Hodgkin and Reed-Sternberg cells harbor alterations in the major tumor suppressor pathways and...

doi:10.1182/blood-2002-04-1128Prepublished online September 12, 2002;

and Miguel A PirisFrancisco Mazorra, Javier Menarguez, Maria J Mestre, Manuela Mollejo, Ana I Saez, Lydia Sanchez

Martinez,Alavaro, Carmen Bellas, Angel Castano, Ana Diez, Teresa Flores, Carmen Martin, Miguel A Juan F Garcia, Francisca I Camacho, Manuel Morente, Maximo Fraga, Carlos Montalban, Tomas tissue-microarraystumor suppressor pathways and cell-cycle checkpoints: analyses using Hodgkin's and Reed-Sternberg cells harbor alterations in the major

(795 articles)Oncogenes and Tumor Suppressors � (4217 articles)Neoplasia � (231 articles)Cell Cycle �

Articles on similar topics can be found in the following Blood collections

http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#repub_requestsInformation about reproducing this article in parts or in its entirety may be found online at:

http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#reprintsInformation about ordering reprints may be found online at:

http://bloodjournal.hematologylibrary.org/site/subscriptions/index.xhtmlInformation about subscriptions and ASH membership may be found online at:

articles must include the digital object identifier (DOIs) and date of initial publication. priority; they are indexed by PubMed from initial publication. Citations to Advance online prior to final publication). Advance online articles are citable and establish publicationyet appeared in the paper journal (edited, typeset versions may be posted when available Advance online articles have been peer reviewed and accepted for publication but have not

Copyright 2011 by The American Society of Hematology; all rights reserved.Washington DC 20036.by the American Society of Hematology, 2021 L St, NW, Suite 900, Blood (print ISSN 0006-4971, online ISSN 1528-0020), is published weekly

For personal use only. by guest on May 30, 2013. bloodjournal.hematologylibrary.orgFrom

http://bloodjournal.hematologylibrary.org/cgi/collection/cell_cycle

http://bloodjournal.hematologylibrary.org/cgi/collection/neoplasia

http://bloodjournal.hematologylibrary.org/cgi/collection/oncogenes_and_tumor_suppressors

http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#repub_requests

http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#reprints

http://bloodjournal.hematologylibrary.org/site/subscriptions/index.xhtml

http://bloodjournal.hematologylibrary.org/subscriptions/ToS.dtl

http://bloodjournal.hematologylibrary.org/


Hodgkin’s and Reed-Sternberg cells harbor alterations in the

major tumor suppressor pathways and cell-cycle checkpoints:

analyses using tissue-microarrays

Juan F. García,1 Francisca I. Camacho,1 Manuel Morente,1 Máximo Fraga,3 Carlos

Montalbán,4 Tomás Álvaro,6 Carmen Bellas,5 Ángel Castaño,7 Ana Díez,2 Teresa

Flores,8 Carmen Martín,9 Miguel A. Martínez,10 Francisco Mazorra,11 Javier

Menárguez12, Maria J. Mestre,13 Manuela Mollejo,14 Ana I. Sáez,1 Lydia Sánchez,2 and

Miguel A. Piris,1 for the Spanish Hodgkin’s Lymphoma Study Group.

From the Lymphoma Group, Molecular Pathology Program,(1) and

Immunohistochemistry and Histology Unit,(2) Centro Nacional de Investigaciones

Oncológicas, Madrid. Dpto. Anatomía Patológica,(3) Hospital C.U., Santiago de

Compostela. Dpto. Medicina Interna(4) and Anatomía Patológica,(5) H. Ramón y Cajal,

Madrid. Dptos. Anatomía Patológica, H. Verge de la Cinta, Tortosa,(6) H. Severo

Ochoa, Leganés,(7) H.C. Salamanca,(8) H.U.C. San Carlos, Madrid,(9) H.U. 12 de

Octubre, Madrid,(10) H. M. Valdecilla, Santander,(11) H. Gregorio Marañón,(12) H.

Móstoles, Madrid,(13) and H. Virgen de la Salud, Toledo.(14) SPAIN

Running title: Cell cycle and apoptosis deregulation in H/RS cells

Scientific Section Heading: Neoplasia

27 pages, including 4 tables and 4 figures.

Total word count: 5.241

Abstract word count: 250

Supplementary Information will be given in the web page

This study was supported by grants from the Comunidad Autónoma de Madrid

(08.1/0028.1/2000), and the Ministerio de Ciencia y Tecnologia (grants 1FD97-0431

and SAF2001-0060), Spain.

Address for correspondence and reprint requests: Juan F García, Molecular Pathology

Program. Centro Nacional de Investigaciones Oncológicas. C/ Melchor Fernández

Almagro 3, E-28029 Madrid, Spain. Phone: +34 91 224 69 00. Fax: +34 91 224 69 23.

E-mail: [email protected]

Copyright (c) 2002 American Society of Hematology

Blood First Edition Paper, prepublished online September 12, 2002; DOI 10.1182/blood-2002-04-1128 For personal use only. by guest on May 30, 2013. bloodjournal.hematologylibrary.orgFrom



Juan F García. Cell cycle and apoptosis deregulation in H/RS cells 2

Hodgkin’s and Reed-Sternberg cells harbor alterations in the

major tumor suppressor pathways and cell-cycle checkpoints:

analyses using tissue-microarrays

ABSTRACT

Tumoral cells in Hodgkin’s Lymphoma (HL) display an increased growth fraction and

diminished apoptosis, implying a profound disturbance of the cell cycle and apoptosis

regulation. However, limitations of molecular techniques have prevented the analysis of

the tumor suppressor pathways and cell-cycle checkpoints. Tissue Microarray (TMA) is

a powerful tool for analyzing a large number of molecular variables in large series of

tumors, although the feasibility of this technique has not yet been demonstrated in

heterogeneous tumors.

The expression of 29 genes regulating the cell cycle and apoptosis were analyzed by

immunohistochemistry and ISH in 288 HL biopsies using TMA. The sensitivity of the

technique was validated by comparing the results with those obtained in standard

tissue sections.

The results revealed multiple alterations in different pathways and checkpoints,

including G1/S, G2/M transition and apoptosis. Striking findings were the

overexpression of Cyclin E, CDK2, CDK6, STAT3, Hdm2, Bcl2, Bcl-XL, Survivin, and

NF-kappaB proteins.

A multiparametric analysis identified proteins associated with increased growth fraction

(Hdm2, p53, p21, Rb, Cyclins A, B1, D3, E, CDK2, CDK6, SKP2, Bcl-XL, Survivin,

STAT1, and STAT3), and proteins associated with apoptosis (NF-kappaB, STAT1, and

RB). The analysis also demonstrated that EBV+ cases displayed a characteristic

profile, confirming the pathogenic role of EBV in HL.

