 28.5 12.7 16 19.3 27.5 19 22

19 14.3 23 23 16 14.3 12 28.5 21 22

17.3 6.3 16.5 26 14.8 14.7 21.5 24 10.5 22

12.5 12.8 15.3 18 18 21.2 11.5 23.3 17 22

15.3 6.3 28.7 20.5 18 19 13 15.5 15.5 22.3

17.3 22.5 25 22 14 23.3 19.3 15.8 8 22.7

15.7 22.3 29 16.3 19.7 15.3 26.7 16 24

18.3 21.5 27 20.5 18.8 14 16 24

13.3 27.3 30 20 21 25.3 18 25

15 26 27 19.5 22.5 20.8 28 25.3

18.3 24.5 18 24.7 16.3 14 26

24 23.3 28.3 11.7 22.5 23.3 26

23.3 17 22 14.7 27

23 15.7 24 15 27

24.3 16.5 13.5 17.8 28

209

21.3 27 23.5 28.5 28

24 28 26.5 29.5

27 30 26 30

21 24 30.3

28.5 18 30.7

21 31

27 31

31.5

32

32

MCF10A γH2AX first experiment


ctrl


si

1 Gy

48 h ctrl

1 Gy 48 h si

24.5 35.8 24 44.5 25.5 37.5 13.2 20.3 8.4 13.7

25.3 24 33 42 25 36 14.5 18.8 6.8 9.8

31 26.5 28.8 44.8 27.3 37 15 13.5 7 14.5

19.7 34.8 29.5 41.3 19.3 30.3 15.6 16.4 7 22.7

21.7 22.2 34.3 25.8 25.5 27 15.4 15 9.5 20.3

18.5 23 23 36.3 28.7 25 9.7 15.4 10.7 25.5

16.7 26 30 28.3 22.3 37.3 13 11 13 23

18 21.3 34.3 34 21.5 34.3 14 22.5 11.5 17

20.8 20.3 36 27 19.8 28 15 15 11.8 24.5

21.3 25.3 34.3 34 25.8 25 13 18.6 12 19.8

22.5 25.7 39.5 30 18 28.3 9.8 14.8 6.5 17.3

20.8 19.3 24 42 25 37.4 10.3 12.5 10 17

21.3 26.7 39 32 18.3 29 10.7 19.2 7.3 19.7

17 27.7 35 41.5 15.4 27.5 9 20 6.3 19

20.8 25.3 40.3 44.8 36 27.3 13.5 17.7 13 12

18 28.3 42.5 34 17.5 25.7 11.8 16.8 9.8 13

21.8 25.6 23.5 33.3 21.6 33.7 15 17 9.5 18.5

20.8 31 27.5 37 37 27.5 10.3 15.5 5.7 10

21.3 20 28 35 16.7 30 10.7 11.7 6.5 14

24.5 21 24 33.3 15.6 37 10.3 11.7 8 8

18.3 14.5 27.5 33 29.5 37.8 10.3 14.5 10 15

18.5 21 22 32 20 40.3 11.4 15.4 7 13.3

16.3 16 21.7 35 17 33 16.3 15.2 9.3 25

32.5 24.3 19.3 48 26 27 11.5 15.4 7.7 7

18.3 22.5 28.7 26.3 21.2 40 16.6 21.3 10.7 19

23 22.2 33 38.7 39.3 14.5 27 11 18.3

24.5 22.5 30.7 46 33.3 13.7 12 5 21

14.7 16.5 27 35.3 38.3 17 8 7

18.3 26.7 31.5 30.8 28.8 13 11.8 24

51 26.8 36.2 12.7 10.5 11

32.3 13.7 6.4 18

23.7 20 16

28 15.5 14

210

10.2

8.3

18.3

16

8.5

25

18

14.5

22

MCF10A γH2AX second experiment


ctrl


si

1 Gy

48 h ctrl

1 Gy 48 h si

20 24.5 24 19.3 10 25 13.4 11.8 7.3 9

15 24 20 21 15 26 12.4 14.7 9.5 11.7

13.5 17 17.7 21 12 23 14 14.2 14.3 14

12.5 23 27.5 18.7 11.3 16 14.6 12 10 9.3

19.5 24.5 24 18.7 25.8 19.3 11.4 11 9 13.3

16.3 21 24 18 14 19.5 11 13.8 12 12

23.7 23.3 22.5 19 16.7 16 15 10.8 13.5 15.5

20.7 17.7 24.8 18 17.8 16.8 10.8 13.5 8.6 15

21.5 20.5 18.7 19 19.8 24 14 10.5 11.4 17.3

16.7 12 22.7 18 13.6 15.3 13.7 11 12.7 17

15.7 23.3 23.3 21.5 17.8 27.3 12.7 12.3 9.3 13

11 18.8 26 18.3 21.3 20 14 12 11.5 17

16.5 19.3 23.7 21 21.5 17.3 11 12 10 11

12 18.5 21 22.7 13.8 30.3 13 15.7 16.5 16.5

12.3 20 23.3 20.7 16.6 24.8 10.5 14.3 15 7

19.3 17 25 18.8 10.2 24.7 11 14.5 9.3 8

13.7 13.5 25 20 16 25 13.8 13 11 10

14.5 19 17.8 21 17.8 18 15 11.3 11.7 17

17.5 23 17.7 26.5 17.3 27 10.4 13.3 8.5 19

21 20.3 21 19.7 21.3 21.3 14.4 13 11.3 11

17.3 22.7 12.3 21.7 19 20.3 10 13 11.5 11

14.3 22 27.5 21 17.3 22.3 10.8 13 9.3 8

16 14.8 24.8 29 21.4 20 15.3 12 8 18.3

17.3 24.7 16 25.3 18 23.3 11 12.3 12.6 16.5

19.2 16.5 23.3 20.6 20.3 32.7 9.8 12.8 14.3 5

18.3 23 19.3 26.6 16.8 19.5 11 14 12.8 15.5

20 18.3 28 15.5 10 24 10 14.3 12.5 15.5

15 17.3 23 16.8 19 25.3 8.6 10.2 11.3 8

22 15 26.5 16.3 15.3 30.5 12.3 13.7 11.6 14

15 21 17.5 29 14.5 23.3 11.3 12.3 11 9

16.7 16.5 23.5 19 10.8 22.5 14.5 16.5 17.7 14

17 24.7 24 16.7 18.3 29 14 16.8 14.7 11

18.7 24 23 24 13.3 26.7 9.8 12.8 8

16 22.3 15.3 18 31 12.4 15 5

211

18 26.5 16.7 33.5 13 14.5 7

18.3 16.5 14.8 9.3 16 9

16 16.3 10.8 11.3 13.8 12.5

23 15.5 16.7 13 16 14

24 15.8 16 14

15.7 17.5 15

18 7

20.5 6

18.7 18.5

12

14

13

Supplementary figure S-7 No changes in 53BP1 foci numbers after IR in TPT1 knockdown cells compared to

controls

Asynchronous, subconfluent cells were treated with siRNA against TPT1 (si, light blue) or scrambled controls

(ctrl, dark blue) 48 h before IR with 1 Gy. Cells were fixed on glass slides 1 h, 6 h, 24 h or 48 h after IR and

stained for TPT1, 53BP1 and DAPI. 53BP1 foci were counted manually in an average of 100 cells on each slide

and cells with a minimum of 3 foci were considered foci-positive and subjected to counting. Means with

standard deviations are shown for ADP cells (left) and MCF10A cells (right).

Supplementary table S-3 Raw data of 53BP1 foci countings in ADP and MCF10A after TPT1 knockdown

ADP MCF10A

Mean SD Mean SD

0 Gy ctrl 8.3 2.7 14.2 2.4

0 Gy si 9.4 3 12.8 2.3

1 Gy 1 h ctrl 17.6 4 17.3 3.6

1 Gy 1 h si 18.1 5.3 15.7 4.1

1 Gy 6 h ctrl 14.9 3.4 13.3 2.7 1 Gy 6 h si 14.3 3.7 17.1 4.7

1 Gy 24 h ctrl 11.34 2.9 9.1 1.2

1 Gy 24 h si 12.4 2.7 10.8 2.0

1 Gy 48 h ctrl 12 3 7.4 2.1

1 Gy 48 h si 13.6 3.8 7.7 3.1

212

Supplementary table S-4 Mutations that occurred in the same genes in more than one patient

HA212 chr19 17397498 17397501 TGTT – exonic ANKLE1+

MC2 chr19 17397501 17397501 – TG exonic ANKLE1+

HA210 chr10 33017896 33017899 AAAT – exonic C10orf68*

HA216 chr10 33018277 33018277 A – exonic C10orf68*

MC1 chr10 33017896 33017899 AAAT – exonic C10orf68*

MC10 chr12 121678327 121678327 – TT exonic CAMKK2+

MC3 chr12 121678328 121678328 T – exonic CAMKK2+

HA211 chr12 121678346 C T intronic CAMKK2+

HA211 chr12 121678327 CT C,CTTTT,

CTTT

exonic CAMKK2+

HA215 chr2 197521469 197521470 TG – exonic CCDC150+

HA216 chr2 197540900 197540900 G T Exonic CCDC150+

HA224 chr2 197521469 197521470 TG – exonic CCDC150+

MC1 chr12 51740415 51740415 – AG exonic CELA1+

MC3 chr12 51740408 51740411 ATAA – exonic CELA1+

MC3 chr12 51740416 51740416 – G exonic CELA1+

HA223 chr22 19171074 19171074 – T exonic CLTCL1+

MC4 chr22 19189003 19189003 – C exonic CLTCL1+

HA215 chr11 6560532 6560532 C T exonic DNHD1+

HA215 chr11 6588977 6588977 A – exonic DNHD1+

MC2 chr11 6550231 6550231 – A exonic DNHD1+

HA175 chr1 97915614 C T DPYD+

HA224 chr1 97915614 97915614 C T intronic DPYD+

HA224 chr6 31380161 31380161 – CT exonic;intronic MICA+

MC3 chr6 31380158 31380161 GCTG – exonic MICA+

HA213 chr5 41017978 41017979 GA – exonic MROH2B

MC3 chr5 41064591 41064598 TTCATCCT – exonic MROH2B*

MC10 chr1 17083816 17083816 G A exonic MST1L*

MC2 chr1 17087542 17087546 GTGCT – exonic MST1L*

HA212 chr12 113384659 113384659 G T exonic OAS3+

HA223 chr12 113403675 113403675 C T exonic OAS3+

HA223 chr1 248801945 248801951 CAGCACG – exonic OR2T35°

MC7 chr1 248801602 248801602 – CA exonic OR2T35°

HA175 chr6 31106507 C CG exonic PSORS1C1*

HA214 chr6 31106501 31106501 – C exonic PSORS1C1*

MC6 chr6 31106500 31106500 – C exonic PSORS1C1*

HA173 chr12 21036518 TTATC T exonic SLCO1B3*

HA195 chr12 21008080 21008080 – AATTG exonic SLCO1B3*

MC1 chr5 139931628 139931628 – GT exonic SRA1+

MC10 chr5 139931629 139931629 – G exonic SRA1+

MC2 chr4 338202 338203 TC – exonic ZNF141+

MC3 chr4 338197 338197 – GA exonic ZNF141+

HA211 chr19 35251141 CTT C exonic ZNF599°

HA225 chr19 35250691 35250692 AG – exonic ZNF599°

213

HA212 chr16 89291210 89291210 – GTGA exonic ZNF778+

MC2 chr16 89294865 89294865 C A exonic ZNF778+

+= validated, *= validation not possible, °= not subjected to validation

Supplementary table S-5 Identical mutations that occurred in at least two patients

HA150 chr19 831815 GT G exonic AZU1+

HA210 chr19 831815 GT G exonic AZU1+

HA210 chr20 34828141 34828141 – C exonic AAR2+

MC10 chr20 34828141 34828141 – C exonic AAR2+

HA210 chr7 31697913 31697913 – T exonic CCDC129+

HA223 chr7 31697913 31697913 – T exonic CCDC129+

HA173 chr3 56655621 A AAGAG exonic CCDC66+

MC1 chr3 56655621 56655621 – AGAG exonic CCDC66+

HA173 chr4 76521525 C T intronic CDKL2+

HA214 chr4 76521525 76521525 C T intronic CDKL2+

HA225 chr4 76521525 76521525 C T intronic CDKL2+

HA150 chr16 23768875 23768875 C T exonic CHP2+

HA195 chr16 23768875 23768875 C T exonic CHP2+

HA210 chrX 133988145 133988145 A – exonic FAM122C+

MC10 chrX 133988145 133988145 A – exonic FAM122C+

HA173 chr11 12270793 GGT G intronic MICAL2+

HA214 chr11 12270794 12270795 GT – intronic MICAL2+

MC3 chr11 12270794 12270795 GT – intronic MICAL2+

HA216 chr18 48331612 48331613 AG – exonic MRO*

MC7 chr18 48331612 48331613 AG – exonic MRO*

HA210 chr14 23889445 23889445 – G intronic MYH7°

HA215 chr14 23889445 23889445 – G intronic MYH7°

HA210 chr7 123197691 123197691 G C exonic NDUFA5°

HA225 chr7 123197691 123197691 G C exonic NDUFA5°

HA195 chr16 450140 450140 – AG exonic NME4+



HA175 chr4 37962608 CAT C exonic PTTG2+

HA210 chr4 37962609 37962610 AT – exonic PTTG2+

HA175 chr6 71378354 AC A exonic SMAP1°

HA215 chr6 71378355 71378355 C – exonic SMAP1°



HA195 chr15 81624929 81624929 G T exonic TMC3+

HA212 chr15 81624929 81624929 G T exonic TMC3+

HA195 chr1 16073527 16073527 – G exonic TMEM82°

HA215 chr1 16073527 16073527 – G exonic TMEM82°

HA211 chr6 41766432 41766432 C CCCCCA exonic USP49+

HA223 chr6 41766432 41766432 – CCCCA exonic USP49+

HA210 chr4 265195 265195 A C exonic ZNF732*

HA224 chr4 265195 265195 A C exonic ZNF732*

+= validated, *= validation not possible, °= not subjected to validation

214

Supplementary table S-6 Mutations identified by exome sequencing and subjected to validation sequencing Patient Chr

.