Survival probability depends on multiple biological factors, including overexpression of

Bcl2, p53, Bax, Bcl-XL, MIB1 and apoptotic index.

In conclusion, H/RS cells harbor concurrent and overlapping alterations in the major

tumor suppressor pathways and cell-cycle checkpoints. This appears to determine the

viability of the tumoral cells and the clinical outcome.

Scientific Section Heading: Neoplasia

Corresponding author’s e-mail address: [email protected]





INTRODUCTION

Hodgkin’s Lymphoma (HL) is a distinct primary solid malignancy of the immune system

in which the exuberant production of cytokines and chemokines is associated with an

abundance of a component of inflammatory cells that outnumber the recognized

tumoral subpopulation of Hodgkin’s and Reed-Sternberg (H/RS) cells. These H/RS

cells harbor clonally rearranged and somatically mutated immunoglobulin genes,

indicating that, in most cases, they are derived from germinal center B cells.1

Despite the progress made in the understanding of the biology of HL, the transforming

events in these cells remain to be elucidated. In normal lymphoid tissues, germinal

center B cells lacking expression of functional high affinity Ab inevitably suffer

apoptosis under normal physiological conditions,2 while H/RS cells escape

programmed cell death, and instead proliferate and disseminate clonally by unknown

means.

The analysis of cell cycle regulation in different types of lymphoid and epithelial

neoplasms reveals a relationship whereby increased clinical aggressiveness is

associated with the accumulation of genetic and epigenetic alterations,3 which lead to

the dismantling and inactivation of the main tumor suppressor pathways: p14ARF-p53-

p21WAF1, p16INK4A-Rb and p27KIP1. Thus, although some low-grade lymphomas exhibit

alterations that are limited to apoptosis control, large cell and Burkitt lymphomas tend

to display concurrent and concerted inactivation of these tumor suppressor pathways,3,4

which finally turns them into neoplasms with an extremely high growth fraction and

resistance to standard chemotherapy.

The alterations in the main pathways responsible for controlling the cell cycle in HL

have only rarely been studied and are poorly understood, mainly because the

techniques used for molecular analyses in this disease have been limited by the

scarcity of tumoral cells. Previous studies have shown some relationships between the

expression of cell cycle proteins and patient outcome.5 The incidence of p53 mutations

has been investigated in H/RS cells and is known to be significantly lower than in other

neoplasias.6 Nonetheless proteins regulating the function of p53, such as p14ARF and

Hdm2 are expressed aberrantly and may have an indirect role in regulating the function

of p53.7 On the other hand, the Rb pathway is disrupted by p16INK4a methylation in

some cases.8 The NF-kappaB (p65/RelA) pathway is constitutively activated in different

HL-derived cell lines and tumors,9,10 partially explaining the resistance of H/RS cells to





apoptosis. The NF-kappaB activation can be related to IkappaBalpha gene mutations

in EBV-negative HL cases,11 but not in EBV-positive cases, indicating a characteristic

regulation of these cases. Other studies have shown disorder in the S-phase,12,13

frequent aneuploidy 14,15 of the tumoral cells, and suggested the presence of structural

anomalies during mitosis that lead to the formation of the characteristic multinucleated

cells.16

The high proliferative index 17,18 and resistance to apoptosis in germinal-center-derived

cells,19,20 such as H/RS cells, that produce no functional immunoglobulin, suggest that

the control of the cell cycle in these cells is seriously disrupted, and highlights the

interest in additional studies that might clarify this issue.

The recently developed Tissue Microarray (TMA) technology allows simultaneous

analyses of hundreds of tissue specimens for numerous molecular targets 21,22 by using

the techniques of immunohistochemistry (IHC), in situ hybridization (ISH) and FISH.

This technology also has the potential to significantly accelerate progress in the search

for associations between molecular changes and clinical traits.23 This tool has proved

to be remarkably useful in evaluating different cancer types, particularly those with

homogeneous histology. However, the feasibility of this technique for analyzing highly

heterogeneous tumors such as HL remains to be elucidated. Recent studies using

TMA 24 have shown the potential of this technology for restricted analyses in HL.

IHC and ISH techniques can contribute significantly to the identification of an

expression profile of cell cycle markers in H/RS cells. However, due to the paucity of

such cells, we decided to investigate whether TMA technology can also be used in this

heterogeneous tumor and in large-scale analyses. With the aim of evaluating the

alterations in the expression of essential cell cycle regulatory proteins, we performed a

series of IHC and ISH analyses of 29 different markers in 288 HL cases. This revealed

different alterations affecting the main checkpoints of the cell cycle, in G1/S and G2/M

transition, and involving all the major pathways simultaneously.

MATERIAL AND METHODS

HL samples and cell lines

288 retrospective cases of HL were collected by collaborating members of the Spanish

Hodgkin’s Lymphoma Study Group. Cases were randomly selected, diagnosed in the





period between 1994 and 1998, stages being evaluated according to standard

protocols and treated with standard polychemotherapeutic regimes (including

adriamycin in the majority of cases) with or without adjuvant radiotherapy. Paraffin

blocks were selected only on the basis of the availability of suitable formalin-fixed

paraffin-embedded tissue (at least 1 mm thick). All the samples included represent at-

diagnosis biopsies; any relapse biopsies were discarded beforehand. The histological

confirmation of HL and subtype was achieved in 277 cases by central review using

standard tissue sections, and diagnoses were made according to the criteria of the

WHO classification,25 with the help of CD30, CD15, CD20, ALK and HE staining. Cases

included 149 cases of nodular sclerosis HL, 99 cases of mixed cellularity HL, 12 cases

of lymphocyte-rich classical HL, 7 cases of lymphocyte depletion HL, 9 cases of

nodular lymphocyte-predominant HL (NLPHL), and 1 case of unclassifiable HL.

Paraffin-embedded blocks from reactive lymphoid tissue and different B- and T-cell

lymphoma samples were obtained from the tissue archives of the CNIO Tumor Bank.

Five HL-derived cell lines (L428, HDLM2, L540, KMH2, and HD-MY-Z) were obtained

from the German Collection of Microorganisms and Cell Cultures (DSMZ,

Braunschweigh, Germany).

Tissue-Microarray design

We used a Tissue Arrayer device (Beecher Instrument, MD) to construct the TMAs. All

HL cases were histologically reviewed and the richest areas of H/RS cells were marked

in the paraffin blocks. Two selected 1-mm-diameter cylinders from two different areas

were included in each case, along with 43 different controls to ensure the quality,

reproducibility and homogenous staining of the slides. Thus, four different TMA blocks

were constructed, each containing 187 cylinders.

Internal controls were provided by cell lines, normal lymphoid tissue, and different B-

and T-cell lymphomas. Five EBV-negative HL-derived cell lines, with known cell cycle

alterations were used: L428, HDLM2, L540, KMH2, and HD-MY-Z. These cell lines

were grown following standard protocols, fixed in formalin and included in paraffin as

previously described.26 Included in each TMA were a representation of reactive

lymphoid tissue (10 samples, including tonsil, spleen, and lymphadenitis), and the most

frequent non-Hodgkin’s lymphomas, of which there were 28 samples: duplicated

cylinders from B-CLL (2 cases), FCL (2 cases), MCL (2 cases), DLBCL (2 cases), BL





(2 cases, EBV-positive and -negative), PTCL (2 cases, EBV-positive and -negative),

and ALCL (2 cases).

Immunohistochemistry

TMA blocks were sectioned at a thickness of 3 µm, dried for 16h at 56ºC before being

dewaxed in xylene and rehydrated through a graded ethanol series, and washed with

phosphate-buffered saline. Antigen retrieval was achieved by heat treatment in a

pressure-cooker for 2 min in 10mM citrate buffer (pH 6.5). Before staining the sections,

endogenous peroxidase was blocked.

Immunohistochemical staining was performed on these sections using 27 different

antibodies (Abs), described in table 1. After incubation, immunodetection was

performed with the LSAB Visualization System (DAKO, Glostrup, Denmark) employing

diaminobenzidine chromogen as substrate. Sections were counterstained with

hematoxylin.

The staining of the TMA sections was evaluated by two different pathologists (JFG,

FC), using uniform criteria. In order to guarantee the reproducibility of this method, we

decided to employ straightforward and clear-cut criteria. Briefly, the pattern of staining

for each Ab was recorded as positive or negative, and high or low expression, taking

into account the expression in H/RS cells and different cut-offs for each marker (table

1).

Some exceptions to these rules were: 1) Cytoplasmic STAT1, STAT3, and NFkappaB

expression can generally be found in normal lymphoid cells and in H/RS cells. In this

study, we considered positive cases only when nuclear expression in the tumoral cells

could be seen without difficulty, indicating the activated form of these proteins.9 2) p53

nuclear overexpression is a well-known phenomenon in HL, so we considered cases

with high expression when more than 80% of tumoral cells were strongly positive. 3)

Bcl2 and other antiapoptoic regulators (Bcl-XL, Survivin) overexpression was

considered only when more than 50% of H/RS cells strongly expressed the protein.

Cases with only faint cytoplasmic expression in some tumoral cells were classified as

negative. 4) Cyclin D1 expression is considered abnormal in lymphoid cells, being

positive only in tumoral cells from MCL, MM, and some PLL. Therefore, those HL

cases displaying any kind of expression in H/RS cells were considered to be positive.





Although the reactivity of most of the antibodies here used have been validated in

different previous studies, we cannot fully exclude that undescribed reactivities of the

antibodies or the technique here used may affect some of the results.

In situ detection of apoptosis and EBER in situ hybridization

Apoptosis was detected using the ApopTag Peroxidase In Situ Apoptosis Detection Kit

(Intergen Co., Oxford, UK), based on the TdT-mediated biotin-dUTP nicked-end

labeling (TUNEL) methodology. Briefly, TMA sections were pre-treated with proteinase

K for 15 min, and then incubated with TdT enzyme for 1 hour at 37ºC and afterwards

with anti-digoxigenin peroxidase conjugate for 1 hour. Color was developed with 3, 3’

diaminobenzidine tetrahydrochloride (10 min) and counterstained with hematoxylin.

EBV was detected by in situ hybridization with Fluorescein-Conjugated Epstein-Barr

Virus (EBER) PNA probe (DAKO). This probe is complementary to the two nuclear

EBER RNAs encoded by the Epstein-Barr virus. TMA sections were pre-treated with

proteinase K for 10 min at 37ºC, and then incubated with EBER PNA probe 1.5 hours

at 55ºC in humid chamber and afterwards washed with Stringent Wash Solution, 25

min at 55ºC in a water bath with shaking. Detection was performed with anti-FITC

antibody (clone DAK-FITC4, from DAKO) diluted at 1:100. After incubation,

immunodetection was performed with biotinylated anti-mouse immunoglobulins,

followed by peroxidase-labeled streptavidin (LSAB Visualization System, DAKO) with

diaminobenzidine chromogen as substrate. Sections were counterstained with

hematoxylin.

Validation of the technique

The reproducibility of the results thus obtained was confirmed by comparing them with

those from whole sections in 42 randomly selected cases, stained using the same

procedures for some of the Abs and probes used in this study, and for other markers

routinely in use in HL that have variable and well-known expression in H/RS cells.

Specifically, we evaluated the expression of CD20, CD30, CD15, LMP, Bcl2, Bcl6, p53,

PTEN, p16, and EBER-ISH.





Table 1. Abs used in the analyses, indicating source, dilution, threshold and pattern of reactivity used, and positive controls.

Protein Clone Source Dilution Reactivity Threshold Internal control

Ki67 MIB1 DAKO 1:100 High / low > 50% positive H/RS cells Proliferating cells

Bcl2 124 DAKO 1:25 High / low > 50% positive H/RS cells with strong expression Small lymphocytes

Bax POLYCLONAL Santa Cruz 1:1000 positive/negative > 10% positive H/RS cells Benign B-lymphocytes

Bcl-XL 2H12 ZYMED 1:10 High / low > 50% positive H/RS cells with strong expression HL-derived cell lines

Mcl1 POLYCLONAL DAKO 1:100 High / low > 50% positive H/RS cells with strong expression Proliferating cells

Survivin POLYCLONAL RD Systems 1:1500 High / low > 50% positive H/RS cells with strong expression HL-derived cell lines

p65/RelA F-6 (p65) Santa Cruz 1:2000 positive/negative Nuclear expression in H/RS cells HL-derived cell lines

Cyclin A 6E6 Novocastra 1:100 positive/negative > 10% positive H/RS cells Proliferating cells (G2/M)

Cyclin B1 7A9 Novocastra 1:25 positive/negative > 10% positive H/RS cells Proliferating cells (G2/M)

Cyclin D1 DCS-6 DAKO 1:100 positive/negative Any positive H/RS cells Macrophages and endothelial cells

Cyclin D3 DCS-22 Novocastra 1:10 positive/negative > 10% positive H/RS cells Proliferating cells

Cyclin E 13A3 Novocastra 1:10 positive/negative > 10% positive H/RS cells TMA controls, proliferating cells

CDK1 1 Transduction Lab 1:1500 positive/negative > 10% positive H/RS cells TMA controls, proliferating cells

CDK2 8D4 NeoMarkers 1:500 positive/negative > 10% positive H/RS cells TMA controls, proliferating cells