Position

start

Position

end

Ref. Mut. Type Gene Forward primer

5’3’ Reverse primer

5’3’ Rs-number

HA210 20 34828141 34828141 – C exonic AAR2 GCATCCACTTCCTC

CACTAC

CAGGTAGCACATCG

GAAAAG

MC10 20 34828141 34828141 – C exonic AAR2 GCATCCACTTCCTC

CACTAC

CAGGTAGCACATCG

GAAAAG

HA223 16 48212598 48212598 C A intronic ABCC11 GCAGAAAGACATA

CAGAGGG

CCTTCATGTACTGCA

GTATC

HA195 17 27893566 27893566 A – exonic ABHD15 CTTGTTTGCAAGC

CGTCGGC

GTGTCGGAAGCGGA

TGTATG

rs201971667

HA216 17 27893566 27893566 A – exonic ABHD15 CTTGTTTGCAAGC

CGTCGGC

GTGTCGGAAGCGGA

TGTATG

rs201971667

MC7 9 13375387

4

13375387

4

T – exonic ABL1 TGCACAGTTGAAT

TTCCTGG

GCCTGGTAAAATGT

CAGAGC

MC7 2 21105754

2

21105754

2

C – exonic ACADL TGGTTTTGAAGCA

CCTCATG

CTCCAACCTGGGTG

ACAGAG

HA175 8 39138654 . G T Intronic ADAM32 GATCTCCTGACCTT

GTGATC

GACTTTATCGATTGT

GGCTG

MC1 21 45712875 45712875 G C intronic AIRE CTTTCCCACTCAGT

GTGGAC

CTCTCCTCCTGTTTC

AGGTG

HA212 19 17397498 17397501 TGTT – exonic ANKLE1 GTTTGAATGTTCC

AGCTGCC

CTTCTGCTTCCCTTCT

TGTC

MC2 19 17397501 17397501 – TG exonic ANKLE1 CTTGTCTTCCTGGC

TGAAGG

GTGGAGTTGCCCAG

GTTCAAAC

MC3 16 28509193 28509193 G – exonic APOBR GTAGAGGCCGAG

GAATCTGC

CCGGAGTCCGACGA

AAAGAG

HA216 2 69046383 69046383 C T exonic ARHGAP2

5

CATAATCTCCAACT

CCAAGC

CACTGCATCACCTAA

AACTC

MC3 19 7504927 7504970 GGCATAAAA

ACGGCGCAG

CCCAGCCTG

GCGCCGCGC

CGGGTCCC

– exonic ARHGEF18 CATCATGTGCGAG

GTTTTGG

GCTCGTTATCCAAGA

AGACG

MC3 10 63852660 63852660 G – exonic ARID5B CTCGCTTGTGATG

CAAAGAG

CGTGCGAAGTGAAT

GATCTG

HA175 7 12326485

6

CTAAT C exonic ASB15 CTGTGTCAAGCGA

TGGTCAG

CAGCAGAGGAAGA

GGAGCTC

rs778460253

MC2 10 73921295 73921295 C T intronic ASCC1 CAGGATCATGGGG

TTGACAG

GGGCTCCATCAAAT

CACATG

HA214 19 57746411 57746411 C G exonic AURKC CTTGCCGCCAGAA

ATGATTG

GCTGTTCTGGACCA

CAGAAG

HA150 19 831815 GT G exonic AZU1 GTCCACTAGCAGT

TAACCAG

CATTCACTGTGTGAC

CTCTG

rs372854624

HA210 19 831815 GT G exonic AZU1 GTCCACTAGCAGT

TAACCAG

CATTCACTGTGTGAC

CTCTG

rs372854624

MC6 21 11098723 11098723 T C intronic BAGE CTTCTCCTAGATCT

CTAGCC

GCTTAGAGGACCAG

GAGAAG

HA175 15 52404514 . T TC exonic BCL2L10 GTCCTTTTTCTCCG

CCTACC

GACTTCACAGCGAA

CGTTCC

HA195 3 13316735

8

13316735

8

A T exonic BFSP2 GGAAGCCAGGTTA

TCAGAAG

GTGAACTTCTGGTCT

TGTGG

MC2 8 22479005 22479005 – C exonic BIN3 CCTTTTGGTTCAGT

CTCAGC

CAAGGATGAATGAG

GCTGAC

HA213 20 31647696 31647696 G T intronic BPIFB3 CTGGATCCTATGC

CATTGCC

GGTGCGAGATGATC

CTGAGC

rs11697151

HA173 5 18047725

3

AC A exonic BTNL9 CTGCAAATGCTGA

ACAGTGG

CACTGACCTGCTATC

TGGAC

rs367635312

HA216 10 33018277 33018277 A – exonic C10orf68 CGTCAGTGTGTAC

TTCAGAC

CGTTTGAGATTCGCT

TCTTG

HA210 10 33017896 33017899 AAAT – exonic C10orf68*

*

CGTCAGTGTGTAC

TTCAGAC

CGTTTGAGATTCGCT

TCTTG

HA210 10 33017896 33017899 AAAT – exonic C10orf68*

*

GTGTCAGATCTAG

CATTATG

CGTTTGAGATTCGCT

TCTTG

rs202220321

HA216 10 33018277 33018277 A – exonic C10orf68*

*

GTGTCAGATCTAG

CATTATG

CGTTTGAGATTCGCT

TCTTG

MC1 10 33017896 33017899 AAAT – exonic C10orf68*

*

GTGTCAGATCTAG

CATTATG

CGTTTGAGATTCGCT

TCTTG

rs202220321

MC1 10 33017896 33017899 AAAT – exonic C10orf68*

*

CGTCAGTGTGTAC

TTCAGAC

CGTTTGAGATTCGCT

TCTTG

rs202220321

HA214 17 71238446 71238446 C – exonic C17orf80 CGGTAAACAATGA

CAGTGAC

GAGGAGGCTAATAC

AACTGG

HA212 1 75065474 75065475 CT – exonic C1orf173 CAGTTCACTCTCA

GAGCATC

GTAGATGAGGAGAA

ACAAGG

HA210 5 41150035 41150035 A G intronic C6 AGAATCCATGCTG

TGCACTG

CAGCAGAGCACAGG

AATATC

HA195 1 57406638 57406638 G A exonic C8B CATCTCTCAGACA

AGTTCAG

GCAGCGTTGTGTAC

CTTAAC

HA211 12 12167832

7

CT C,CTTTT

,CTTT

exonic CAMKK2 GTTTTCTGTTCGGT

GAGCAG

GAGTTTTCTGCTCGC

CTTTC

rs761569371

215

MC10 12 12167832

7

12167832

7

– TT exonic CAMKK2 GTTTTCTGTTCGGT

GAGCAG

GAGTTTTCTGCTCGC

CTTTC

MC3 12 12167832

8

12167832

8

T – exonic CAMKK2 GTTTTCTGTTCGGT

GAGCAG

GAGTTTTCTGCTCGC

CTTTC

HA211 12 12167834

6

C T intronic CAMKK2 GTTTTCTGTTCGGT

GAGCAG

GAGTTTTCTGCTCGC

CTTTC

rs770833088

MC6 11 10487804

0

10487804

0

– T exonic CASP5* CATTATTCCCAATG

CCACAG

GTCAGAACATCGTG

TTTTGC

HA210 7 31697913 31697913 – T exonic CCDC129 GCATAGGCCATGT

AGATTTG

GTGTTATACTCTGGA

AACTG

HA223 7 31697913 31697913 – T exonic CCDC129 GCATAGGCCATGT

AGATTTG

GTGTTATACTCTGGA

AACTG

rs35589779

HA215 2 19752146

9

19752147

0

TG – exonic CCDC150 GCTATTTGGAAGC

TCCAGAC

GCTTCAGGTCCTTAG

AATGC

rs143904259

HA216 2 19754090

0

19754090

0

G T exonic CCDC150 CAGTTACTCCAAA

TGACACC

CTAGTTTCTTGAGG

GCAGAG

HA224 2 19752146

9

19752147

0

TG – exonic CCDC150 GCTATTTGGAAGC

TCCAGAC

GCTTCAGGTCCTTAG

AATGC

rs143904259

HA173 3 56655621 A AAGAG exonic CCDC66 CAAATGAGGTGGT

CTAGTAC

GGTGACAGAGCAGA

AGAACC

rs570037412

MC1 3 56655621 56655621 – AGAG exonic CCDC66 CAAATGAGGTGGT

CTAGTAC

GGTGACAGAGCAGA

AGAACC

HA215 12 549867 549867 C T exonic CCDC77 GTCCCTTTGACTTG

TAGTCC

GGAAGGCATTTACG

AAGGTG

HA216 7 75401263 75401263 C T exonic CCL26 GAACTGCCACACG

TACGTAG

CCCATCCTGTTGCAT

GACTG

rs41463245

HA223 7 80303461 80303464 TAAG – exonic CD36 CTTGATTACAGAC

TGGGACC

CAGTGGCTAGACAT

GTCTAG

rs56293647

HA173 4 76521525 C T Intronic CDKL2 CTGCTTGTTAGTTG

GTGCTG

AAGTCTAGAGCTGA

CTGGTG

rs56229013

HA214 4 76521525 76521525 C T intronic CDKL2 CTGCTTGTTAGTTG

GTGCTG

AAGTCTAGAGCTGA

CTGGTG

rs56229013

HA225 4 76521525 76521525 C T intronic CDKL2 CTGCTTGTTAGTTG

GTGCTG

AAGTCTAGAGCTGA

CTGGTG

rs56229013

MC1 12 51740415 51740415 – AG exonic CELA1 GATGATTAATTCA

GCCCTGG

CCTTTTCTATCTTGG

CCTCC

MC3 12 51740408 51740411 ATAA – exonic CELA1 GATGATTAATTCA

GCCCTGG

CCTTTTCTATCTTGG

CCTCC

MC3 12 51740416 51740416 – G exonic CELA1 GATGATTAATTCA

GCCCTGG

CCTTTTCTATCTTGG

CCTCC

MC10 9 80881357 80881357 G C intronic CEP78 GACCTACTCCTGG

CTATAGC

GGACTCCTAGGTTG

TTGCTG

HA150 16 23768875 23768875 C T exonic CHP2 GACAGACTTGGGA

AACGTTC

GCTGAGCTAGACTT

TAGTAC

rs61731149

HA195 16 23768875 23768875 C T exonic CHP2 GACAGACTTGGGA

AACGTTC

GCTGAGCTAGACTT

TAGTAC

rs61731149

HA216 12 12019005

4

12019005

4

– GA intronic CIT GAGAAGGTGGTTC

CAAGACC

CTTCAGCTTCTGCTG

TGGTC

rs141931278

HA212 1 86894223 86894227 TAACT – exonic CLCA2 CATACACCCTACA

ATACAGAG

CAGGTTTTGTGAGT

GAGTCC

HA212 1 86894223 86894227 TAACT – exonic CLCA2** CCATACACCCTACA

ATACAG

CTGCTGCCACAGTTT

TCTTC

MC2 7 14162994

9

14162994

9

T – exonic CLEC5A CCTGCAAGACTCT

CACTCTG

GCAAGGACCGCTAC

TGGTAG

HA223 22 19171074 19171074 – T exonic CLTCL1 CATCTCCGTTTCAC

CAGTGG

GTCATAGCAGGTGA

AGAGAC

MC4 22 19189003 19189003 – C exonic CLTCL1 CTTACCACCCTAGC

AAACAG

CACTGCTGCCTGATA

CTCAC

HA175 1 22454474

6 G A intronic CNIH4 CTCTCTCCTCGATT

GTTGCG

GAAAAACAGCGACG

CTTCTC

rs56105022

MC2 3 13018766

2

13018766

2

G T exonic COL6A5 CCTCATGCTGTGT

ATTTGCC

CAACCCTGTCTCCTA

AGGTG

rs115375867

HA223 4 83970472 83970472 – A intronic COPS4 GCACACATCTTCCT

AACTTG

GCAAATGTCAGTTG

GAGTTG

HA175 3 9976205 . G A intronic CRELD1 CTTGTAATAACGC

AGATCCC

GAGTTCCCCACTCTA

AATCG

HA225 4 1388594 1388622 CACGTGCCCA

TGTGGAGTG

CCCGCCTGCT

– exonic CRIPAK CTGCTCACACATG

TCGATGC

GCAGGCGAACACTC

CACATG

MC4 4 1388350 1388350 – TGCCC

ATGTG

GAGTG

CCCGC

CTGCTC

ACACA

exonic CRIPAK GGCATCTCGTTCCT

CAGATC

CCACATGGGCACAT

GAGCAG

HA214 20 20033322 20033322 G A exonic CRNKL1 GGGAATGGTAGTT

TCCTCGC

CTTTGACCTCTCGCT

TGAGC

rs74404969

MC7 22 37333973 37333973 C – exonic CSF2RB AACAGGCTTCCAG

CTTTGAC

GCTCCACATAGCCCT

CAAAC

MC4 11 65647351 65647358 GCCTCCTG – exonic CTSW CAGGGACTGAAA

GCCTGAAG

CATAGGTAAGGGTT

TGGGAG

MC4 11 65647351 65647358 GCCTCCTG – exonic CTSW** GAATTGCTTGAAC GTTAGCCTTTTCTGT

216

CCGGGAG CTTCCC

MC4 11 65647351 65647358 GCCTCCTG – exonic CTSW** CAGGGACTGAAAG

CCTGAAG

CATAGGTAAGGGTT

TGGGAG

HA213 6 16869481

7

16869481

7

G C exonic DACT2 CTCTGTGTCCTCAC

ACCTAG

CGTCTGCTACTGCTC

TTTGC

HA213 1 32674742 32674742 – G exonic DCDC2B GATAAATGCTCCT

GCCACAG

GGCCATGACAAGGT

GTGTAG

rs200086869

HA173 20 168625 G GT exonic DEFB128 CTCTTCTGCTCTTC

CTTACG

GATGTAATCCTGCA

GCACAC

rs11396059

HA213 20 239946 239946 A C exonic DEFB132 GACTTCTCTGTCTT

GTCCTC

CAGCAATGTAGGAG

GAATTG

rs147196160

HA213 2 19675980

8

19675980

8

– T exonic DNAH7 GCGTATGTGAACT

ATTCCTC

GTCGAAAGCAAGTT

TGTGGC

MC3 6 38818191 38818191 G A intronic DNAH8 CAGCCTGAGACTA

ATAGAGG

CAAAGGTGTCTTCCT

CACAG

MC2 11 6550231 6550231 – A exonic DNHD1 CCATTATAGCCGC

ATGCCTC

GAAGAGAAGCAGTA

CTCACC

HA215 11 6560532 6560532 C T exonic DNHD1 GTGCTCTAGACCT

TGAGTTC

GGAGTCTGGAATCA

CACAAG

HA215 11 6588977 6588977 A – exonic DNHD1 GTCACTGTCATCC

ACAGTGC

GTGGCCAAGAAACT

AGGTTC

HA214 2 25467083 25467083 G A exonic DNMT3A CCAGGTGCTTTTG

CGTGGAG

TCACAAATTCCTGGT

CGTGG

HA175 1 97915614 C T intronic DPYD CATCAGTGAGAAA

ACGGCTG

GCATCAGCAAAGCA

ACTGGC

rs3918290

HA224 1 97915614 C T intronic DPYD CATCAGTGAGAAA

ACGGCTG

GCATCAGCAAAGCA

ACTGGC

rs3918290

HA210 18 29055783 29055783 A T exonic DSG3 GATAATGAAGGCG

CAGATGC

CAAAGCAGAAGCTC

CTTGAC

HA195 17 45438788 45438788 C T exonic EFCAB13 CCTTAGTAGGCTA

TTGACAC

GGAGAAGCAAAGG

ACAGATC

HA150 6 32134398 32134398 G T intronic EGFL8 GCTCCAAGCAGAC

ACTGGTG

GAAGACCCAGCCTC

ACCTTC

HA175 2 63175824 . GACACAGA G exonic EHBP1 GGTTGGAGAGTCA

GAAAGTG

CTGTGCTTGGGTTG

AATCTG

HA175 2 63175824 . GACACAGA G exonic EHBP1** CTATGCAGAGCTT

AGTGATC

GTGGAGACATATCC

TTCTTC

HA150 1 32696768 32696768 C T exonic EIF3I CAACAGTGTTGCC

TTCCATC

CTGGTCTTAAACTCC

TGACC

HA175 16 1823389 CG C exonic EME2 GACCTCCAACCTG

GGAGATC

CTGGCGGAGAAAGG

CCTTTC

rs377074694

MC3 11 726303 726303 G A intronic EPS8L2* AGGCCGGTCAGAA

GTACTGG

GCATGGTGAGCTGG

CTGTAC

MC3 11 726303 726303 G A intronic EPS8L2** AGGCCGGTCAGAA

GTACTGG

GCCGCACACTTTCTT

CAGCT

MC3 11 726303 726303 G A intronic EPS8L2** GGAACAAAGACG

GTGAGAGG

CCTCGCCGCACACTT

TCTTC

MC3 11 726303 726303 G A intronic EPS8L2** GCTTCCCGGGGAA

CAAAGAC