CDK6 K6.83 Chemicon 1:10 positive/negative > 10% positive H/RS cells TMA controls

Bcl6 PG-B6p DAKO 1:10 positive/negative > 10% positive H/RS cells CG B-cells and B-cell lymphomas

SKP2 1G12E9 ZYMED 1:10 positive/negative > 50% positive H/RS cells Proliferating cells

STAT1 C-136 Santa Cruz 1:50 positive/negative Nuclear expression in H/RS cells Reactive lymphocytes and macrophages

STAT3 F-2 Santa Cruz 1:500 positive/negative Nuclear expression in H/RS cells Reactive lymphocytes and macrophages

PTEN 28H6 Novocastra 1:500 positive/negative Expression in H/RS cells similar to benign cells Normal cells

P53 DO-7 Novocastra 1:50 High / low > 80% positive H/RS cells Scattered GC cells

P21 EA10 Oncogene 1:50 High / low > 50% positive H/RS cells Scattered GC cells

P16 POLICLONAL Santa Cruz 1:50 High / low Expression in H/RS cells similar to benign cells Normal cells

P27 57 Transduction Lab 1:1000 High / low > 50% positive H/RS cells Resting lymphoid cells

Hdm2 IF2 (Mdm2) Oncogen 1:10 High / low > 50% positive H/RS cells TMA internal controls, macrophages, and endothelial cells

Rb G3-245 BD PharMingen 1:250 High / low > 50% positive H/RS cells Proliferating cells

EBV-LMP CS1-4 Novocastra 1:250 positive/negative Cytoplasmic and membranous expression in H/RS EBV-positive TMA controls

F

or personal use only. by guest on M

ay 30, 2013. bloodjournal.hem

atologylibrary.orgF

rom




Statistical study

The Pearson chi-square test and Fisher’s exact test were used where appropriate to

establish whether there were any relationships between the different markers included

in this study. Differences were considered to be significant for values of p<0.05.

Survival analyses were performed of all the classical HL cases for which clinical

information was available (approximately 70%). Actuarial survival curves, in terms of

Overall Survival (OS) were plotted using the Kaplan and Meier method. Statistical

significance of associations between individual variables and OS was determined by

using the log-rank test. Cox’s proportional hazard univariate analysis was also

performed independently for each variable, estimating values of the relative risk (RR),

chi-square and p. All the statistical analyses were performed using the software

package SPSS.

RESULTS

With this design, 89.3% individual core biopsies were found to include identifiable H/RS

cells. As each TMA included two different core cylinders from the same patient, this

resulted in 95.3% of cases being considered as having TMA results that could be

evaluated (Figure 1). An analysis comparing both core samples from the same cases

showed a concordance of 87%.

Figure 1. TMA design: distribution of core cylinders in TMAs (left). Preservation of

morphology, antigen preservation, and representativity of these samples is shown in

one of these cylinders, corresponding to nodular sclerosis HL, stained for H/E (middle)

and CD30 (right). Original magnification 40x; CD30 inset 600x.





To validate the chosen approach, the results obtained from the staining of 10 different

Abs and probes using TMAs were compared in a series of 42 randomly selected cases

with those obtained in the analysis of whole sections. These proved to be highly

reproducible (table 2). The overall concordance was 93.8%, a figure that accords with

previously reported results for other tumoral models,27 where concordances of greater

than 90% have been recorded when comparing results from the use of TMAs with

whole sections.

Table 2. Evaluation of IHC results in whole sections by comparison with TMA

results: number of concordant cases/number of evaluable cases. Percentage

concordance is shown in brackets. All the cases correspond to classical HL samples.

Concordant results between whole

sections and TMA cores

CD20 32/39 (82.5%)

CD30 38/38 (100%)

CD15 36/39 (92.3%)

BCL2 35/39 (89.8%)

BCL6 37/41 (90.2%)

P53 39/39 (100%)

P16 30/37 (81.1%)

PTEN 35/35 (100%)

LMP 37/37 (100%)

EBER 41/41 (100%)

Overall concordance: 93.5%





Immunohistochemistry

Threshold reactivity was defined for each Ab according to the characteristics of the

staining, giving priority to the ease of reproducibility of results. Internal control was

provided in each case by the reactivity of accompanying lymphocytes and

macrophages, or the cylinders included in the TMA for control purposes. Figure 2

shows the common pattern of expression for each Ab, and a summary of the results is

shown in Table 3.

As part of the validation process, the immunohistochemical expression of LMP protein

from EBV virus was analyzed and the results compared with those of EBER ISH. A

concordance of nearly 100% was found, thus confirming the specificity of this system.

Additionally, the different control samples illustrated the expression pattern for the

proteins analyzed and provided internal controls for EBER ISH and TUNEL techniques.

As expected, proliferating cells in normal tissue samples showed expression of MIB1,

cyclins A, B1, and D3, CDK1 and 2, SKP2, and Rb, but were negative for p27, whose

expression is opposed to proliferation. Tumor suppressor genes such as PTEN and

p16 were expressed in most cells in normal tissues, whereas only scattered lymphoid

cells in the germinal centers were p53- or Hdm2-positive. The levels of Cyclin D1 and

CDK6 were undetectable in normal lymphoid cells. STAT1 and STAT3 expression was

associated with proliferating cells, markedly in EBV-infected tissues such as those with

infectious mononucleosis. Cytoplasmic p65/RelA expression could be seen in most

lymphocytes, but nuclear protein was undetectable in normal lymphoid cells. The

pattern of expression of Bcl2, Bax, Bcl-XL, Survivin, and Bcl6 in lymphoid tissue has

been described elsewhere 28,29.

In the HL-derived cell lines, overexpression and/or loss of some oncogenes, tumor

suppressor genes, STAT proteins, and p65/RelA have been previously described 7, 30, 31. Our results from the TMAs confirmed these observations and also revealed the

frequent expression of PTEN, Cyclins A, B1, E, CDK1, 2, 6, and Rb. Finally, the

analysis of the different lymphoma samples included in these TMAs demonstrated the

pattern of expression for each protein, provided internal controls for markers such as

Cyclin D1 in MCLs or Bcl2 and Bcl6 in FCLs or DLBCLs, and also delineated the

differences between low-growth fraction lymphomas (indolent lymphomas, such as

CLL, FCL, or MCL, showing low-level expression of Cyclins, p53 and CDKs and

expressing CDKIs) and high-growth fraction lymphomas (aggressive lymphomas, such





as DLBCL, BL, ALCL, and PTCL, with high-level expression of Cyclins and CDKs,

frequent expression of p53 and loss of some CDKIs, and generally expressing Bcl6).