CACACTTTCTTCAGC

TCCTC

HA195 9 14024269

2

14024269

2

T C intronic EXD3 AAAACAGAGACA

GAGTGCTGG

CTTCACCATTGCCCA

GCATG

HA211 1 40981245 C CG exonic EXO5 GTCTCTAACACTGT

CAGACC

CAACAGGAGCAGGA

AGGATC

rs150018949

MC4 9 96259883 96259883 – A intronic FAM120A CACCTTGCGACGT

AGTGATC

GAACATGACCAGGC

TACCTC

HA210 X 13398814

5

13398814

5

A – exonic FAM122C CATGTGTAGACAA

AGCAGAG

CACAGGAGAGTTTG

TGACAG

MC10 X 13398814

5

13398814

5

A – exonic FAM122C CATGTGTAGACAA

AGCAGAG

CACAGGAGAGTTTG

TGACAG

HA225 7 286468 286468 – GACAG

GTGAG

CCCTTC

CTTCCT

CCCTCC

ATCCG

C

exonic FAM20C GGCTTTCTCAGTG

ACAAACC

GTGACAGAGGGATG

ATTAGG

HA150 8 12419535

2

12419535

2

G T exonic FAM83A GCTGACTTTAGTG

ACAACGAG

GACGGTCTGGAAGT

ACACAG

rs148011353

HA214 19 49104533 49104533 G A exonic FAM83E CTCCACAGCTCAA

GAAATCC

CTCTGGGCTCTTGAA

GTTTG

MC7 2 58386928 58386928 – TAAT exonic FANCL TCGCATCATCATAC

CTGTCC

TCCTAGGTGATCTG

AAACTTC

HA173 4 18751698

1

. C T Intronic FAT1 GAGTAAATCTCAG

GCCATCG

CCATTGTCATCGCAC

GATTC

MC4 4 18752435

0

18752435

7

GCCCTGTG – exonic FAT1 CTTCCGTGACTGA

CATTGAG

CCATCAAAGGCTTCA

AAGGC

HA225 1 16703297

6

16703297

6

T C intronic GPA33 GCCATATTGGGGT

GAATTGG

GCATGTGTTGCACTT

TGACG

HA173 7 23313823 G T exonic GPNMB GAATGTGGTCAGA

AGCAAAG

GTTAATAGCCACTCC

AGCAC

rs11537976

MC10 17 72366664 72366664 C – exonic GPR142 GGTGGTCTTGGCA

AGAATTC

GACAATGGCAAGGA

AAGACC

217

MC6 5 17602613

6

17602614

6

CCTCCTTCCT

C

– exonic GPRIN1 CACTTCCATAGGA

AAGGAGG

CCGACAATACAAGA

TCTACC

MC7 5 17602612

2

17602613

4

CAAAGACCC

AGGA

– exonic GPRIN1 CACTTCCATAGGA

AAGGAGG

CCGACAATACAAGA

TCTACC

HA223 1 24649608 24649608 G C intronic GRHL3 GACATTGTGTCGA

GTGCTTG

GATGATGATGATGG

TCCACG

HA224 2 14470962

2

14470962

2

– TAGAA

TACAG

ATATTC

AGCTG

CAGGA

AAA

exonic GTDC1 GTTGTACGGGTAC

ATAAGGC

CCTAGGTTAATACAA

CTGGC

MC7 5 15648244

2

15648244

2

– CT exonic HAVCR1** GTTTTGCCATGTTG

GCTAGG

CTATGGTCAAAGAG

ACATCC

MC7 5 15648244

2

15648244

2

– CT exonic HAVCR1 GTTCTTGGATTAC

AGGCGTG

GCTTATAGCGTGTG

TCCTTC

HA212 12 66704274 66704274 G – exonic HELB GTGAAGTTCAGCT

GGATCAG

CAGTGTGTAGGCAT

GAAGAC

rs199672632

MC1 15 28518115 28518115 C – exonic HERC2 GTGATTGTAAGCA

TGCTGTC

CAGTGAAACACACA

CAATGC

MC1 3 10807687

5

10807687

5

G A exonic HHLA2 CTGTCCTGGCTTAC

TATCTG

CTACATGCACTGTGT

GGATG

rs41267017

MC2 22 30517624 30517624 – A exonic HORMAD2 CCATCGCTCCCCTA

ATTTAC

GCACTTAAGGAGGA

ATTTGC

MC1 1 15219572

9

15219572

9

T – exonic HRNR CTACATGGCTTGA

ACAAGTC

GTATCATACTCCCCA

TGCTG

rs34061715

HA223 19 16268208 16268208 A – intronic HSH2D CTCCAATTTCTGG

GACAGAC

GTGATCTTGGCTGC

CTTTTC

MC1 16 70896016 70896016 A – exonic HYDIN CTGCCTCTCACTGC

AAATGC

GGGGATAAGAGCCA

CAGAGC

rs77276171

HA175 1 79101171 T A exonic IFI44L GTCTTGAATGCTG

GGTGATG

GCAAATGAGTAGAA

TCCTGC

rs115901054

HA212 14 36004018 36004018 – CCTTCA

GAGTC

TGAAG

CGG

exonic INSM2** GCAGTTTCTGCTG

CCGCTTC

CTTTGGCTTCTTGAT

TCCCG

HA211 9 95411816 . G GT exonic IPPK CTGTGTGTGTCCC

ACAATCC

CACGTGACTCTTGG

ACTTAC

HA195 3 10242051 10242051 A G intronic IRAK2 GCAACACCATGCA

TTTGTGG

CCTTTCTTACAGAAG

CTGCC

rs140903779

HA210 16 31418867 31418867 C T exonic ITGAD CTCTCCAGATGAG

AGGACTG

GATAGCGTAGCGGA

TGATGC

rs147321998

HA215 8 13315023

3

13315023

3

T – exonic KCNQ3 GAAGTTCTTCCAG

CAAGCTC

CTAGACATCCACAA

GGCTTC

HA212 3 10827860

4

10827860

5

CT – exonic KIAA1524 GGAAACAAAAGCT

CTAGCCC

GAGGCATGTCAAAT

GCTAAGG

HA175 20 16410518 . TATAAG T exonic KIF16B CCCATTCTGACAAT

CTGAAG

GTTCCTTACCTCCCT

CTTAC

MC10 5 15439561

3

15439561

3

C T exonic KIF4B CAATCCAGTGTGC

TCAGACG

GAGTTGAACCACAT

CCTGAG

HA214 6 39387723 39387723 C T intronic KIF6 CAGCACAGAAACC

TTACAGC

CTCTCAAAGCAGCTT

CCTTG

rs371798783

HA214 19 55331298 55331298 G – exonic KIR3DL1 GAAAAGACACGG

AGATGCAG

CAGAACCGTAGCAT

CTGTAG

MC3 19 55331298 55331298 G – exonic KIR3DL1** CTCTTTCTAGGAA

ACCACAG

CAATGTCTAGACACT

CTCAC

MC3 19 55331298 55331298 G – exonic KIR3DL1 GAAAAGACACGG

AGATGCAG

CAGAACCGTAGCAT

CTGTAG

MC6 19 55341708 55341708 C – exonic KIR3DL1** CTCACTCAGCATTT

CCCTCC

GAGAGGCACCAGAT

TTGTGG

MC2 7 15194507

1

15194507

1

– T exonic KMT2C CAGACTTGCCTTC

GCATGAC

CACCCTACCTGTTTG

GACCG

rs150073007

HA216 12 52681822 52681822 A T exonic KRT81 GATCCTCATTCTCC

AGTCGC

CTGACACGTCTAGC

AGGCAG

rs138597671

HA150 12 52711747 52711747 C A exonic KRT83 GGCACTTCATTTCT

CCAGTG

GCTTCACTCACCTTC

TTTAG

rs146753414

MC1 21 45959556 45959556 – TG exonic KRTAP10–1**

CTGGCAGCATGAA

GTGGAAG

GGATTCCTCTTCATG

CTGCC

MC6 11 1651595 1651598 GTCC – exonic KRTAP5–5 CCAAGAGAGGCTG

TGTCTCC

GTTCAGGAGAAGTA

GTAGGC

HA225 11 1651600 1651625 GCTGCTGTAA

GCCTTACTGC

TGCCAG

– exonic KRTAP5–5*

CCAAGAGAGGCTG

TGTCTCC

GTTCAGGAGAAGTA

GTAGGC

HA225 11 1651600 1651625 GCTGCTGTA

AGCCTTACTG

CTGCCAG

– exonic KRTAP5–5**

TGTTCCTGCTCCAG

CTGTGG

CTCAGATCTTACACT

GGCAG

MC6 11 1651595 1651598 GTCC – exonic KRTAP5–5**

TGTTCCTGCTCCAG

CTGTGG

CTCAGATCTTACACT

GGCAG

HA214 1 62676248 62676251 AACT – exonic L1TD1 GTCACTAGAGATG

AGTCATG

CAAGACACCTGAAT

GGGAAC

rs202029696

HA211 11 71807767 A C Intronic LAMTOR1 GACAAGGTTTCGC

CATGTTG

GTGATGATGGGAAC

ACTGTC

218

HA211 11 71807767 A C Intronic LAMTOR1

**

CACTGGAGACGTG

GGAAAAC

GCTGAACAGACCTG

AATCTG

HA225 8 98788165 98788165 – GGCGG

GCTCC

AGGCG

A

exonic LAPTM4B CTGATGGATTTAC

TCACCGG

CACCCGGAGAATTA

AGTTTC

HA225 8 98788165 98788165 – GGCGG

GCTCCA

GGCGA

exonic LAPTM4B*

*

GCACGCTGATGGA

TTTACTC

CAACTTTAGGCGGA

TGAGCG

MC7 1 20374359

4

20374359

4

C – exonic LAX1 GACAGGGTTGGAT

CTCAGTG

GTCCTCACTCTGTGT

GAATG

MC7 1 20374359

4

20374359

4

C – exonic LAX1** TCATAGTCTCTGCA

GCACTG

CACTGGAGTCCTCAT

TTGAC

MC7 7 2552881 2552881 – GATG exonic LFNG GCATGGAGCAAAT

GCTCAGG

CAAAGGATATTCCA

GGCTGC

rs34637446

HA213 19 55107223 G T exonic LILRA1 GAAGCCATCACTC

TCAGTGC

GTTGTATGCACCGG

AGCATC

rs150508449

HA210 17 61775990 61775990 G C exonic LIMD2 CGTTGTTTGGCTTC

TGCAGC

GAAGGTTACAGAGG

CCTCAG

MC7 4 14137265

6

14137265

6

G A exonic LOC15258

6

GCACAACTGGGAA

CAGTAAG

CCAACTCCTTTGCTC

TATTC

rs62346874

MC3 15 31521506 31521507 GG – exonic LOC28371

0

CTATGAAGTGGCC

GGCAGTC

GCTCCTTGGGTCAG

GGTCTA

rs3835087

MC6 15 31521507 31521507 G – exonic LOC28371

0

CTATGAAGTGGCC

GGCAGTC

GCTCCTTGGGTCAG

GGTCTA

rs3835087

MC7 15 31521506 31521506 G – exonic LOC28371

0

CTATGAAGTGGCC

GGCAGTC

GCTCCTTGGGTCAG

GGTCTA

rs3835087

MC3 15 31521506 31521507 GG – exonic LOC28371

0**

TCTGAGGCCATTG

AGACCATG

GACCTGCAGACATTT

CTGCAG

rs3835087

MC3 19 19735379 19735379 C T intronic LPAR2 GGCTGTGGATTTG

TTGCTTG

GAATCAGGGAAACA

AGCAGC

MC3 19 19735379 19735379 C T intronic LPAR2** GGAAGTACTTTTCT

ACAGCC

GCCACTGTGTACCA

ATTAGC

MC7 3 18847802

4

18847807

4

CATTCTATGC

TGTGGAAAA

GAAAGCATA

CTGCGAGCC

CTGCTACATT

GTAA

– exonic LPP GAAAACGTAGTTG

GGGAAGG

GCTTATGAATGGGG

GATGTG

MC6 14 60448779 60448779 G A ncRNA

intronic

LRRC9 CAGCAACTGATTT

TGCAATG

CGCTTTAGGTAGCA

TTGTAC

HA214 8 86057746 86057746 A G exonic LRRCC1 CATGTCGATTTAG

GTCCATC

GTGGAGATGGCTAC

ATATAC

rs200010501

HA173 21 30318610 CTAAAG C Intronic LTN1 GTTTGGAGACAGG

GTCTCTG

GGGGATGAGCAGTA

TTTCAG

rs373358802

MC10 3 47917305 47917305 – T exonic MAP4 CTTGTCTGTTTGAT

GTTGCC

GTCTATCTGACACTC

AGAGG

MC10 3 47917305 47917305 – T exonic MAP4** GTTGCATCTATCCT

CATTGC

CTTACCTTTGGCTTC

ACGTC

MC10 3 47917305 47917305 – T exonic MAP4** CAGTTCACTCTCAG

AGCATC

GTAGATGAGGAGAA

ACAAGG

HA215 X 20069020 20069020 G A exonic MAP7D2 CAAAGCCAGCAAA

TAGGAAGC

CATGTTCTGCCACCC

AAAAG

HA214 4 87023187 87023187 – AGA intronic MAPK10 GAGAGGAAGTGA

TTCCCTAG

GAATGGAGGTGCTT

AATGCC

MC4 18 32558480 32558483 GAAT – exonic MAPRE2 CTACCAATCACTC

GGTGAGC

GTTGCGATTGTGGT

CAGACG

HA210 3 19251707

7

19251707

7

– A exonic MB21D2 CCCAAAAGTGGTT

CTCCATG

GTAATCAGCCTGTG

ACACTC

HA175 16 21611081 . C A exonic METTL9 AGTGCTCCGGATG

GAAACTG

CGCTAGTCATGTTCA

CGTAC

HA175 16 21611081 . C A exonic METTL9** CCTCCGCCATTTAC

TAGAGG

GTACCTGGTGGTTCT

CCTTC

HA215 2 22819449

8

22819449

8

– G exonic MFF CCTAAGCCATGTT

CAAATCC

AAAGAGCATGGTTA

GCCTAC

HA214 15 42000407 42000407 G A intronic MGA CCATAATATTGGC

CTGCTAG

CAAGAGCAAAACTC

AGTCTC

HA175 5 17922285

8

G A Intronic MGAT4B GGGTGAACTGCAG

CGAGTAC

GCGAGGAGGCCCGC

TTCTTC

HA224 6 31380161 31380161 – CT exonic,

intronic

MICA GAACACAGCGGG

AATCACAG

GAAGCCTTGTCACC

AACATG

MC3 6 31380158 31380161 GCTG – exonic MICA GAACACAGCGGG

AATCACAG

GAAGCCTTGTCACC

AACATG

rs138201170

HA173 11 12270793 GGT G Intronic MICAL2 CTGCAATGTCCTA

ACCTATG

CCAGTACAAGCACA

TGTCTG

rs146412715

HA214 11 12270794 12270795 GT – intronic MICAL2 CTGCAATGTCCTA

ACCTATG

CCAGTACAAGCACA

TGTCTG

rs146412715

MC3 11 12270794 12270795 GT – intronic MICAL2 CTGCAATGTCCTA

ACCTATG

CCAGTACAAGCACA

TGTCTG

rs146412715

HA212 6 31473525 31473525 C – exonic MICB CACCCTCACAGTTT

TCCTTG

CTTGTAATGAGTCA

GGGTCC

rs45459705

HA150 10 21845667 21845667 C A exonic MLLT10 TTGCAGTTTTCTAG GACCACATCAGAAA

219

GGCAGG CACAAG

HA224 11 10264948

2

10264948

2

T C intronic MMP10 CAGCAGACACCAA

CATTCAG

CACCTGATGCATCTT

CTGTC

rs17860955

MC1 10 88703604 88703604 C – exonic MMRN2 CAATTTGGTGTCC

ACATCGG

CTACAAGTGCATTTC

AGCCC

HA173 10 99229890 . GTC G exonic MMS19 CTTGATGTGACTG

ACACACC

GTCAGCCTTTCCTCA

GTTAC

MC7 18 48331612 48331613 AG – exonic MRO* CAGTTCCTGTGCTA

TTACTG

GCTGAGATTACAGG

CATGAG

HA216 18 48331612 48331613 AG – exonic MRO* CAGTTCCTGTGCTA

TTACTG

GCTGAGATTACAGG

CATGAG

HA213 5 41017978 41017979 GA – exonic MROH2B GCTGAACTATAGA

GGGAAGG

CATCCTGGGATATG

ACCAAG

MC3 5 41064591 41064598 TTCATCCT – exonic MROH2B* CTGCAATGTCCTA

ACCTATG

GATAACTCCCTGCTG

AGGAC

HA213 5 41017978 41017979 GA – exonic MROH2B*

*

CATCACAATAGGA

TGCCTCC

GAGGAGGACAGAA

GAAGATG

HA175 8 16035502 C T Intronic MSR1 GATGACGAGTTTG

TGGGTGC

GCTGTCATTGAGCG

AGCATC