Figure 2. IHC and ISH patterns: Samples with positive and negative (or high vs. low

expression) for each marker are shown. All these cases are representative of classical

HL, with either nodular sclerosis or mixed cellularity. Original magnification for Cyclins,

MIB1, Rb, p53, p27, p65/RelA, Bcl6, TUNEL, and EBER 1000x; remaining panels

600x.





Table 3: IHC and ISH results, indicating number of positive cases (percentage).

The different markers are ordered by the percentage of positive cases in the series

(see also additional information).

Marker Positive cases (%)

PTEN 258/258 (100%)

Bax 259/266 (97.4%)

Cyclin A 262/271 (96.7%)

Cyclin B1 239/257 (93%)

Cyclin E 231/257 (89.9%)

Survivin 234/262 (89.3%)

STAT1 236/267 (88.4%)

CDK1 269/264 (86.7%)

SKP2 226/268 (84.3%)

CDK2 223/265 (83.8%)

P21 218/270 (80.7%)

TUNEL 169/210 (80.5%)

P65/RelA 196/257 (76.3%)

P16 189/259 (73%)

Hdm2 171/244 (70.1%)

STAT3 145/261 (55.6%)

MIB1 121/265 (45.7%)

Rb 102/262 (38.9%)

CyclinD3 103/267 (38.6%)

EBER 98/256 (38.3%)

LMP 96/252 (38.1%)

Bcl2 61/264 (23.1%)

P27 59/256 (23.0%)

CDK6 54/262 (20.6%)

Bcl-XL 50/260 (19.2%)

P53 41/265 (15.5%)

Bcl6 24/254 (9.4%)

Mcl1 18/263 (6.8%)

Cyclin D1 14/270 (5.2%)





Considering these results together, it seems that H/RS cells express Cyclins and CDKs

involved in G1/S transition (Cyclin D, Cyclin E1, CDK2, CDK6), G2/M transition (Cyclin

A, Cyclin B1, CDK1), and molecules involved in apoptosis control (p65/RelA, Bcl2, Bcl-

XL, Survivin, and Bax). At the same time they exhibit markers suggestive of dysfunction

of the major tumor suppressor pathways, such as high p53 and Hdm2 staining,

frequent loss of p27KIP1 and also p16INK4A in a number of cases, with increased

expression of SKP2.

Some of the most striking findings were the overexpression of Cyclin E, CDK2, and

CDK6, and the increased nuclear expression of p65/RelA, STAT1 and STAT3.

Thus, in 89.9% of cases, H/RS cells showed stronger Cyclin E staining than that

observed in the reactive germinal centers included for control within the TMA. Similar

findings have been observed for CDK2, the normal partner of Cyclin E, whose

overexpression could be detected in 83.8% of samples. Lower percentages of positive

cases were observed for CDK6 (21%), Cyclin D3 (39%) and Cyclin D1 (5%). A high

degree of expression of Cyclin A and Cyclin B1 was also observed in nearly all cases

(97 and 93%, respectively).

In this series, nuclear p65/RelA could also be demonstrated in 76.3% of cases, with a

clear difference from the results obtained in reactive germinal centers, where nuclear

p65/RelA was only rarely detected. Survivin expression was found in 89.3% of cases.

Nuclear STAT1 and STAT3 staining of H/RS cells was detectable in up to 88% and

56% of samples, respectively. In this case there was also a marked difference in

comparison with the rarity of either or both transcription factors in reactive lymphocytes,

with the sole exception of Infectious Mononucleosis control cases.

Cyclin D1, besides its expected presence in endothelial cells and macrophages, was

unexpectedly found in H/RS cells in 5% of samples. Nuclear PTEN was demonstrable

in all cases, in reactive and tumoral cells. Bcl6 was observed in the majority of NLPHL

(67%), and also in a small proportion (7.3%) of classical HL cases.

Classical HL vs. Lymphocyte Predominance HL

The comparison of the expression profiling of classical HL with NLPHL revealed

differences in the profile between the two types of HL. These differences were





significant even though few NLPHL cases were included. Thus, NLPHL cases were

more frequently negative for EBV (0% positive cases vs. 39.5% in classical HL,

p=0.020), p65/RelA (37.5% vs. 77.5%, p=0.020), CDK2 (37.5% vs. 85.2%, p=0.003),

p16 (37.5% vs. 74.1% in classical HL, p=0.035), and Bcl2 (0% vs. 23.9%, p=0.048);

and they were commonly positive for Bcl6 (66.7% vs. 7.3%, p=0.000). (p values are

those associated with calculated Fisher’s exact test statistics)

Relationship between different markers

The relationships between the different markers are illustrated in Figure 3. Statistical

analysis using the Pearson and Fisher’s exact tests revealed a large number of

significant associations between different characters (see also additional information).

All NPLHL cases were EBV negative. In classical HL, the presence of EBV virus was

more frequent in MC types than in other subtypes (64.6% vs. 20.2%, p=0.000). The

presence of EBV virus in this series appears to be directly associated with STAT1 and

STAT3 expression, while there is an inverse relation with Cyclin E, CDK6, p27, p53,

Hdm2, and Bcl-XL. This confirms the role that EBV plays in this disease. It is of

particular note that EBV presence is strongly associated with STAT1 and STAT3

expression.

One of the most striking associations is that established between MIB1 and apoptosis.

In addition, growth fraction, as detected by MIB1, is associated with a large set of

markers including STAT1 and STAT3, CDK1, CDK2, CDK6, SKP2, Cyclins B1, D3,

and E, Hdm2, p53, p21, Rb, Bcl-XL, and Survivin. The strongest relationships were

found for SKP2 and STAT3.

Apoptosis rate, as measured with TUNEL, was related with nuclear p65/RelA, Rb and

STAT1 expression. At the same time, both MIB1 and TUNEL were closely related.

Cyclin E appears to have a more ubiquitous relationship, being directly related with

Cyclin A and B1, MIB1, p21, p27, Rb, SKP2, STAT1, STAT3, CDK1, CDK2, CDK6 and

p65/RelA. Of particular relevance is the strong relationship between Cyclin E and

p65/RelA identified here.

NF-kappaB (p65/RelA) is also one of the most widely related markers, as shown by two

x two contingency analyses, since in this series its expression is associated with p21,





p16, p27, Rb, Cyclin E, Cyclin D3, CDK1, CDK2, SKP2, STAT1, STAT3, Survivin, and

TUNEL.

Lastly, Bcl6 expression is strongly opposed to p27 in this series. This finding is

reminiscent of what may be observed in reactive germinal centers. At the same time,

Cyclin D3 is simultaneously expressed with Bcl6.

Figure 3: Chi-square tests: Most significant results. p values of Pearson or Fisher’s

exact (italic) test are indicated. Inverse relationships between pairs of markers are

indicated with an asterisk (*)

Relationship with survival probability

The survival analyses, restricted to classical HL cases, were done in those cases for

whom a complete clinical follow-up was available. The results of survival analyses

using Kaplan-Meier and Cox regression models are shown in table 4. Shorter OS was

significantly related with high apoptotic index (TUNEL), high proliferative index (MIB1),

and overexpression of Bcl2, p53, Bcl-XL, and Bax. Trends were also observed for low

p21 and high STAT3 expression, but they were not statistically significant (see also

additional information).

0,0970,052 0,051

0,032 0,000 0,0150,002 0,000

0,083 0,0240,020 0,0510,093 0,003 0,053 0,000 0,000 0,008

0,068 0,039 0,046 0,0070,082 0,037 0,033 0,019 0,000 0,011

0,060 0,088 0,000 0,062 0,089 0,0660,003 0,001 0,001 0,006 0,022 0,087 0,002

0,001 0,001 0,006 0,004 0,001 0,009 0,014 0,0040,034 0,001 0,004 0,001 0,003 0,008 0,001 0,032 0,004 0,006 0,015 0,000

0,083 0,015 0,010 0,058 0,057 0,0120,005 0,001

0,029 0,051 0,001 0,0280,010 0,081

0,014 0,015* 0,025* 0,006*0,006 0,026 0,013 0,007 0,019 0,080 0,001 0,013 0,002 0,0610,044 0,018 0,040* 0,086

0,027 0,000 0,018 0,000 0,001 0,002 0,020 0,000 0,012 0,001 0,0590,050 0,042 0,014 0,028 0,006 0,018 0,010 0,012 0,000 0,006 0,000

0,012 0,080 0,029 0,0110,072* 0,005* 0,045* 0,016* 0,000* 0,000 0,000 0,019*

Cyclin A

Cyclin D3

Cyclin D3

Cyclin ECyclin E

CDK1CDK1

CDK2CDK2

p16p16

p21p21

p27p27

Hdm2Hdm2

p53p53

RbRbSKP2SKP2

MIB1MIB1

STAT3STAT3

BaxBax

Bcl6Bcl6

BclXLBclXL

Mcl1

SurvivinSurvivin

TUNELTUNEL

EBV

Cyclin ACyclin B1Cyclin D3Cyclin ECDK1CDK2CDK6p16p21p27

Hdm2p53Rb

SKP2MIB1

STAT1STAT3BaxBcl2Bcl6

BclXLMcl1

NF-kBSurvivinTUNEL

EBV

Cyclin A

Cyclin B1

NF-kBNF-kB

Bcl2Bcl2

STAT1STAT1

CDK6CDK6





Table 4: Biological markers related with patient’s outcome.

DISCUSSION

Experimental models and observations in viral-induced cell transformation have shown

the synergistic effect of concurrent and multiple tumor suppressor pathway inactivation.

Examples of this are provided by viral E6 and E7 HPV proteins binding p53 and Rb,32,33

and EBV-mediated B-cell transformation through p53 and Rb binding by EBNA5

protein.34-36 Observations performed in different experimental models have proved

difficult to transfer and confirm in human tumors, where the simultaneous analysis of

different suppressor pathways requires multiple genes to be explored with an array of

techniques. The availability of monoclonal Abs for paraffin-embedded tissue and the

development of TMA now make it possible to explore this matter in tissue samples from

human tumors, even in the case of HL, where the low proportion of tumoral cells

requires the use of highly sensitive techniques.

HL is exceptional among malignant neoplasms in that the tissue samples involved

consist mainly of reactive lymphocytes, plasma cells and often fibrous stroma,

containing only a limited number of the putative neoplastic cell, the H/RS cell. Thus, in

a majority of cases H/RS cells represent less than 10% of the lymph node cell

population, making in situ techniques such as IHC and ISH the most suitable methods

for analyzing protein, DNA, and RNA expression, as they allow the visualization and

identification of this expression selectively in the neoplastic cells.

Kaplan-Meier Cox’s regression model

P Chi-square RR p

Bcl2 0.0041 8.41 2.83 0.004

MIB1 0.0307 4.67 2.28 0.031

p53 0.0232 5.15 2.45 0.023

Bcl-xL 0.0121 6.28 2.47 0.012

Bax 0.0130 6.16 4.05 0.013

TUNEL 0.0296 4.72 6.78 0.030

STAT3 0.0623 - - 0.068

p21 0.0842 - - 0.061





TMA allows simultaneous analysis of several proteins in large series of patients, thus

revealing the complex interactions between diverse pathways and genes, and, in turn,

the clinical relevance of multiple biological parameters. Different groups in several

types of human tumors have previously demonstrated the suitability of this technique.

To our knowledge, a single limited study 24 has previously provided evidence of the

feasibility of this tool in HL, based solely on the expression of a single protein.

In this paper we have shown the adequacy of TMA in the analysis of heterogeneous

tumors such as HL, made a comparative study of results from analyses of whole tissue

sections, and demonstrated the suitability of this design and the chosen conditions (two

1-mm diameter cylinders per sample). Detection of EBV LMP by IHC vs. EBER by ISH

has also shown a high concordance rate, highlighting the accuracy of the technique.

Since TMA technology is a population-level research tool, and is not intended for

making clinical diagnoses of individual cases, the general picture provided by these

experiments more than compensates for the information probably lost concerning some

of the cylinders and cases.

The checkpoint regulating transition from G1 to S is frequently disrupted in cancer, and

the mechanism of this regulation is complex. Two Cyclin/CDK complexes, Cyclin

D/CDK4 or –6 and CyclinE/CDK2, phosphorylate the retinoblastoma gene product, Rb,

alter its ability to associate with other cellular proteins, such as E2F, and activate the

transcription of several genes required for S progression. The kinase activities of

CDK4/Cyclin D and CDK2/Cyclin E convert Rb to the hyperphosphorylated state with

loss of binding activity. G1 CDK activity is positively regulated by growth factors and

inhibited by a variety of physiological signals from the cell microenvironment.37

This series shows that H/RS cells display in most of cases deregulation of the genes

involved in the G1/S and G2/M checkpoints, and inactivation of the tumor suppressor

pathways defined by p14ARF-p53-p21WAF1, p16INK4A-Rb and p27KIP1. Thus, the tumoral

cells show almost constant Hdm2 overexpression, which has been found in previous

studies to be associated with the presence of alternative transcripts of Hdm2 lacking

the adhesion to p14ARF, its inhibitory protein.7 Hdm2 overexpression is considered to be

a mechanism that leads to p53 inactivation, binding it and concealing its transcriptional

activity.38 Although alterations in the p53 gene are the most common genetic alteration

found in human cancer (>50%), the incidence of p53 mutations is significantly lower in

HL than in other neoplasias.39,40 The understanding of the activity of these proteins in





HL may explain the unusual low frequency of p53 mutations in this tumor with

overexpression of the protein and defective p53 function.