rs33912200

MC10 1 17083816 17083816 G A exonic MST1L* GCAGGCTAGTCAT

TGCTGTG

CCCAGTCTCATGACC

TTGTG

rs11260920

MC2 1 17087542 17087546 GTGCT – exonic MST1L* GCTAGACTGGCCC

TTGAAAG

GGCTGCTCACATTGT

AGTGG

rs113982165

HA150 17 72768101 72768101 G A exonic NAT9 CGGTAAGAAAGTG

TGAGCAG

CTCTGTAAGGCTTCT

CTTCC

HA213 2 15235793

7

15235793

7

G A exonic NEB GTGGCTTCAAGTC

CAGTATC

GATGGGTCCAGGTT

GATTTG

MC10 15 75641682 75641682 T C intronic NEIL1* CAGTTTGTGAATG

AGGCCTG

CACTAAGAGAGTCA

GGTGTG

rs5745908

HA213 3 52780827 52780827 G A exonic NEK4 GTACCAGGTTGCT

GCTATAC

CCTTACTCTGCTTCG

AACTC

rs201029132

HA215 16 3599227 3599227 – G intronic NLRC3 GCCCAGACTATGC

AGAACTC

CATGGCATGAACAG

CCTGTG

HA173 19 56423924 TGAAA T exonic NLRP13 CAGTGACCAAAAT

CCTACAC

GAGTGATTGACTGG

AGATCG

rs147101216

HA195 16 450140 450140 – AG exonic NME4 CATGACAGCTCAC

ACTGGTG

GTAAGTGGTTTGGG

ACAGGC


ACTGGTG

GTAAGTGGTTTGGG

ACAGGC


ACTGGTG

GTAAGTGGTTTGGG

ACAGGC

rs35963490

HA150 9 95064094 95064094 G A exonic NOL8 GAGAAAACTGAG

GCCTAGTG

CCTGGATTTCCTCAG

GTTTC

MC7 1 12061200

3

12061200

4

GG – exonic NOTCH2 GGAGTTTCTGAGA

CTTGCTG

CACACCCGAGAAAG

TTTCAG

MC10 9 14032555

4

14032555

4

T G intronic NOXA1 CATCCCTGTGTAA

GACCTGG

CTTGGGGAGTCCAT

GATTAG

rs148308245

MC7 11 10804058

0

10804058

0

C T intronic NPAT GTAGGGATGATCC

CAGTATC

CTTAGTCCCTGAGCC

TTCTG

MC3 7 15104243

3

15104243

3

G A intronic NUB1 GACAGAGGAAGG

GAGCTTTG

GGTCATGCCTGACA

ATTCAG

MC1 15 41663884 41663884 – A intronic NUSAP1* GAAAGTCTGCACA

TGTGACC

CTGGGTGACAAAAG

CGAAAC

HA212 12 11338465

9

11338465

9

G T exonic OAS3 CACTTGTTCTTGGA

ACAGGC

GCTATTAGGAAGTA

CCTGGG

HA223 12 11340367

5

11340367

5

C T exonic OAS3 CTAACTCACAGTC

CAGAACC

GGGCCCTCTTCTTTA

GATAC

rs61942233

HA213 13 25671814 25671814 C – exonic PABPC3 GTGCCAGACCTCA

TCCATTC

GCTGTGCATTACGA

TGTTGC

HA215 5 14079520

8

14079520

8

– A exonic PCDHGA1

0

GCATTCAGAGGAA

CAGCTAG

GGAAAAGCAAGCTA

CTCTGC

MC3 5 14081139

5

14081139

5

C – exonic PCDHGA1

2

CTACCAGATGGAA

GTGCAAG

GGTCACTGTGATGT

TGTAGC

MC7 9 5522576 5522576 G – exonic PDCD1LG2 CCTATAACTTCTCC

TCCCAG

AGCCCAGAAATCAT

ACGTCC

HA223 1 14492372

9

14492372

9

T – exonic PDE4DIP CCAAAGCACTGGC

ATTACAG

CCATGACTGAAGAG

TTGCTG

HA175 12 18715827 G A Intronic PIK3C2G CACACACTTGCAC

AAATGTC

CCTCTTAATGACACT

TCTGC

rs187352063

HA195 19 30102847 30102847 G T intronic POP4 CATCCCAAGCTCA

TGTTGTC

CTTGGCCTGAATCAT

CTGTG

HA211 8 12842818

0

G A exonic POU5F1B CATACGGTCACAG

AGCTTTC

CACATCGGCCTGTG

TATATC

rs531267041

HA195 11 61254687 61254687 C T exonic PPP1R32 GACTTGACAATTC

CCCTGTC

CTTATCCCAGTCTCA

GTCTG

rs144191864

HA150 7 11351916

1

11351916

2

CT – exonic PPP1R3A GAGAAGACAGTTC

ACAGCAC

GCAATCACAGCAGA

TGTGTC

HA210 9 15465556 15465557 TC – exonic PSIP1 CAACCATGTCTGG

AAAAGCAG

GTCCATGACACTTTG

CTGAG

MC6 6 31106500 31106500 – C exonic PSORS1C1

*

GTTCACTTGACCCA

CTTTAAACTG

CCAGAAATGGCTTTC

TGGAC

rs138474986

220

HA214 6 31106501 31106501 – C exonic PSORS1C1

*

GATGGATCTGAAC

CGTTCAC

CCAGAAATGGCTTTC

TGGAC

HA175 6 31106507 . C CG exonic PSORS1C1

*

GATGGATCTGAAC

CGTTCAC

CCAGAAATGGCTTTC

TGGAC

MC6 6 31106500 31106500 – C exonic PSORS1C1

**

GATGGATCTGAAC

CGTTCAC

CCAGAAATGGCTTTC

TGGAC

rs138474986

HA175 6 31106500 TC T exonic PSORS1C1

*

GATGGATCTGAAC

CGTTCAC

CCAGAAATGGCTTTC

TGGAC

rs373592714

HA216 1 71418662 71418662 G – exonic PTGER3 GCAGTTTGCAGAA

CTCTCAG

GACCAACCAGTTTGT

TCAGC

HA175 4 37962608 CAT C exonic PTTG2 CATGATCCTTGAT

GAGGAGG

GACAGCTGAGACAG

ATGCAC

rs200376306

HA210 4 37962609 37962610 AT – exonic PTTG2 CATGATCCTTGAT

GAGGAGG

GACAGCTGAGACAG

ATGCAC

rs200376306

HA175 5 34911900 G A exonic RAD1 GCAGAAATCAAAG

TCCAGGG

GAGGAGTGTATGAC

AACCTG

rs2308956

MC3

17 56774211 56774214 AAGG - exonic RAD51C

TGATAGAGTGGTA

GACCTTG

GTCCAGTAATTAGG

CTTCAC

MC7 19 15568282 15568295 GCGCCCGCA

GCGCT

– exonic RASAL3* ACTCCCATCTGCA

GGACAAC

CGAAGCGCGTTATC

GGTCTA

MC7 19 15568282 15568295 GCGCCCGCA

GCGCT

– exonic RASAL3* CTCAGGCCCAGTC

CTTCAAG

GAGGCTCCACGCTT

CACTTG

MC7 19 15568282 15568295 GCGCCCGCA

GCGCT

– exonic RASAL3** GTGCCAACAAACC

AAAACGC

CATTACAGGTGCAA

CTCAGG

MC3 16 24564880 24564881 TA – intronic RBBP6 GTAGGCTGAGCTA

CATTTTC

CAGCAACTACTCTTT

ACAGG

HA225 X 11929321

6

11929321

6

– G exonic RHOXF2 GAGAAGAAAAAG

ATGGCGGC

CGTTGGAAAATGCG

CTCCAG

HA213 7 10519093

4

10519093

4

G A intronic RINT1 CTGTCATTTGGTG

GATGAAG

CAAACTACTGCACTT

TAGCC

HA213 7 10519093

4

10519093

4

G A intronic RINT1** GGAGCTACACAGT

GTTCATG

CAACAGAGCAAGAG

TCTGTC

MC6 19 50140152 50140167 CCCGAACTCT

TCCTGG

– exonic RRAS GAATCTGCGTGAA

GAGCTTG

GCACTGCAGTAACT

ATCCTC

MC10 3 13390191

6

13390191

6

C T intronic RYK CAACACTGAAATG

CTGGTGG

GCATTTCTTAGGACT

GAGGC

MC10 3 13390191

6

13390191

6

C T intronic RYK** CAGTCTGTTATTGC

ATTTTC

CAAGTGTTGCCATG

CTCAAC

HA211 16 51175657 CTG C exonic SALL1 CGTTGCTGTTGATT

ACGGAG

CAGATCTTCTGCTCC

ACAAG

rs768581623

HA211 16 51175660 CTGCTGCT C exonic SALL1 CGTTGCTGTTGATT

ACGGAG

CAGATCTTCTGCTCC

ACAAG

MC7 17 26708303 26708304 GT – exonic SARM1 CACTGTCCCCTTCC

ACTTTC

CCTCCTTGGAGAAG

GCGAGC

HA225 1 87333787 87333787 T – intronic SEP15 CTCCACTACAATCA

CCTTAC

CTCTCCCTCTCTCTG

ATTTG

MC7 19 50455629 50455629 – C exonic SIGLEC11 GTGAGCCTTGCTA

AGCAGAG

CCTGCTCTGATCCTC

TTGCC

MC3 13 21729952 21729952 – A intronic SKA3* CATCTGTGTAACT

GGCTAGG

CCACTTTTTTCCAAC

TGCTG

rs11446085

MC3 13 21729952 21729952 – A intronic SKA3* TTTACCTGTTGTCC

AGCCTG

CCATGTTGGTCAGG

ATGGTC

rs11446085

MC3 13 21729952 21729952 – A intronic SKA3** CAAACTCCTGACCT

CAAGTG

GGTTCCTTAAACATG

GACAG

rs11446085

MC7 X 48769143 48769144 AC – exonic SLC35A2 GAAAAACCACTTC

CGCGTTC

CTTCCCTTATGTGCG

TCAAC

MC7 X 48769143 48769144 AC – exonic SLC35A2 CTGCCCTGACTATT

CTTACAC

GCTGGAAAAAAGAG

ATCTCC

HA195 12 21008080 21008080 – AATTG exonic SLCO1B3 CATCATGGCCATC

TGAGAAC

CCCAGCCCATTTATA

GCAAC

HA173 12 21036518 TTATC T exonic SLCO1B3 GGGAGCTATTTTG

CCTTCAC

CACACTGATTGACA

GTTGCC

rs775300015

HA175 14 62235390 GAA G exonic SNAPC1* CAGATGTACCCTT

ACAGCTG

CATCTTCAGTCCAGG

TCCAG

rs758866144

HA175 14 62235390 GAA G Exonic SNAPC1* GGCATGTGAGAG

GATACTTC

CTGAGATTACAGGT

GTGAGC

rs758866144

HA210 7 16502202 16502202 T – exonic SOSTDC1 CAGTAGTCACTGC

CTGCAAG

GCTGGGTTTGATCA

AAGCAG

MC2 17 74382047 74382048 TT – exonic SPHK1* GTTATGGATCCAG

GTTTGTG

GAAGGAGATTTCAG

CCTCAG

HA173 19 4328755 G C exonic STAP2 CACCTCAGCTCTG

ACTCCTC

CAAGAGCGAAACCC

TGTCTC

rs79657645

HA215 11 4108092 4108092 G A intronic STIM1 AGCCTTTCATCTG

GACAGTC

GGTCATGAGGGAAG

AAAGTC

rs118128831

MC7 6 15913491

1

15913491

1

G – intronic SYTL3 CGCTGAATGAAGA

AGATGCC

CTCTTCCTATGAGGA

ACCAG

rs369429053

MC1 7 38299702 38299702 C – exonic TARP CACATGAGAACTG

AAATGGC

TAGATACACTACTGC

TGCAG

HA211 7 45148836 TG T exonic TBRG4 GTAGATGCTCGTT

CCTTCTC

CAGGCTGTAATGTT

CCTGAG

rs36007488

HA195 4 10615738

4

10615738

4

– C exonic TET2 GCAACATAAGCCT

CATAAACAG

GACATTATGAGTCTC

GAACTCG

221

HA211 2 74275166 . G T exonic TET3 CTTGCGCTATTTGC

ACCTAG

GGTACTTAAGAGGT

GACTCC

HA210 8 30694326 30694326 C T exonic TEX15 CTAGATTTCCACCC

TCTCTG

CATCAGCCATTACCA

CAAGC

rs146619272

HA195 15 81624929 81624929 G T exonic TMC3 GGAAGCCTAGACA

TCTGAAC

CCGGAATTTCCAATA

CCCAC

rs150843673

HA212 15 81624929 81624929 G T exonic TMC3 GGAAGCCTAGACA

TCTGAAC

CCGGAATTTCCAATA

CCCAC

rs150843673

HA213 8 23049208 23049208 C A exonic TNFRSF10

A

GAAGATTCAGGAC

CTCTTGG

GCTGGTCTTGAACTT

CTGAC

rs144773234

HA213 8 23049208 23049208 C A exonic TNFRSF10

A**

GGATGCCTTGTAT

GCAATGC

CTGGGATTACAGGC

ATGAGC

rs144773234

HA225 1 7980985 7980985 – A intronic TNFRSF9 GTTTTGCTATGTTG

GCCACG

GGGGAATCCTGGGT

ATTATG

HA210 5 15043173

0

15043173

1

GC - exonic TNIP1 CAAGTGGCTTAGC

TCCTTAG

CTCAACCCAGAAATC

AGTGC

MC4 6 11191279

9

11191280

8

GGTAAACTTT – exonic TRAF3IP2 GCACTCAAGTTCT

GGAGGAC

CATGCTGGATACCTC

TGAGG

HA225 11 4408214 4408214 – CA exonic TRIM21 GCTTTGAGCTGGT

CAGAATC

GATGGGGAAAACTT

CAGTGC

HA195 11 89606435 89606435 C T intronic TRIM6 CCTCTAGAGTAGA

AGATGCC

CTTAATGCCCACTGA

TGAAG

MC6 22 20100166 20100166 – C exonic TRMT2A CTACCTCTGAATAT

CCTGGC

GTGTTTGCCTCCTCA

GATTC

HA214 2 17940182

7

17940182

7

C – exonic TTN GATGCCGAAAGTG

TTCTGAG

GCTCTATTGAAGAA

CTCCGC

HA216 11 62359061 62359061 G – exonic TUT1 GATTCGACATCCG

AATCCAC

CAGATAAGCATCGT

AACGCG

HA223 6 41766432 41766432 – CCCCA exonic USP49 CTTTGCCTATGATC

TCTCCG

CTAGGATTACAGGT

GTGAGC

rs201338884

HA211 6 41766432 41766432 – CCCCA exonic USP49 CTTTGCCTATGATC

TCTCCG

CTAGGATTACAGGT

GTGAGC

rs201338884

HA214 6 17001375

1

17001375

1

C – exonic WDR27 CAAAGTCTCCCTC

AACATCG

CTTCTGTAACTCTCA

GTGGC

HA216 16 706805 706805 G – exonic WDR90 CAACAGCTATACG

ACTTCAC

CTGGGCACTTACGT

GTGTTC

HA223 20 44108616 44108616 C – exonic WFDC2 GTTAATCTCCCTGT

ATCGCC

CGTTTTCTCCTGTTT

CCCAC

MC1 2 31610687 31610687 G – exonic XDH CACCTACCTGTTCT

CTTTCC

CACATAGCAGAGAC

TCAACC

MC2 4 338202 338203 TC – exonic ZNF141 GGTAGTGGAACTT

AGAACCC

GCTTCCTTCTTGACC

TTTGG

MC3 4 338197 338197 – GA exonic ZNF141 GGTAGTGGAACTT

AGAACCC

GCTTCCTTCTTGACC

TTTGG

HA210 4 265195 265195 A C exonic ZNF732* CTTTAGTCGGTTCA

CAACCC

GTATGTGGACCATC

CAAAGG

rs201614981

HA224 4 265195 265195 A C exonic ZNF732* CTTTAGTCGGTTCA

CAACCC

GTATGTGGACCATC

CAAAGG

rs201614981

HA212 16 89291210 89291210 – GTGA exonic ZNF778 CCCTGTGTACAGG

ACATCAC

GACACAATCCTTCCA

TAGCC

rs10625512

MC2 16 89294865 89294865 C A exonic ZNF778 GTGCACATAAGAA

CCCACAC

GAATGAGTGTAGCT

GACAGC

rs201425656

HA210 7 14897869

5

14897869

5

– C exonic ZNF783 CCAACATAGACTC

CTTTGCC

CATGGGTCCGCTGA

TGAATC

*=sequencing not successful, **=primer did not work

Supplementary table S-7 Mutations identified by exome sequencing that failed validation Patient . Position start Position end Ref. Mut. Type Gene Forward