The p16INK4a-Rb pathway is also presumably inactivated in a large fraction of these

samples as the result of p16INK4a loss (due to promoter region methylation or deletion)

and/or Cyclin D overexpression. Results obtained here concerning p16 loss differ

slightly from those previously reported, probably as a consequence of the higher

sensitivity of the techniques or the larger size of the series employed in the current

study.

In the majority of cases, p27KIP1 protein is also lost, probably as a consequence of

increased degradation mediated by SKP2. SKP2 protein acts as a ubiquitin ligase for

p27KIP1, and most cases show overexpression of this protein in H/RS cells. Indeed,

consistent with this interpretation, there is an inverse relationship between p27KIP1 and

SKP2 expression in HL tumors.

At the same time, the tumoral cells are characterized by the increased expression in a

large proportion of cases of Cyclins and CDKs involved in G1/S and G2/M transition,

such as Cyclin D, Cyclin A, Cyclin B1, Cyclin E, CDK2 and CDK6. A striking finding

here is the observation that 90% and 84% of cases show overexpression of Cyclin E

and CDK2, respectively, which differs strongly from the observations in reactive

lymphoid tissue and other NHLs. Cyclin E and CDK2 both form a complex, which is

negatively regulated through the interaction with p27KIP1, and whose balance

determines the cell-cycle progression to the S phase. This almost universal finding in

H/RS could be related with the increased growth fraction seen in these cells, as already

described.41 Additionally, deregulated Cyclin E increases chromosomal instability and

polyploidy,42 affecting those processes involved in the faithful duplication and

segregation of chromosomes. These are findings that could be considered to be the

hallmark of HL cells.

Consistent with altered mitotic checkpoint control, the H/RS cells also express elevated

protein levels of the mitotic regulatory proteins cyclin A, cyclin B1, and CDK1 (cdc2).

The cyclin B/CDK1 complex (also called mitosis promoting factor, MPF) is the primary

regulator of transition from G2 to M phase, being involved in chromosome

condensation, nuclear membrane breakdown, and spindle formation. The transition

from G2 to M phases and the proper transition during mitosis depend on cyclin A and B

proteosomal degradation.43 For example, onset of mitosis is regulated by the activation





of Cyclin B1/CDK1 and this event is controlled at several levels, ensuring that

chromosome segregation does not occur in the case of unreplicated or damaged DNA,

or misaligned chromosomes. The altered expression of these G2/M Cyclins and CDKs

in H/RS cells could depend on inappropriate ubiquitination/degradation, and also could,

at least partially, explain the frequent alterations in cytokinesis and the morphological

abnormalities found in these cells, leading to the formation of the characteristic

multinucleated cells.

H/RS cells also have defective regulation of apoptosis, as shown by the association of

Bcl2 (23%), Bcl-XL (19%), and Survivin (89%) overexpression, loss of Bax expression

(3%), and increased nuclear expression of p65/RelA (76%). These findings are

consistent with those of previous studies9,44,45 suggesting that Bcl2, Bcl-xL, and NF-

kappaB activation are critical mechanisms involved in the resistance to apoptosis by

H/RS cells, at least in some cases as a consequence of the transforming capacity of

LMP1-EBV protein46. The frequent expression of Survivin in the H/RS cells in HL has

not been previously described, and may represent an additional mechanism for

evading apoptosis in the G2/M checkpoint. The relevance of Bcl2 and Bcl-XL

overexpression is underlined by the shortened OS of these patients. This result is

similar to observations in DLBCL, and confirms previous observations in HL.47 In this

context it is worth mentioning that the disease in cases of HL with marked

overexpression of p53 proteins, as observed in 15% of cases, is more aggressive and

has a shortened OS. Here we have chosen this high threshold of p53 expression,

similar to that found to reflect p53 mutations in other lymphoid tumors.

H/RS cells harbor clonally rearranged and somatically mutated immunoglobulin genes,

indicating their derivation in most cases from germinal center B cells,1 but lack B-cell

receptor expression. Although germinal center B cells that lack a functional high-affinity

Ab undergo apoptosis within the germinal center, under physiological conditions,2 the

H/RS cells escape programmed cell death (apoptosis), and instead proliferate and

disseminate. The concurrent alterations in cell cycle regulatory pathways observed in

this series thus explain the insensitivity of H/RS cells to inhibitory signals, and its high

growth fraction.

The analysis of the relationships among the proteins studied yields some interesting

findings. Thus, EBV positive cases have a characteristic profile distinguished by the

overexpression of STAT1 and STAT3 by the H/RS cells, and down-regulation of the

expression of p27, Hdm2, p53, Cyclin E, CDK6, and Bcl-xL, which seems to confirm





that EBV presence in H/RS is not just an innocent bystander, but also plays a role in

the progression of the disease and the survival of tumoral cells. STAT1 and STAT3

also seem to play a determinant role, since their expression in H/RS cells is

significantly associated with the presence of increased levels of CDK1, CDK2 and

CDK6, Rb, NF-kappaB, and Bax, and also is associated with higher proliferative index.

Previous studies analyzing the expression profile in EBV positive cases at RNA level34

also revealed a specific pattern, but showing some differences from our results at the

protein level. These findings provide convincing evidence that the EBV virus exploits

the normal program of B-cell-cycle activation as part of its strategy.

Another key transcription factor revealed by this study as playing an important role in

HL is NF-kappaB, as has been observed previously in HL-derived cells48,49 and

tumors.9,10 This transcription factor regulates the expression of numerous genes

regulating critical functions in the immune system, inflammatory responses involved in

the control of cell proliferation and apoptosis. This analysis proves that the presence of

NF-kappaB and its activation, as reflected by the nuclear expression, is related to

changes in the expression of a set of proteins that play a role in the control of cell-cycle

progression, apoptosis and gene transcription, such as p21, p16, p27, Rb, Cyclin E,

Cyclin D3, CDK1, CDK2, SKP2, STAT1, STAT3, and Survivin. It is noteworthy the

strong relation observed with Survivin (p<0.000), a member of the inhibitor of apoptosis

(IAP) family, which has been described as a target of NF-kappaB 50. Although the

association with Bcl-XL (another NF-kappaB target) is not statistically significant, the

majority of cases express high levels of both proteins.

High MIB1 expression is associated here with the increased expression of Rb, p21,

p53, Hdm2, Cyclins A, B1, D3, and E, CDK1, CDK2 and CDK6, SKP2, STAT1, STAT3,

and Bcl-XL. Thus it appears that the increased growth fraction, typical of Hodgkin’s

cells, is the consequence of deregulation of multiple genes, significantly including

Cyclins and CDK, transcription factors and SKP2, a key gene in protein degradation

mediated by ubiquitin. The complexity of the changes in cell-cycle regulation in H/RS

cells is shown in Figure 4.