primer5’3’ Reverse

primer5’3’ Rs-number

MC7 9 107556793 107556793 – A intronic ABCA1

CCCAGACATGAGCAA

TTTGC

CAAAGTTCAGGGTACCA

AGG

MC7 1 26671539 26671542 GCAC – exonic AIM1L

CATCGTCCCCAAGGA

ATAAG

CCCTTCACAACCTCTTTC

TG

MC10 1 26671545 26671578

GGGCCCTTCAC

GACCTCTTTCCA

GGTGGGGAACA – exonic AIM1L

CATCGTCCCCAAGGA

ATAAG

CCCTTCACAACCTCTTTC

TG

HA223 1 26671523 26671535

AAATGAGGCAT

CA – exonic AIM1L

CATCGTCCCCAAGGA

ATAAG

CCCTTCACAACCTCTTTC

TG

HA210 20 57042412 57042412 G/C – exonic APCDD1L GGTGACAAAGTGAGA

TTCTG

GTCTCATCCTTGCCTGT

GAC

HA214 2 68805143 68805143 A – exonic APLF CCTGAACGACAGCTT

TCTAG

CTCTGTCTTCCTATTTCC

AG

HA173 11 108172487 108172487 C - exonic ATM

GACTGGACATAGTTT

CTGGG

CTCAGGTTACCTATCTG

AGC rs587779846

HA175 12 112036798 rs772627768 TGC T exonic ATXN2

CTTCGTCGTCCTCCTT

CTCC

CAGGCCTGACAATCCCA

GAG rs772627768

HA175 12 112036796 rs780952627 GC G exonic ATXN2

CTTCGTCGTCCTCCTT

CTCC

CAGGCCTGACAATCCCA

GAG rs780952627

HA225 16 50368678 50368679 CT – exonic BRD7

CTTCCCTGGTTAATGA

CAGG

GCACTTGGTCTTCCCAA

GTC rs145896392

222

MC4 14 93727952 93727967

ATCTGCTATTCT

TTTC – exonic BTBD7

CCATTTTCACCAGGCA

ACAG

GTAGCACATACCTGTAG

TCC

HA214 3 56653422 56653423 AG – exonic CCDC66

CAACAGAGCGAGACT

TCATC

GTTGACGGGGTTTACAT

GGG

HA211 17 45214727 . C

CTCTGGCT

GGCGAATT

T intronic CDC27

CTGTTCTAAGTTGAG

GCTTG

GCACCATCAATACGACT

TTG

HA175 17 45214700 . G GA frameshift CDC27

CTGTTCTAAGTTGAG

GCTTG

GCACCATCAATACGACT

TTG

MC3 17 45221348 45221348 –

CCTTTCGG

CTCTTTCCC

CTCTG exonic CDC27

CACAAGAGGCCATCT

GCAAG

CTTGGTTGTGGAGCTGT

CAC

HA225 13 115089265 115089265 G A intronic CHAMP1

CTGGACCAGAGAAAG

TCAGG

CCTCTGAAACTGCAATG

GTC

MC4 12 58217738 58217741 GGTC – exonic CTDSP2

CTAGGGTTATACAGG

AGGAC

GGTGTACTTCTCTGGTG

GAG

MC1 12 58217389 58217389 G – exonic CTDSP2 CTDSP2

GAGATTGACACCACATC

TTC

MC3 X 55172685 55172685 – T exonic FAM104B

CTGCTATTCTCCAAGC

CAAG

GAAGTGAGCCTCCTTCA

AGG

HA224 X 55172689 55172689 G – exonic FAM104B

CTGCTATTCTCCAAGC

CAAG

GAAGTGAGCCTCCTTCA

AGG

MC3 2 220043304 220043307 AGAA – exonic FAM134A

CTAGGCATGAGTGAG

GCCAC

GAAAGGGGAATGGTGC

TCTC

MC3 2 220043291 220043291 T – exonic FAM134A

CTAGGCATGAGTGAG

GCCAC

GAAAGGGGAATGGTGC

TCTC

MC3 2 220043327 220043327 – C exonic FAM134A

CTAGGCATGAGTGAG

GCCAC

GAAAGGGGAATGGTGC

TCTC

MC3 2 220043321 220043322 CT – exonic FAM134A

CTAGGCATGAGTGAG

GCCAC

GAAAGGGGAATGGTGC

TCTC

MC3 2 220043324 220043324 – AC exonic FAM134A

CTAGGCATGAGTGAG

GCCAC

GAAAGGGGAATGGTGC

TCTC

MC4 19 52227177 52227177 –

ACACACAC

A intronic HAS1

TGCGCTGGTCTTCAA

ATGAC

CTCACCTACATGTACTTG

GG

MC6 16 70977799 70977799 –

TGTGGGGT

CACGGGA

AAGCATTT

TTAATGAT

GCGAATAA

TAATACAG

CATG exonic HYDIN

GGTAAGTGTAGGAGT

TGTTG

GAGCTGTCAAAAAGAC

AAGC

HA212 14 36004018 36004018 –

CCTTCAGA

GTCTGAAG

CGG exonic INSM2

GAACCAGGAAAGGG

GTTGAC

CATCGGCAAAGCTCAAC

TTC

MC3 19 55324674 55324674 – A exonic KIR2DL4

CGTGGGTGCTTGTCT

TAAAG

CACAATCAGGCAACGGT

CTG rs148484482

MC3 19 55358654 55358654 – GC exonic KIR2DS4

CCATGACCCAAACAC

CTCTG

CTCTGCTTCGTGAGACT

TAC

MC6 19 55341708 55341708 C – exonic KIR3DL1 CCAAACAGTCCTGGA

AAACG

GAACTGTGGGCTAAGC

AAAG

MC7 21 45959558 45959559 TC – exonic KRTAP10–1 CTGGCAGCATGAAGT

GGAAG

GGATTCCTCTTCATGCT

GCC

MC4 17 21216816 21216816 C – exonic MAP2K3 GAGCCAGAGAAACTT

GCTGC

CATCTGTGTGCAGGAT

GCAG

HA225 11 10711918 10711918 – A intronic MRVI1 GGGCCTTCAAATTCA

GAGTC

CTGATTAAGCCCAGCCT

TAG

HA225 1 17086940 17086941 AC – exonic MST1L CAGACTACATACGGA

CCTGC

GACAAAGAGCCAGTGG

GTTC

MC3 1 17085995 17085995 – C exonic MST1L GTGACCTGAGAGCAT

ATCCC

GAAGTTCTCCCGAAGGT

CTC

MC3 1 17087245 17087245 C – intronic MST1L GTGGCAGATGCTGAA

GAGTG

CTGGGAGCAAGAGACA

GAAG

rs58502471

MC1 1 149908526 149908526 – C exonic MTMR11 CACGTCAAATGCTCCT

TTCC

GGTCTAGAGTTAACCCC

TAG

MC4 11 95590800 95590800 – AGGT intronic MTMR2 GCGATGAAAGCAACA

TCAGG

CATACCTGCCTTCTATAC

TC

HA173 7 100635388 . C A exonic MUC12

CATCAGTTCAGGCTC

AATGG

GGTGTTGTCAGGTAAGA

GTG

MC6 19 9012898 9012898 G – exonic MUC16** GAGCTCTGAATATGC

ACCAC

GATGTAGGAGGTACTG

ACTC

MC6

19 9012898 9012898 G – exonic

MUC16

GGATAATGCCAGTGA

TGGTG

GATCTTGTTCCATCACCT

GG

HA223 11 1260249 1260249 – G exonic MUC5B

CCAAAGAGCACATGT

GAAGG

GAAACTTGTGCACTCAC

ATG

MC3 11 1018223 1018224 AT – exonic MUC6

CCAACAGGTACCATT

CCTCC

GGTGTGATGGGGTTGG

ATAG

HA225 11 1018215 1018215 – CA exonic MUC6

CTGCAACATCTTTCCA

TGCC

GGTGGTCTTGAAGGAT

GTTG

MC4 13 41897260 41897279

ATACCATTTGCT

GAAAGATT – exonic NAA16

GGAGACAAGATACCA

GCTTC

GTTTTCCCGTTTTCCATA

GG

HA210 16 18532238 18532238 C A exonic NOMO2

GTCAAATTCCCACTGA

CCAC

GGGCCTTGTAACTCATC

TAC

223

MC7 1 145248811 145248811 A G intronic NOTCH2NL

GATGGAGATGTAACA

GCTGG

CAGTATCCTGTGCCATT

GTG

MC7 8 101721933 101721933 T – exonic PABPC1

CTGTCAGTTCTCTGAC

CTGG

GTACACTTGCCATTCTCT

GC rs112966887

MC1 1 144946744 144946744 T C intronic PDE4DIP

CTGCACTTCCATGCTA

GTTG

CCTGCTATACTAGACCA

TGC

HA225 1 87333787 87333787 T – intronic SEP15 CTGCCCTGACTATTCT

TACAC

GCTGGAAAAAAGAGAT

CTCC

MC4 1 150900294 150900295 TC – exonic SETDB1

GAATAGGGAGGGAG

AACATG

CGGATGCCTATAATTCC

AGC

MC3 6 134495725 134495725 C G intronic SGK1

GCTTTCATGAAGCAG

AGGAG

CTGACTCCCTTACAGTTC

TC

MC4 13 21736016 21736016 – TTTATTAT

TCCTC

intronic SKA3** GGATTTTGAAGTCCC

AGGAG

CATGCTGAATGAAATG

GTAC

MC4

13 21736016 21736016 – TTTATTAT

TCCTC

intronic

SKA3

CATCTGTGTAACTGG

CTAGG

CCACTTTTTTCCAACTGC

TG

HA173 13 21734126

T TCA intronic SKA3

CCCTAAAAGCTGGAT

TCATC

GAGTAAGTCCTGCCATC

TTG rs758463308

HA225 13 21732060 21732060 C G intronic SKA3

CGACATGGAAACCAC

AGTTG

GGCATATGGGAGCCTAT

TAG rs151054732

MC1 12 11244067 11244067 – TT exonic TAS2R43

CAGCTCCATGGTAAA

GGATC

CCTCTCGTGAATCTATG

GAG

MC4 12 11244071 11244072 CC – exonic TAS2R43

CAGCTCCATGGTAAA

GGATC

CCTCTCGTGAATCTATG

GAG

HA173 6 170871039 170871040 A AGC exonic TBP

GCCAGCCTAACCTGTT

TTTC

GTACAATCCCAGAACTC

TCC rs71010672

HA214 2 160092703 160092703 – A intronic WDSUB1 CGTCTCCATCCAATCA

ATGC

GATGGCCATTTTCAGA

GTCC

HA223 2 160092703 160092703 – A intronic WDSUB1 CGTCTCCATCCAATCA

ATGC

GATGGCCATTTTCAGA

GTCC

HA214 2 160092703 160092703 – A intronic WDSUB1

CGTCTCCATCCAATCA

ATGC

CAAAGTTCAGGGTACCA

AGG

HA223 2 160092703 160092703 – A intronic WDSUB1

CGTCTCCATCCAATCA

ATGC

CCCTTCACAACCTCTTTC

TG

HA216 19 12541543 12541544 AA – exonic ZNF443 CATGAAAGGACTCAC

ACTGC

GTTTCTCTCCTGTGTGA

GTC

HA223 19 12541541 12541541 – TG exonic ZNF443 CATGAAAGGACTCAC

ACTGC

GTTTCTCTCCTGTGTGA

GTC

HA216 19 12541543 12541544 AA – exonic ZNF443 CATGAAAGGACTCAC

ACTGC

GTTTCTCTCCTGTGTGA

GTC

HA216 19 12541543 12541544 AA – exonic ZNF443

CATGAAAGGACTCAC

ACTGC

GTTTCTCTCCTGTGTGA

GTC

HA223 19 12541541 12541541 – TG exonic ZNF443***

CATGAAAGGACTCAC

ACTGC

GTTTCTCTCCTGTGTGA

GTC

**=primer did not work, *** frameshift is there because this mutation is not

Supplementary table S-8 Mutations identified by exome sequencing that were not subjected to validation

sequencing Patient Chr. Position start Position end Ref. Mut. Type Gene Rsnumber

HA175 5 1033582 C TT exonic NKD2 rs375939102

HA224 20 62493175 62493175 – GGCCAGCTCGC

TAGCTACGCGC

T

exonic ABHD16B

MC4 17 43215126 43215126 G A exonic;introni

c

ACBD4

HA223 1 55059613 55059613 G C intronic ACOT11

HA223 14 74060511 74060511 – TCAA exonic ACOT4

MC6 4 8372713 8372713 G A exonic ACOX3

HA210 19 6183170 6183171 AG – exonic ACSBG2

MC6 X 127185638 127185638 – T exonic ACTRT1

MC2 15 73067221 73067221 – T exonic ADPGK

HA214 10 5043799 5043800 AT – exonic AKR1C2

HA215 1 19203960 19203960 G A exonic ALDH4A1

HA214 4 113353696 113353696 – T exonic ALPK1

HA223 7 16676082 16676082 – A intronic ANKMY2

HA225 20 61906994 61906994 T G intronic ARFGAP1

HA215 2 144276933 144276933 G – exonic ARHGAP15

MC3 8 62550924 62550924 – A intronic ASPH

224

MC3 13 31843415 31843415 G A intronic B3GALTL

MC1 21 11098704 11098723 ACTCCAGC

CGCCATCT

TACT

– exonic BAGE2

MC7 11 101929618 101929618 – CC exonic C11orf70

HA215 16 81094957 81094957 G A exonic C16orf46

HA210 17 65989037 65989037 A G exonic C17orf58

HA223 18 47010118 47010118 T – exonic C18orf32,RPL

17–C18orf32

MC2 1 154171909 154171910 TC – exonic C1orf189

MC6 20 1187535 1187536 AG – exonic C20orf202

MC3 22 38340509 38340509 T – exonic C22orf23

HA223 22 19435270 19435270 – A exonic C22orf39

MC1 3 138668458 138668467 GGCATTC

GAA

– exonic C3orf72

HA195 4 76489322 76489322 A G intronic C4orf26

HA195 4 5527115 5527115 – T exonic C4orf6

HA210 7 1037383 1037383 C – exonic C7orf50 rs200169409

MC4 8 67590023 67590023 G – exonic C8orf44

HA212 9 74586535 74586538 GTGA – intronic C9orf85

HA216 1 116243979 116243979 C T exonic CASQ2

MC2 2 179714812 179714812 T – exonic CCDC141

HA210 13 103399818 103399818 – T exonic CCDC168

HA215 3 126133023 126133023 G A intronic CCDC37

MC4 Y 21154529 21154529 – TTA exonic CD24

MC4 Y 21154528 21154528 – AAAATACATAA

AAA

exonic CD24

MC7 1 54605318 54605318 – GG exonic CDCP2

HA224 16 55844924 55844924 – A intronic CES1

HA223 1 203186950 203186950 – AGACCATGGCC

CCGCCCAGTCC

CT

exonic CHIT1

HA223 2 233406191 233406191 – A exonic CHRNG

MC1 10 125780753 125780753 G – exonic CHST15

HA224 3 190106072 190106072 G – exonic CLDN16

HA223 16 58577316 58577316 A – exonic CNOT1

HA195 4 84206004 84206004 T A exonic COQ2

MC2 11 46342259 46342259 – G intronic CREB3L1

MC4 10 126692023 126692023 G – exonic CTBP2

HA225 X 23933912 23933912 G A intronic CXorf58

HA173 3 50391167 T C CYB561D2 rs114924982

MC2 1 155003712 155003712 – G intronic DCST2

HA224 4 169315747 169315747 G A exonic DDX60L

MC6 1 197621397 197621421 GTACTGG

GTGGTTAT

ACAGTGA

TCT

– exonic DENND1B

HA216 1 225334919 225334922 AATT – exonic DNAH14

MC3 2 25170534 25170534 A – exonic DNAJC27

MC2 11 637537 637549 CCGCCGA

CCTCCT

– exonic DRD4

MC1 18 28647999 28647999 – TC exonic DSC2

HA224 17 80019231 80019232 TG – intronic DUS1L

MC10 3 73111724 73111724 T G exonic EBLN2

225

HA224 6 53152683 53152683 G A exonic ELOVL5

MC1 12 7080212 7080212 T C intronic EMG1

HA150 4 71508402 71508402 – AG exonic ENAM

HA195 1 43621956 43621956 G A exonic FAM183A rs149435229

MC4 12 50747117 50747121 TTTCT – exonic FAM186A

HA223 5 7863112 7863112 – A intronic FASTKD3

MC10 18 74208486 74208486 G – intronic FLJ44313

MC3 10 135438960 135438960 C – exonic FRG2B

MC3 15 40018807 40018807 – A exonic FSIP1

HA173 2 242716400 G A intronic GAL3ST2 rs78620448

HA150 5 145895394 145895394 G A exonic GPR151 rs114285050

HA212 17 36493523 36493523 G – exonic GPR179

HA214 5 90049403 90049403 G T exonic GPR98

MC2 6 117113762 117113762 – A exonic GPRC6A

MC3 12 122287697 122287697 C T intronic HPD

HA210 4 88235068 88235068 G C exonic HSD17B13 rs142648167

HA225 20 43374722 43374723 GG – exonic KCNK15

HA210 6 39282816 39282816 G A exonic KCNK16 rs138573996

HA225 6 36452603 36452603 – A intronic KCTD20

MC2 1 175129948 175129955 TCTTCTTG – exonic KIAA0040

MC1 13 46946088 46946088 C – exonic KIAA0226L

HA216 14 58899157 58899157 G – exonic KIAA0586

MC6 5 5460669 5460669 A T exonic KIAA0947

MC2 20 36869090 36869090 T – exonic KIAA1755

MC7 22 50987497 50987497 G – exonic KLHDC7B

MC6 17 39458574 39458586 GTACAGA

TGGTTG

– exonic KRTAP29-1 rs144150438

HA150 3 156697055 156697055 – T exonic LEKR1 rs200834448

HA216 12 49499706 49499706 C T intronic LMBR1L rs201470223

HA224 19 4682879 4682880 AG – exonic LOC1001310

94

HA195 10 105005931 105005931 C T exonic LOC729020

HA224 17 62855003 62855003 – A intronic LRRC37A3

MC3 7 91793327 91793327 A – exonic LRRD1

MC4 11 71807767 71807767 A C intronic LRTOMT

MC2 9 139748277 139748296 CCCTGTG

GCAGAGC

ACAGGG

– exonic MAMDC4

HA150 4 103611909 103611909 C T exonic MANBA

HA215 8 144651725 144651725 – G exonic MROH6

MC1 12 65762786 65762786 C – exonic MSRB3

MC2 3 195452668 195452668 C G exonic;introni

c

MUC20 rs201581458

HA150 6 30993758 30993758 G – exonic MUC22

HA210 14 23889445 23889445 – G intronic MYH7 rs45504498

HA215 14 23889445 23889445 – G intronic MYH7 rs45504498

MC2 17 18062605 18062605 C – exonic MYO15A

MC6 10 95159156 95159156 C – exonic MYOF

HA210 7 123197691 123197691 G C exonic NDUFA5 rs118062590

HA225 7 123197691 123197691 G C exonic NDUFA5 rs118062590

226

MC3 18 70423384 70423384 – A intronic NETO1

MC10 20 44519224 44519224 – T exonic NEURL2

MC6 5 175811094 175811094 – GT exonic NOP16

HA150 14 74947404 74947404 C T intronic NPC2

MC3 17 45669428 45669428 – A intronic NPEPPS rs59875832

HA225 19 49168026 49168026 T C intronic NTN5

HA223 9 99694525 99694525 – A exonic NUTM2G

MC4 1 228558993 228558994 CA – exonic OBSCN

HA210 22 50969725 50969725 C T intronic ODF3B

HA213 17 80369330 80369330 C T intronic OGFOD3

HA224 9 125424415 125424415 – G exonic OR1L1

HA223 1 248801945 248801951 CAGCACG – exonic OR2T35

MC7 1 248801602 248801602 – CA exonic OR2T35

MC6 15 22369176 22369177 TG – exonic OR4M2

HA210 11 5410769 5410769 C G exonic OR51M1 rs182074434

HA214 11 58207036 58207036 T – exonic OR5B12 rs201567144

HA210 11 55703050 55703051 AT – exonic OR5I1

HA214 12 55759485 55759485 – T exonic OR6C75

MC4 11 17631831 17631831 G T exonic OTOG

HA213 12 29630166 29630166 C T intronic OVCH1 rs189316643

HA212 12 121570899 121570899 G T intronic P2RX7

HA225 12 56500502 56500502 – A intronic PA2G4 rs34728522

HA211 5 140181971 CT C exonic PCDHA3 rs782412251

MC7 5 140579736 140579736 – T exonic PCDHB11

MC10 2 178969170 178969171 TC – exonic PDE11A

MC3 13 73409508 73409508 – A intronic PIBF1

MC2 10 3208567 3208567 – GCACGCTAGG

GAAGAGAGAG

GAATG

exonic PITRM1

MC3 16 81242149 81242150 TT – exonic PKD1L2

HA213 8 110464510 110464510 G A intronic PKHD1L1

HA215 3 16926562 16926562 T C intronic PLCL2

MC1 9 140356449 140356449 – C exonic PNPLA7

MC2 1 145592762 145592762 G – exonic POLR3C

MC6 8 67922949 67922949 C T intronic PPP1R42

HA223 12 11461154 11461154 C G intronic PRB4

HA215 16 31150656 31150656 C A exonic PRSS36 rs201757658

HA225 19 43420568 43420568 A – exonic PSG6

MC1 12 133277869 133277869 – G exonic PXMP2

MC3 2 28081439 28081439 C G intronic RBKS

HA224 2 220197294 220197294 G – exonic RESP18

HA223 1 156354348 156354348 C – intronic RHBG

HA225 X 119293216 119293216 – G exonic RHOXF2B

MC7 1 153520256 153520256 C – exonic S100A3

MC1 19 3179413 3179413 G – exonic S1PR4

MC7 6 130466547 130466548 AT – exonic SAMD3

MC4 14 55251159 55251159 C T exonic SAMD4A

HA212 4 129925032 129925032 C A intronic SCLT1

227

HA216 2 167138320 167138320 – A intronic SCN9A rs35888674

MC6 2 167138320 167138320 – A intronic SCN9A rs35888674

HA223 1 1222262 1222262 C – exonic SCNN1D

MC2 2 120219488 120219488 – T exonic SCTR

HA216 14 24909629 24909629 C – exonic SDR39U1

MC3 12 113874568 113874568 C – exonic SDSL

MC2 4 119666217 119666217 – A intronic SEC24D rs35951660

MC10 6 108243115 108243115 – GGG intronic SEC63

HA210 21 40823984 40823985 AG – exonic SH3BGR

MC7 2 233131 233131 C – exonic SH3YL1

HA175 X 50350726 T TC exonic SHROOM4 rs587780460

HA150 3 38355433 38355433 G T intronic SLC22A14

HA215 5 140683301 140683301 – T exonic SLC25A2

MC4 7 103062016 103062016 T C intronic SLC26A5

HA210 4 25678141 25678141 C T exonic SLC34A2

HA175 6 71378354 AC A exonic SMAP1 rs200042613

HA215 6 71378355 71378355 C – exonic SMAP1 rs200042613



MC2 11 57313384 57313384 – C exonic SMTNL1

MC10 8 145086759 145086759 A T exonic SPATC1

MC2 15 42147511 42147511 G A exonic SPTBN5 rs369248083

MC1 5 139931628 139931628 – GT exonic SRA1 rs3085220

MC10 5 139931629 139931629 – G exonic SRA1 rs5871740

MC4 14 38679763 38679763 – GCTCTGAGCCC

GGGCCACGCA

GGG

exonic SSTR1

HA212 2 153004816 153004816 – A intronic STAM2

HA214 3 111718266 111718266 A G intronic TAGLN3

MC3 12 10958845 10958845 – A exonic TAS2R8

HA212 6 167591956 167591956 C T exonic TCP10L2

MC2 19 36530272 36530272 G – exonic THAP8

HA216 17 1613129 1613130 GC – exonic TLCD2

MC3 4 159136408 159136408 T – exonic TMEM144

HA224 10 81841421 81841421 – A exonic TMEM254

HA195 1 16073527 16073527 – G exonic TMEM82 rs199908593

HA215 1 16073527 16073527 – G exonic TMEM82 rs199908593

MC7 21 10970008 10970008 C T intronic TPTE

HA215 11 89606435 89606435 C T intronic TRIM64B rs201030722

HA223 22 38106569 38106578 AAGAGGT

GGG

– exonic TRIOBP

MC3 4 8442843 8442843 C A exonic TRMT44

MC7 6 41010518 41010518 G A intronic TSPO2

HA223 5 34896981 34896981 G T intronic TTC23L

HA211 6 30689576 C T Intronic TUBB rs145807661

HA216 3 38043191 38043191 A T intronic VILL

MC7 16 89782865 89782868 CTTA – intronic VPS9D1

HA212 3 183959134 183959134 – C exonic VWA5B2

MC10 3 101370529 101370529 – AAA intronic ZBTB11

228

MC2 19 44932910 44932910 – T exonic ZNF229

HA223 19 58437532 58437535 TTCT – exonic ZNF418

MC2 19 37879852 37879852 – TGTG exonic ZNF527

MC4 19 9764285 9764285 – T exonic ZNF562

HA211 19 35251141 CTT C exonic ZNF599 rs571541043

HA225 19 35250691 35250692 AG – exonic ZNF599 rs148227520

HA215 19 53912008 53912008 C – exonic ZNF765

MC10 19 53994822 53994823 AA – exonic ZNF813

MC3 19 12186971 12186975 TTATC – exonic ZNF844

MC4 19 22575784 22575784 C A intronic ZNF98

MC3 6 17601125 17601125 – CTAACCTGGGA

ACAGCTGCT

exonic FAM8A1

MC3 6 17601123 17601123 – ACAG exonic FAM8A1

HA173 14 51348345

G T intronic ABHD12B rs138523238

HA211 7 99026828

C T intronic ATP5J2-

PTCD1 -

HA211 9 116130660

TC T exonic BSPRY -

HA173 19 14194130

CG C exonic C19orf67 rs779526443

HA211 19 47768204

G A intronic CCDC9 rs202156396

HA211 4 2451724

C T exonic CFAP99 rs771764585

HA173 20 23473679

GC G exonic CST8 -

HA175 22 42525085

CA C exonic CYP2D6 rs5030655

HA175 1 47489633

GC G exonic CYP4X1 rs539638964

HA173 1 153907305

G GC exonic DENND4B rs35902206

HA173 11 71146886

G C intronic DHCR7 rs138659167

HA175 9 139258136

T TCGGCG exonic DNLZ rs765100405

HA175 1 167086633

C CT exonic DUSP27 rs763223361

HA211 6 46107848

AC A exonic ENPP4 -

HA175 20 55108506

CCGTGT CAATAC exonic FAM209B rs756419294,

rs780605931

HA211 4 190862176

C A exonic FRG1 -

HA211 5 74324982

T TG exonic GCNT4 rs768450027

HA173 12 75728510

T C exonic GLIPR1L1 -

HA211 5 94957045

C T exonic GPR150 rs185804545

HA173 11 108352891

C T exonic KDELC2 rs186063712

HA211 4 8951859

G A exonic LOC650293 rs777389545

HA211 11 71807767

A C intronic LRTOMT rs188080974

HA175 5 179222858

G A intronic LTC4S rs137887093

HA175 4 71346700

A AC exonic MUC7 rs34918942

HA173 11 77784146

CA C exonic NDUFC2-

KCTD14 rs747914168

HA175 11 4825211

G A exonic OR52R1 rs200658751

HA175 2 242051654

C T intronic PASK rs140030739

HA175 5 171389

C T exonic PLEKHG4B -

HA211 7 99026828

C T intronic PTCD1 -

HA211 14 69928413

G A intronic SLC39A9 rs111495442

HA173 X 142803691

AT A exonic SPANXN2 rs782748787

HA175 9 71152192

G A exonic TMEM252 rs147880223

HA175 7 12433329

AG A exonic VWDE -

HA211 19 23328751

A AT exonic ZNF730 rs529180941

229

HA175 19 11834158

C T intronic ZNF823 -

HA173 14 51348345

G T intronic ABHD12B rs138523238

HA211 7 99026828

C T intronic ATP5J2-

PTCD1 -

HA211 9 116130660

TC T exonic BSPRY -

230

Supplementary figure S-8 Complete IPA core analysis results of all RS patients

231

Supplementary figure S-9 Complete IPA core analysis results of RS BC patients

232

Supplementary figure S-10 Complete IPA core analysis results of RS patients with other cancers Five RS patients with the following cancer types were analyzed: Hypopharynx, squamous epithelium carcinoma of left

tonsil, keratinizing squamous cell carcinoma of the base of the tongue, squamous cell carcinoma external ear, rectum

carcinoma.

233

Supplementary figure S-11 Complete IPA core analysis results of all Chemo RS patients Chemo RS patients with the following cancer types were analyzed: two breast cancer and one prostate cancer.

235

Supplementary figure S-13 Complete IPA core analysis results of BC patients

236

Supplementary figure S-14 Complete IPA core analysis results of Fam BC patients

237

Supplementary figure S-15 IPA heatmaps of “Cancer” and “Organismal Injury and Abnormalities” in RS

patients

238

Supplementary figure S-16 “Neurological disease”, “Reproductive system disease” and “Dermatological

diseases and conditions” IPA hits in RS patients

239

Supplementary figure S-17 IPA heatmaps of “Cancer” and “Organismal Injury and Abnormalities” in RS BC

patients

240

Supplementary figure S-18 IPA heatmaps of “Cancer” and “Organismal Injury and Abnormalities” in BC

patients

241

Supplementary figure S-19 IPA heatmaps of “Cancer” and “Organismal Injury and Abnormalities” in Fam BC

patients

242

Supplementary figure S-20 IPA heatmaps of “Reproductive system disease” and “Neurological Disease” in RS

BC patients

Supplementary figure S-21 IPA heatmap of “Hereditary Disorder” in Fam BC patients

243

Label of square in upper left corner= Susceptibility to familial breast-ovarian cancer type 1, lower left

square= hereditary prostate cancer

Supplementary table S-9 Genes identified in DNA replication, recombination and repair by IPA Underlined genes were excluded from the analysis as they were not prove-read by GeneCards to be part of DNA repair.

RS BC BC Fam BC

ABL1 CENPW APOBEC3B

AIRE DNMT3A BRCA2

DNMT3A FIGNL1 HIST1H4B

EXO5 MITF KNTC1

FANCL MSH6 NBN

HELB SLC22A2 NEIL1

HERC2 STARD9

MICA TDG

NEIL1 WRAP53

NEK4

NUSAP1

PDE11A

RAD51C

RBBP6

RINT1

TARP

Supplementary table S-10 IPA definitions of DNA repair subpathways and underlying references

IPA subpathway RS BC BC Fam BC

DNA damage

response of cells

ABL654, HELB89,

HERC2658, FANCL655,

NEK472, RBBP6106

- NBN653

Repair of DNA ABL1215, RAD51C663,

FANCL655, NEIL1671-674

FIGNL176, MSH6675-679 NEIL1671-674, TDG37

664 665, BRCA2668-670,

NBN653 660-662

244

Supplementary figure S-22 IPA comparison analyses between groups with unique genes The following abbreviations were used: Neurolog.= neurological, Orgn. Inj./Abnorm.= organismal injuries and abnormalities,

Reprod. S. Dis.= reproductive system disease, Dermat. Dis./Cond.= dermatological diseases and conditions,

Endocr. S. Dis.= endocrine system disease, Immunolog. Disease= immunological disease, Heredit. Dis= Hereditary Disorder.

245

Supplementary figure S-23 Canonical pathways in comparative analyses of unique genes from RS BC, BC and

Fam BC groups

246

Heatmaps of canonical pathways identified by Ingenuity Pathway Analysis comparison tool regarding only genes, which

were unique to the respective patient group, compare Figure 20. Heatmaps of canonical pathways identified by Ingenuity

Pathway Analysis comparison tool. Panel A shows results of superior canonical pathways in 11 radiosensitive (RS) breast

cancer (BC) patients, 11 BC and 11 familial (Fam) BC patients. Pathways of interest are enclosed by squares. Panel B shows

the results of the comparison analysis in the “Diseases and Disorders” section, filtered for “Cancer” subcategory. Panels C

and D show the results of comparison analysis with the modified datasets filtered for results obtained in the “DNA Replication, Recombination and Repair” category and further restricted to “DNA repair” as revised by GeneCards analysis,

see also Figure 22. The genes in the three datasets are listed in Supplementary table S-9. Arrows indicate particularly

interesting categories in the radiosensitive context. List of p-values of overlap for panel C and the top 40 hits in panel D are

given in. Supplementary table S-12 and Supplementary table S-13.

Supplementary table S-11 Canonical pathway p-values of comparative IPA analysis

Canonical Pathway RS BC BC Fam BC

Dopamine Degradation 0.049354 0.035189 0.240749

L-DOPA Degradation 0.024489 0.020327 1

Inflammasome pathway 0.22931 0.019194 0.18078

Crosstalk between Dendritic Cells and Natural Killer Cells 0.024307 0.063025 0.571119

Noradrenaline and Adrenaline Degradation 0.068967 0.049568 0.282841

DNA Double-Strand Break Repair by Homologous

Recombination

0.159379 1 0.007494

Uracil Degradation II (Reductive) 1 0.040244 0.037253

Thymine Degradation 1 0.040244 0.037253

Bladder Cancer Signaling 1 0.012172 0.562863

P2Y Purigenic Receptor Signaling Pathway 1 0.01152 1

Agrin Interactions at Neuromuscular Junction 0.564826 0.031212 1

Chronic Myeloid Leukemia Signaling 1 0.021338 1

GPCR-Mediated Integration of Enteroendocrine Signaling

Exemplified by an L Cell

0.591071 0.037461 1

Glioblastoma Multiforme Signaling 1 0.023805 1

4-hydroxyproline Degradation I 0.024489 1 1

Proline Degradation 0.024489 1 1

Non-Small Cell Lung Cancer Signaling 0.61574 0.044298 1

Oxidized GTP and dGTP Detoxification 1 1 0.028071

ErbB4 Signaling 1 0.03489 1

L-serine Degradation 0.036509 1 1

1D-myo-inositol Hexakisphosphate Biosynthesis V 0.036509 1 1

p70S6K Signaling 1 0.045529 1

Serine Biosynthesis 1 1 0.046349

Lactose Degradation III 1 1 0.046349

Arginine Degradation I (Arginase Pathway) 0.048382 1 1

Protein Citrullination 1 0.05005 1

Supplementary table S-12 Canonical pathway p-values of comparative IPA analysis after DNA repair filtering

Canonical Pathway RS BC

(p-value of

overlap)

BC

(p-value of

overlap)

Fam BC

(p-value of

overlap)

DNA Double-Strand Break Repair by Homologous

Recombination

0.00716531 1 2.88E-06

Role of BRCA1 in DNA Damage Response 0.03933616 0.007992 9.45E-05

Hereditary Breast Cancer Signaling 0.07008492 0.014424 0.000309

ATM Signaling 0.00071552 1 0.016125

Ovarian Cancer Signaling 0.07104639 0.014628 0.029044

Pancreatic Adenocarcinoma Signaling 0.0589634 1 0.024013

Mismatch Repair in Eukaryotes 1 0.001642 1

DNA Double-Strand Break Repair by Non-Homologous End 1 1 0.002872

247

Joining

NAD Biosynthesis from 2-amino-3-carboxymuconate

Semialdehyde

0.00307653 1 1

Telomere Extension by Telomerase 1 1 0.003077

NAD biosynthesis II (from tryptophan) 0.00665504 1 1

Role of CHK Proteins in Cell Cycle Checkpoint Control 1 1 0.011247

G Protein Signaling Mediated by Tubby 0.0158039 1 1

Sumoylation Pathway 1 1 0.019569

Axonal Guidance Signaling 0.02075259 1 1

Colorectal Cancer Metastasis Signaling 1 0.024794 1

Cell Cycle: G2/M DNA Damage Checkpoint Regulation 0.02487686 1 1

Cell Cycle: G1/S Checkpoint Regulation 0.03188149 1 1

Caveolar-mediated Endocytosis Signaling 0.03586377 1 1

Non-Small Cell Lung Cancer Signaling 0.0388408 1 1

Cyclins and Cell Cycle Regulation 0.0388408 1 1

Small Cell Lung Cancer Signaling 0.0427973 1 1

Bladder Cancer Signaling 0.04378413 1 1

PDGF Signaling 0.04526266 1 1

Prostate Cancer Signaling 0.04723084 1 1

CDK5 Signaling 0.04919536 1 1

Supplementary table S-13 First 40 Hits of Diseases and Biofunctions p-values of comparative IPA analyses

after DNA repair filtering

Diseases and Bio Functions after filtering for

DNA repair

RS BC - unique

(p-value of

overlap)

BC – unique

(p-value of

overlap)

Fam BC – unique

(p-value of

overlap)

Repair of DNA 0.000209 0.000251 3.97E-06

DNA damage response of cells 5.51E-11 1 0.03369

Metastatic malignant neoplasm of prostate 0.039596 0.010048 7.51E-05

Susceptibility to familial breast-ovarian cancer

type 1 1 1 4.75E-08

Mismatch repair 0.011049 0.002773 0.004157

Elongation of telomeres 1 0.001028 0.001541

Tumor predisposition syndrome 1 0.00113 0.001695

Cell viability of cervical cancer cell lines 1 1 2.61E-06

Binding of DNA fragment 1 1 5.15E-06

Cell viability of fibroblast cell lines 1 1 5.56E-06

Cell proliferation of bone cancer cell lines 1.56E-05 1 1

Survival of lung cell lines 0,006969 1 0.002619

Double-stranded DNA break repair of cells 1 1 2.61E-05

Repair of tumor cell lines 1 1 3.29E-05

Carcinoma of unknown primary 0.011863 0.002979 1

Cell cycle progression 0.005529 1 0.007027

Excision repair 1 1 4.15E-05

Primary ovarian cancer 1 1 4.63E-05

Formation of nuclear foci 1 1 4.87E-05

Cell proliferation of sarcoma cell lines 5.19E-05 1 1

Formation of gamma H2AX nuclear focus 1 0.006158 0.009223

Aplastic anemia 1 1 6.05E-05

Fanconi anemia 9.78E-05 1 1

Colorectal and endometrial cancer 1 0.000103 1

Early-onset colorectal cancer 1 0.000103 1

Hereditary nonpolyposis colorectal cancer 1 0.000103 1

248

type 5

Osteosarcoma 0.000121 1 1

DNA repair-deficiency disorder 1 1 0.000124

Susceptibility to familial breast-ovarian cancer

type 2 1 1 0.000154

Sensitivity of embryonic stem cells 1 1 0.000154

Nijmegen breakage syndrome 1 1 0.000154

Binding of DNA double strand break site 1 1 0.000154

Glioma susceptibility 3 1 1 0.000154

Medulloblastoma 1 1 0.000156

Brain tumor 1 1 0.000167

Metastatic osteosarcomagenesis 0.000179 1 1

Metabolism of DNA 0.000183 1 1

Primary peritoneal cancer 0.024006 1 0.009069

Stage II breast cancer 0.000242 1 1

Supplementary table S-14 Comparison of annotation methods: cancer

GeneCards Reactome IPA

RS BC ABL1, ANKLE1, ARID5B, ASCC1, ASPH, AURKC, BAGE2, C10orf68, C17orf80, C1orf173, CLCA2,

CREB3L1, DNAH8, DNAJC27, DNMT3A, DSC2, GPR142, HELB, ITGAD, KIAA1524, L1TD1, LIMD2, LPAR2, MAP4, MAG, MICA, MICB,

NPAT, NUB1, PDE11A, POU5F1B, PTTG2, RAD51C, RBBP6, RYK, SCTR, SKA3, SRA1,

STIM1, SYTL3, TCP10L2, TMC3, TNFRSF10A

ABL1, MUC20, TNIP1 ABL1,ACADL,ARHGAP15,ARID5B,ASCC1,ASPH,AURKC,C17orf80,C7orf50,C9orf85,CAMKK2,CCDC141,CCDC1

50,CCDC168,CCDC66,CDCP2,CDKL2,CELA1,CHST15,COL6A5,CREB3L1,CRNKL1,DEFB132,DNAH7,DNAH8,D

NHD1,DNMT3A,DSG3,ERICH3,FANCL,FRG1,FRG2/FRG

2B,GPRC6A,GPRIN1,HAVCR1,HELB,HERC2,HHLA2,HRNR,HYDIN,ITGAD,KCNK16,KCNQ3,KIAA0040,KIAA152

4,KIAA1755,KIR3DL1,KMT2C,LILRA1,LRRCC1,MAMDC4,MAP4,MAPK10,MB21D2,MGA,MICA,MICB,MUC20,MYH7,MYO15A,NEB,NEIL1,NOTCH2,NPEPPS,OAS3,P

ABPC3,PCDHA3,PCDHGA10,PDE11A,PITRM1,PKD1L2,PKHD1L1,PNPLA7,PSORS1C1,PXMP2,RBBP6,SALL1,SA

MD3,SH3BGR,SIGLEC11,SKA3,SPHK1,SRA1,STIM1,TARP,TEX15,TRIM64/TRIM64B,TTN,USP49,WDR27,ZNF

527,ZNF599,ZNF844

BC AIM2,BAGE,C1QTNF8,CCBE1,CD44,CHST5,CHTF18,CLEC11A,CLTCL1,CRIPAK,DNAH2,DNMT3A

,ERBB4,FAM120A,FAT1,FGF20,KRT83,LASP1,MAGEC1,MAPRE2,MICB,MMP8,MOK,MSH6,NMB,NOP16,PTCHD3,RNASEL,RRAS,SLC22A2,SP10

0,SSTR1,SYTL3,TKTL2,TMC3,TNXB,TRIM40,TRMT2A,ULBP3

ERBB4, SOS2, CTBP2, MSH6 ,FGF20

A1BG,A2ML1,ACOT4,ADAR,AFP,AIM2,C17orf82,C1orf167,C1QTNF12,C1QTNF8,C4orf36,CASP5,CCDC150,C

D24,CD44,CEP126,CHST5,CHTF18,CIT,CLEC4M,CLTCL1,COL20A1,COL23A1,COQ2,CRIPAK,CTBP2,CTU2,CXCR3,CXorf58,CYHR1,DNAH2,DNMT3A,EIF2AK4,ERBB4,

FADS6,FAM120A,FAM151A,FAM186A,FAT1,FLG2,GGN,GPRIN1,GZMM,KIAA1683,KIR3DL1,KRTAP5-

3/KRTAP5-5,MAGEC1,MICB,MITF,MNDA,MSH6,MYH15,MYH7,

MYOF,NF1,NIPSNAP1,NLRX1,NMB,OBSCN,PADI1,PCD

HGA9,PLCH2,PRAMEF1(includesothers),PRB4,PSORS

1C1,PTCHD3,PXDNL,RAB3GAP1,RBM44,RNFT1,RP1L1,SAMD1,SAMD4A,SCN9A,SLC13A1,SLC22A2,SLC34A3,

SLCO1B3,SLFN13,SOSTDC1,SP100,SPERT,SSC5D,SSTR1,TARS2,TAS2R43,TBC1D17,TNXB,UPK3B,USP49,ZFYV

E19,ZNF527,ZNF534

249

Fam

BC

BRCA2,ANO7,C4orf6,CD22,CDC27,CDK11A,CEP290,CHP2,CRIPAK,DDX43,DDX6,DNAH7,EPPK1,

FAM120A,GPRC5A,IFLTD1,KLK14,KMT2C,LPAR3,MLX,MMP1,MOK,MSR1,MST1,NBN,NES,NOMO2,NOP16,PNLIPRP3,PSMB11,PSPH,SLC6A1

3,SLC9A1,SPANXN4,TCP10L2,TDRKH

CD22,DDX6,NBN,NEURL3 ADAM2,AGBL1,ANKRD36,APOBEC3B,ARHGEF16,BRCA2,BTN3A3,C11orf40,C7orf50,CASP8AP2,CCDC178,C

D48,CDC27,CDKL2,CLCN1,CRIPAK,CYP2A6(includesothers),DDX6,DNAH7,DNAH9,EPPK1,FAM120A,FHAD1,FOLH1B,GJA1,GLB1L3,GPRC5A,GPRC6A,HIST1H4B,IFI

44L,IGFN1,IGSF3,KCNK16,KIAA1755,KIAA1841,KIR2DS4(includesothers),KIR3DL2,KMT2C,KNTC1,LEXM,LGALS9B,LILRA1,LRG1,MMP1,MSR1,MST1,NEIL1,NES,NLR

C4,OPRM1,PCDHGA10,PDE4DIP,PNLIPRP3,PRSS3,PSPH,RIPK3,SLC22A24,SLC9A1,SNAPC2,STARD9,TAS2R43

,TDG,TLR5,TMEM247,TRIM38,TRIM58,TRIM64/TRIM64B,ZAN,ZCCHC4,ZDHHC13,ZNF527,ZNF599

Supplementary table S-15 Comparison of annotation methods: immune system GeneCards Reactome IPA

RS BC ABL1, AIRE, APOBR, BPIFB3, C6, CELA1,

CHST15, CLEC5A, CSF2RB, DCST2, DEFB132, DSG3, GPRC6A, GPRIN1, HAVCR1, HERC2,

HHLA2, KIF4B, KIR3DL1, LAX1, LFNG, LILRA1,

MICA, MICB, MROH2B, MST1L, NLRC3, NPEPPS, NUB1, OAS3, PDCD1LG2, POLR3C,

RASAL3, RBBP6, RYK, SARM1, SEC24D, SIGLEC11, SLC35A2, SPHK1, SPTBN5, STAM2,

STIM1, TARP, TNIP1, TTN, ZNF783

ABL1, AZU1, C6,

CLEC5A,CSF2RB, DEFB132, DSC2, ENPP4, HERC2, HRNR, ITGAD, KIF4B,

KIR3DL1, LAMTOR1, LILRA1, MAPK10, MAG,

MICA, MICB, MUC20, NLRC3, NPEPPS, OAS3,

P2RX7, PDCD1LG2,

POLR3C, RASAL3, RBBP6, SARM1, SEC24D,

SIGLEC11, SPTBN5, STIM1,

TUBB, XDH

ABL1, AIRE, ALPK1, ARID5B, CCDC7, CHST15, CSF2RB,

DNMT3A, FAM83E, FANCL, GPRIN1, HAVCR1, HELB, HERC2, HRNR, HYDIN, KIR3DL1, KMT2C, LPP, LRRCC1,

MAG, MICA, MICB, MMRN2, MYO15A, NEB, NEK4,

NOTCH2, NPAT, PABPC3, PDCD1LG2, PDE11A, PSIP1, SEC24D, SIGLEC11, STIM1, TARP, TNFRSF10A, TSPO2,

TTN, XDH, ZNF229, ZNF527

BC A1BG,ADAR,AIM2,AMICA1,BAGE,C1orf168,CASP5,CCBE1,CD24,CD44,CLEC11A,CLEC4M,CLTC

L1,CNP,CTSW,CXCL6,CXCR3,DENND1B,FAM132A,FLG2,GPRIN1,GZMM,IFNA5,KIR3DL1,MICB,MMP8,MNDA,MST1L,MYH15,MYH7,NLRX1,PA

2G4,PRG3,RNASEL,SCART1,SLC22A2,SP100,SSC5D,STBD1,TRAF3IP2,TRIM40,ULBP3

A1BG,ADAR,AIM2,AMICA1,CD44,CLEC4M,ERBB4,FAT

1,FGF20,FLG2,GZMM,IFNA5,KIR3DL1,MICB,MMP8,MNDA,NF1,NLRX1,PA2G4,PR

G3,RNASEL,SP100,STBD1,ULBP3

ADAR,AGRN,AIM2,C1orf167,CD24,CD44,CLEC4M,CRIPAK,CTBP2,CTSW,CXCL6,CXCR3,DNAH2,DNMT3A,EFC

AB5,FAT1,FLG2,GPRIN1,GZMM,HPS1,KCNK18,KIR3DL1,MICB,MITF,MMP8,MYOF,NF1,OBSCN,OTOA,PADI1,PSORS1C1,PVRIG,SCN9A,TNXB,TRIM40,TSPO2,ZNF49

2/ZNF98,ZNF527

Fam

BC

APOBEC3B,ARHGAP9,ASGR1,BTN3A3,C2,CD22

,CD300A,CD48,CEP290,CFHR5,CXCL6,DDX43,IFI44L,IFNK,KIR2DS4,KIR3DL2,LILRA1,LRG1,MOK,

MSR1,NBN,NLRC4,PLA2G4D,PSMB11,SPTBN5,TLR5,TRIM38,UBE2W,UBE3B,WRAP53,

ARHGAP9,BTN3A3,C2,CD2

2,CD300A,CDC27,CEP290,CFHR5,CNKSR1,HSPA6,KIR2

DS4,KIR3DL2,LILRA1,LRG1,MMP1,NLRC4,OPRM1,PRSS3,PSMB11,RIPK3,SPTBN5,

TLR5,TRIM38,UBE2W,UBE3B

ADAM2,AFAP1L1,AGBL1,ALDH1L2,C2,CD22,CD48,CF

HR5,CRELD2,CYP2A6(includesothers),DNAH9,GJA1,HSPA6,IGSF3,KIR3DL2,KMT2C,LEKR1,LEXM,MMP1,MT

MR11,NBN,NLRC4,NOMO1(includesothers),OPRM1,PDIA2,PRSS3,SLC9A1,TLR5,TRIM38,ZAN,ZNF492/ZNF9

8,ZNF599,

Supplementary table S-16 P-values of densitometric analyses performed for results discussed in 4.4.1

p-CHEK2 compared to ß-actin BJ5TA MC1 TERT MC3 TERT MC7 TERT

0 Gy/1.5 Gy 0.789 1.000 0.158 0.021

1.5 Gy/6 Gy 0.001 0.0001 0.038 < 0.0001

BJ5TA 1.5 Gy/1.5 Gy 1.000 0.272 0.106

BJ5TA 6 Gy/6 Gy 0.056 0.401 0.101

MC3 TERT 1.5 Gy/1.5 Gy 0.272 0.106 0.106

MC3 TERT 6 Gy/6 Gy 0.401 0.945 0.789

MC1 TERT 1.5 Gy/1.5 Gy 1.000 0.106 0.106

250

MC1 TERT 6 Gy/6 Gy 0.056 0.945 0.386

p-CHEK2 compared to BJ5TA MC1 TERT MC3 TERT MC7 TERT

0 Gy/1.5 Gy 0.459 0.874 0.589

1.5 Gy/6 Gy 0.555 0.968 0.303

MC3 TERT 1.5 Gy/1.5 Gy 0.631 0.642

MC3 TERT 6 Gy/6 Gy 0.394 0.593

MC1 TERT 1.5 Gy/1.5 Gy 0.631 0.379

MC1 TERT 6 Gy/6 Gy 0.394 0.848

p-KAP1 compared to ß-actin BJ5TA MC1 TERT MC3 TERT MC7 TERT

0 Gy /1.5 Gy 0.025 0.054 0.102 0.092

1.5 Gy/6 Gy 0.012 0.145 0.005 < 0.0001

BJ5TA 1.5 Gy /1.5 Gy 0.398 0.381 0.078

BJ5TA 6 Gy/6 Gy 0.817 0.293 0.545

MC3 TERT 1.5 Gy/1.5 Gy 0.381 0.133 0.338

MC3 TERT 6 Gy/6 Gy 0.293 0.156 0.501

MC1 TERT 1.5 Gy/1.5 Gy 0.398 0.133 0.025

MC1 TERT 6 Gy/6 Gy 0.817 0.156 0.087

p-KAP1 compared to BJ5TA MC1 TERT MC3 TERT MC7 TERT

0 Gy/1.5 Gy 0.855 0.373 0.040 1.5 Gy/6 Gy 0.395 0.584 0.885

MC3 TERT 1.5 Gy/1.5 Gy 0.551 0.262

MC3 TERT 6 Gy/6 Gy 0.872 0.558

MC1 TERT 1.5 Gy/1.5 Gy 0.551 0.219

MC1 TERT 6 Gy/6 Gy 0.872 0.664

251

Supplementary table S-17 P-values of γH2AX foci corresponding to Figure 31

BJ5TA MC1 TERT MC3 TERT MC7 TERT

0 Gy/1 Gy 1 h γH2AX foci 0.023 0.004 0.002 0.002

0 Gy/1 Gy 1 h γH2AX foci 0.0002 0.002 < 0.0001 < 0.0001

1 Gy 1 h/1 Gy 6 h γH2AX foci 0.008 0.280 0.020 0.005

1 Gy 1 h/1 Gy 6 h γH2AX foci 0.001 0.194 0.005 0.002

1 Gy 6 h/1 Gy 24 h γH2AX foci 0.007 0.093 0.024 0.031

1 Gy 6 h/1 Gy 24 h γH2AX foci 0.003 0.090 0.020 0.008

1 Gy 24 h/1 Gy 48 h γH2AX foci 0.400 0.046 0.536 0.292

1 Gy 24 h/1 Gy 48 h γH2AX foci 0.111 0.010 0.203 0.222

BJ5TA 0 Gy/0 Gy yH2AX Foci 0.334 0.648 0.163

BJ5TA 1 Gy 1 h/1 Gy 1 h yH2AX Foci 0.193 0.255 0.207




MC3 TERT 0 Gy/0Gy yH2AX Foci 0.648 0.400 0.125

MC3 TERT 1 Gy 1 h/1 Gy 1 h yH2AX Foci 0.255 0.655 0.699




MC1 TERT 0 Gy/0 Gy yH2AX Foci 0.334 0.400 0.267





252

Supplementary table S-18 P-values of 53BP1 foci corresponding to Figure 31

BJ5TA MC1 TERT MC3 TERT MC7 TERT

BJ5TA 0 Gy/0 Gy 53BP1 Foci 0.279 0.615 0.275

BJ5TA 1 Gy 1 h /1 Gy 1 h 53BP1 Foci 0.201 0.423 0.155

BJ5TA 1 Gy 6 h/1 Gy 6 h 53BP1 Foci 0.449 0.966 0.147



MC3 TERT 0 Gy/0 Gy 53BP1 Foci 0.615 0.699 0.719

MC3 TERT 1 Gy 1 h /1 Gy 1 h 53BP1 Foci 0.423 0.329 0.119

MC3 TERT 1 Gy 6 h/1 Gy 6 h 53BP1 Foci 0.966 0.525 0.433



MC1 TERT 0 Gy/0 Gy 53BP1 Foci 0.279 0.699 0.928

MC1 TERT 1 Gy 1 h /1 Gy 1 h 53BP1 Foci 0.201 0.329 0.705




Supplementary figure S-24 Predicted effects of the mutations in ABL1 and FANCL of patient MC7 on protein

sequence Gene sequence to protein sequence translation was computed with ApE-A plasmid Editor. Arrows indicate mutation sites

and squares show resulting stop codons. Western blot results of BJ5TA and MC/ TERT cells using two different antibodies

directed against the kinase domain of ABL1 are shown in the upper panel on the right-hand side. S. e.= short exposure,

l. e.= long exposure. For further information about the antibodies see subsection 3.1.2.1. Publications relating to the FANCL

mutation are listed below the lower panel.

253

Supplementary figure S-25 Predicted effects of the mutations in RAD51C and RBBP6 of patient MC3 on

protein sequence or intronic

Gene sequence to protein sequence translation was computed with ApE-A plasmid Editor. Arrows indicate

mutation sites and the square shows the resulting stop codon. A representative figure of RAD51 foci analysis in

ADP (control) and MC3 primary cells after 6 Gy IR is given on the right-hand side as previously published507

.

Splice effect analysis was computed by MaxEntScan and results shown for RBBP6 in the lower panel.

WT= wildtype MUT= mutation.

Supplementary figure S-26 Predicted effects of the mutations in HERC2 of patient MC1 and NPAT of patient

MC7 on protein sequence or splice site

254

Gene sequence to protein sequence translation was computed with ApE-A plasmid Editor. Arrows indicate

mutation sites and the square shows the resulting stop codon. Splice effect analysis was computed by

MaxEntScan and results shown for NPAT in the lower panel. WT= wildtypem MUT= mutation.

Supplementary figure S-27 RAD51 foci analysis in primary and immortalized RS cells RAD51 foci were counted 4 h after IR with 6 Gy in primary RS BC fibroblasts MC3 and MC7 in comparison to the SV40

immortalized wildtype ADP fibroblasts and median values of two biological and two technical replicates are shown on the

left-hand side of the graphs and marked by obs 1= observer one507

. Results of ADP are given in dark green , MC3 primary

cells in blue and MC7 primary cells in yellow, respectively. RAD51 foci analyzed with the same protocol but by a different

observer (obs 2, namely Katharina Stemwedel) in TERT immortalized RS BC fibroblasts of patients MC1 (light blue), MC3

(dark blue) and MC7 (yellow). The TERT immortalized wildtype fibroblast cell line BJ5TA served as control.

255

Supplementary figure S-28 CSA in 6well plates with different coating Colony survival assays fixed 14 days after no (0 Gy) or 4 Gy IR. BJ5TA, MC3 TERT and MC7 TERT cells were grown in seeding

numbers of 1500 cells per 6-well for unirradiated and 3000 cells per 6-well for irradiated plates. Uncoated, gelatin-coated

and collagen-coated 6-wells were used and colonies stained with crystal violet. Medium without and including hygromycin

(10µg/ml= 10H) was applied to the cells during culture. Arrows indicate areas of higher density cell growth, however, not

resembling colonies.

256

Supplementary figure S-29 No colony growth in 6-well plates and change of morphology of MC3 TERT cells Colony survival assay results with unirradiated BJ5TA, MC3 TERT and MC7 TERT cells seeded in uncoated 6-well plates in

two different concentrations low D= low densitiy = 1500 cells and high D= high densitiy = 3000 cells (panel A). Panels B and

C show corresponding cells after 3 weeks in culture in T25 flasks, with arrows in panel C indicating MC3 TERT colonies

growing in the middle of the flasks, as supplementation to the finding of panel F (upper figure), which shows MC3 TERT cells

growing predominantly at the edges of the flask without irradiation when seeded in higher densities. Cell numbers MC3

TERT and BJ5TA in panels B and C, respectively= 2000, MC3 TERT in panel F= 5000 cells. Panels D and E show magnification

of panels C and F and display microscopic views of colonies of unirradiated MC3 TERT cells growing in the middle and edge

of the flask, respectively. The arrow in the upper picture of panel F indicates the area of magnification shown in the lower

picture of panel F that depicts increased granularity of cells. Scale= 100µm.

Supplementary table S-19 Raw data pilot experiment senescence after irradiation

BJ5TA 0 Gy BJ5TA

4 Gy 24 h

BJ5TA

4 Gy 48 h

BJ5TA

4 Gy 7 d

MC1 TERT

0 Gy

MC1 TERT

4 Gy 24 h

MC1 TERT

4 Gy 48 h

MC1 TERT

4 Gy 7 d

59.6 39.3 37.5 32.5 36.6 32 22.6 18.6

47.1 26.3 20.9 29.6 45.7 40.6 28.2 15.7

MC3 TERT

0 Gy

MC3 TERT

4 Gy 24 h

MC3 TERT

4 Gy 48 h

MC3 TERT

4 Gy 7 d

MC7 TERT

0 Gy

MC7 TERT

4 Gy 24 h

MC7 TERT

4 Gy 48 h

MC7 TERT

4 Gy 7 d

45.3 15 14.7 12.2 43.4 20.9 21,3 9.7

49.2 28.1 17 10.3 60.9 40.0 26.9 19.9

Supplementary table S-20 Raw data senescence after irradiation in BJ5TA and MC3 TERT cells BJ5TA

0 Gy

BJ5TA

4 Gy 24 h

BJ5TA

4 Gy 48 h

BJ5TA

4 Gy 7 d

BJ5TA

4 Gy 9 d

MC3 TERT

0 Gy

MC3 TERT

4 Gy 24 h

MC3 TERT

4 Gy 48 h

MC3 TERT

4 Gy 7 d

MC3 TERT

4 Gy 9 d

59.6 39.3 37.5 32.5 45.3 15 14.7 12.2

40.3 34.9 33.5 16.3 36.1 24.5 22 7.9 7.2 2.3

50.7 45.7 32.7 44.5 24.9 25.8 23.4 11.9 10.1 7.2

45.6 39.5 31.2 39.8 24.5 22.8 21.3 9.4 6.7 9.3

257

Supplementary figure S-30 Senescence assay results analyzed by Mann-Whitney test and fitted for

exponential decay Results of senescence assays after 4 Gy IR performed in BJ5TA and MC3 TERT cells. Data is adapted from Figure 35 and

results of two-tailed Mann-Whitney tests applied by GraphPad Prism software are given in panel A for non-normalized and

in panel B for normalized values. Significance levels are indicated by p ≤ 0.05 (*) or P > 0.05 (ns = not significant). Panels C

and D show results of non-linear fit performed with GraphPad Prism software following one-phase exponential decay,

R2= coefficient of determination.

259

9 Acknowledgement

Herrn Dr. Thilo Dörk-Bousset danke ich für die Übernahme der Erstbetreuung und die

Bereitstellung des interessanten Themas. Insbesondere danke ich ihm für die Verarbeitung

und Bereitstellung der Exomsequenzierungsdaten. Der große Freiraum, der mir während der

Durchführung dieser Arbeit gewährt wurde, hat maßgeblich zu meiner wissenschaftlichen

sowie persönlichen Entwicklung beigetragen.

Herrn Professor Dr. Christiansen danke ich für die Übernahme des Erstreferats und für die

fachliche und persönliche Unterstützung. Ebenfalls vielen Dank an das Team der

Radioonkologie für die Unterstützung bei der Bestrahlung der Zellen.

Ich danke Frau Professor Dr. Tamura-Niemann für die Übernahme der Zweitbetreuung und

die produktiven Diskussionen während der Projektbesprechungen. Ebenfalls vielen Dank an

Dr. Alexandra Koch für die Bereitstellung der ABL-Antikörper.

Dr. Natalia Bogdanova danke ich für ihre Unterstützung auf wissenschaftlicher Ebene im

Rahmen der Hilfe bei der PCR-Amplifikation und Sequenzierung und für die interessanten

Diskussionen. Dr. Kristine Bousset danke ich ebenfalls für die Hilfe bei der Bewältigung

alltäglicher Schwierigkeiten des Laboralltags und die vielen fachlichen Diskussionen. Dr.

Bianca Schröder-Heurich, Dr. Sonja Helbig, Dr. Anna Otte, Hoda Radmanesh und Catharina

Melzer danke ich für das freundliche Arbeitsklima, das das Arbeiten im Labor auf fachlicher

und persönlicher Ebene bereichert hat. Ebenso danke ich Peter Schürmann, Britta Wieland

und dem gesamten Team der Molekularen Gynäkologie für das angenehme Arbeitsklima und

die Hilfe im Labor. Britta Wieland danke ich im Besonderen für Ihre Unterstützung während

der schwierigen Etablierung des Immortalisierungsprotokolls und Julia Enssen sowie Louisa

Weinhold für ihre Hilfe bei der Validierung der vielen Mutationen. Vielen Dank an Maike

Willers für Ihre Untersuchungen während ihres Praktikums und insbesondere Katharina

Stemwedel für die optimale Zusammenarbeit und das positive Arbeitsklima während der

Durchführung ihrer Bachelorarbeit und anschließender HiWi-Tätigkeit.

Der Arbeitsgruppe von Dr. Robert Geffers am Helmholtz-Zentrum in Braunschweig danke ich

für die Kooperation die Durchführung der Exomsequenzierung betreffend. Vielen Dank an

Prof. Dr. Axel Schambach für die Bereitstellung des Nukleofektors. Professor Dr. Detlev

Schindler, PD Dr. Kerstin Borgmann, Dr. Margret Rave-Fränk und Prof. Dr. Markus Stumm

danke ich für die Bereitstellung der Patientenzellen.

Vielen herzlichen Dank an meine lieben Eltern, die mich während all meiner Vorhaben stets

unterstützt haben. Ich danke Euch für Euer immer offenes Ohr und insbesondere dafür, dass

Ihr mir immer wieder Mut gemacht und mir beigebracht habt, dass es sich stets lohnt, stark

zu bleiben und nicht aufzugeben. Ein besonderer Dank gilt Dir, Holger, für Deine

bedingungslose Unterstützung nicht nur während der Höhen und Tiefen dieser Arbeit,

sondern auch dafür, dass Du in den letzten 10 Jahren immer für mich da warst. Mit deiner

positiven Art hast Du mir stets Kraft gegeben. Vielen Dank natürlich auch an meine Freunde

für die tolle Unterstützung, ihre Anteilnahme und Motivation, die mich durch diese Arbeit

geführt haben.

261

Hannover, den 29.11.2017

Publications and contributions

Journal article:

Pfeifer K, Schürmann P, Bogdanova N, Neuhäuser K, Kostovska IM, Plaseska-Karanfilska D,

Park-Simon TW, Schindler D, Dörk T Frameshift variant FANCL*c.1096_1099dupATTA is not

associated with high breast cancer risk. Clinical Genetics 2016:n/a-n/a. doi: 10.1111/cge.12837.

Conference paper and oral presentation:

Neuhäuser K, Bogdanova N, Bhuju S, Geffers R, Christiansen H, Dörk T, Rave-Fränk M

Mutation in FANCO/RAD51C, but not FANCL, is Associated with Clinical and Chromosomal

Radiosensitivity. Experimentelle Strahlentherapie und Klinische Strahlenbiologie, 2016:31-37.

Conference paper and poster presentation:

Neuhäuser K, Bogdanova N, Borgmann K, Dahm-Daphi J, Schindler D, Christiansen H, Dörk T Evidence for elevated basal levels of TPT1, but no induction after irradiation, in

lymphoblastoid cells from individuals with increased clinical radiosensitivity.

Experimentelle Strahlentherapie und Klinische Strahlenbiologie, 2017:24-30.

Bogdanova N, Jguburia N, Neuhäuser K, Wieland B, Stamm G, Wacker F, Christiansen H, Dörk

T Chromosomal radiosensitivity of breast epithelial cells and lymphocytes in repeated

diagnostic CT scans. International Wolfsberg Meeting on Molecular Radiation

Biology/Oncology, Ermatingen, Switzerland, 2017:36.

Manuscripts:

Neuhäuser K, Küper L, Bogdanova N, Willers M, Wieland B, Christiansen H, Dörk T.

Assessment of the role of TPT1 in ATM signaling and breast cancer susceptibility. Radiation

research (accepted with major revision requirements)


Dörk T. Chromosomal radiosensitivity of breast epithelial cells and lymphocytes in

repeated diagnostic CT scans. Radiology (in review)

262

Erklärung

Hiermit erkläre ich, dass ich die Dissertation (“Impact of the DNA damage response in clinical

and cellular radiosensitivity of cancer patients“) selbstständig verfasst habe. Bei der

Anfertigung wurden folgende Hilfen Dritter in Anspruch genommen:

Dr. Thilo Dörk-Bousset Betreuung der Doktorarbeit

Ich habe keine entgeltliche Hilfe von Vermittlungs- bzw. Beratungsdiensten

(Promotionsberater oder anderer Personen) in Anspruch genommen. Niemand hat von mir

unmittelbar oder mittelbar entgeltliche Leistungen für Arbeiten erhalten, die im

Zusammenhang mit dem Inhalt der vorgelegten Dissertation stehen. Ich habe die

Dissertation an folgender Institution angefertigt:

Klinik für Strahlentherapie und Spezielle Onkologie, Arbeitsgruppe Experimentelle Radioonkologie,

Medizinische Hochschule Hannover

Die Dissertation wurde bisher nicht für eine Prüfung oder Promotion oder für einen

ähnlichen Zweck zur Beurteilung eingereicht. Ich versichere, dass ich die vorstehenden

Angaben nach bestem Wissen vollständig und der Wahrheit entsprechend gemacht habe.

Ort, Datum Unterschrift

263

Electronic appendix

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