In spite of the small number of NLPHL cases here included, this study also reveals that

these cases have a distinctive profile (Bcl6+, EBV-, p65/RelA-, p16-, Bcl2-, and CDK2-

), different from that seen in classical HL, and not only attributable to the presence of

EBV virus.





Clinical correlation also sheds further light on the relevance of these findings. Several

of these regulator proteins seem to be associated with patient outcome. Thus, a shorter

survival in this series is related with Bcl2, p53, Bcl-XL, Bax, and high proliferative and

apoptotic indexes. Some of these prognostic markers had been previously noted in the

literature.5,45,51,52 These findings have been shown to be statistically significant using

Kaplan-Meier and Cox regression analyses and restricted to classical HL cases.

Nevertheless, a more comprehensive analysis of these and other markers is currently

being performed with the aim of incorporating biological variables into the clinical

prognosis scoring system.

In summary, TMA studies with a panel of Abs for cell cycle markers show an

unexpected constellation of abnormalities for the expression of oncogenes and cell-

cycle control molecules, thus confirming the complexity of the changes involved in the

malignant transformation in HL. Variations in the expression profiling reflect the

histological sub-typing and account for some of the clinical variability observed in this

disease.

Figure 4. Scheme of cell cycle showing main checkpoints commonly deregulated in

HL tumors (see text).





ACKNOWLEDGMENTS

We are indebted to Laura Cereceda (CNIO Tumor Bank) and L. García (Hematology,

H. Ramón y Cajal, Madrid) for their excellent assistance with data managing, and to R.

Pajares, and M.J. Acuña for their expertise and excellent technical assistance with

TMA technology and immunohistochemical assays. We also thank all the participants

of the Spanish Hodgkin’s Lymphoma Study Group for their cooperation: P. Domínguez

and C. Jara (F.H.A, Alcorcón), R. Quibén and L. Borbolla (H. Móstoles, Madrid), C.

Grande (H. 12 Octubre, Madrid), J. García (H. Ramón y Cajal, Madrid), A. Castaño and

P. Sáncjez-Godoy (H. Servero Ochoa, Leganés), R. Martínez (H.U.C. San Carlos,

Madrid), J. Menárguez, P. Sabín (H. Gregorio Marañón, Madrid), J. González-Carrero

and C. Poderós (H. Xeral-Cies, Vigo), Ll. Font (H. Verge de la Cinta, Tortosa), M.A.

Cruz (H. Virgen de la Salud, Toledo), M. Llanos (H.U. Canarias), C. Morante (H.

Cabueñes, Gijón), E. Conde (H.M. De Valdecilla, Santander), M.F. Fresno and C.

Rayón (H.C. de Asturias, Oviedo), R. García (H.C.U. Salamanca), J. Guma (H. Sant

Joan, Reus), P. Gonzalvo (H.C.de Jarrio, Coaña), G. Fernández (H. Alvarez Buyllas,

Mieres), J. Forteza and J.L. Bello (F. Med Santiago de Compostela), and J.R. Méndez

(H. Valle de Nalón, Asturias).

REFERENCES

1. Kuppers R, Hansmann ML, Rajewsky K. Clonality and germinal centre B-cell

derivation of Hodgkin/Reed-Sternberg cells in Hodgkin's disease. Ann Oncol.

1998;9:S17-20.

2. Rajewsky K. Clonal selection and learning in the antibody system. Nature.

1996;381:751-758.

3. Sanchez-Aguilera A, Sanchez-Beato M, Garcia JF, Prieto I, Pollan M, Piris

MA. p14(ARF) nuclear overexpression in aggressive B-cell lymphomas is a sensor of

malfunction of the common tumor suppressor pathways. Blood. 2002;99:1411-1418.

4. Sanchez-Beato M, Saez AI, Navas IC, Algara P, Sol Mateo M, Villuendas R,

Camacho F, Sanchez-Aguilera A, Sanchez E, Piris MA. Overall survival in aggressive

B-cell lymphomas is dependent on the accumulation of alterations in p53, p16, and

p27. Am J Pathol. 2001;159:205-213.

5. Morente MM, Piris MA, Abraira V, Acevedo A, Aguilera B, Bellas C, Fraga M,

Garcia-Del-Moral R, Gomez-Marcos F, Menarguez J, Oliva H, Sanchez-Beato M,





Montalban C. Adverse clinical outcome in Hodgkin's disease is associated with loss of

retinoblastoma protein expression, high Ki67 proliferation index, and absence of

Epstein-Barr virus-latent membrane protein 1 expression. Blood. 1997;90:2429-2436.

6. Maggio EM, Stekelenburg E, Van den Berg A, Poppema S. TP53 gene

mutations in Hodgkin lymphoma are infrequent and not associated with absence of

Epstein-Barr virus. Int J Cancer. 2001;94:60-66.

7. Garcia JF, Villuendas R, Sanchez-Beato M, Sanchez-Aguilera A, Sanchez L,

Prieto I, Piris MA. Nucleolar p14(ARF) overexpression in Reed-Sternberg cells in

Hodgkin's lymphoma: absence of p14(ARF)/Hdm2 complexes is associated with

expression of alternatively spliced Hdm2 transcripts. Am J Pathol. 2002;160:569-578.

8. Garcia JF, Villuendas R, Algara P, Saez AI, Sanchez-Verde L, Martinez-

Montero JC, Martinez P, Piris MA. Loss of p16 protein expression associated with

methylation of the p16INK4A gene is a frequent finding in Hodgkin's disease. Lab

Invest. 1999;79:1453-1459.

9. Hinz M, Loser P, Mathas S, Krappmann D, Dorken B, Scheidereit C.

Constitutive NF-kappaB maintains high expression of a characteristic gene network,

including CD40, CD86, and a set of antiapoptotic genes in Hodgkin/Reed-Sternberg

cells. Blood. 2001;97:2798-2807.

10. Izban KF, Ergin M, Huang Q, Qin JZ, Martinez RL, Schnitzer B, Ni H,

Nickoloff BJ, Alkan S. Characterization of NF-kappaB expression in Hodgkin's disease:

inhibition of constitutively expressed NF-kappaB results in spontaneous caspase-

independent apoptosis in Hodgkin and Reed-Sternberg cells. Mod Pathol.

2001;14:297-310.

11. Jungnickel B, Staratschek-Jox A, Brauninger A, Spieker T, Wolf J, Diehl V,

Hansmann ML, Rajewsky K, Kuppers R. Clonal deleterious mutations in the

IkappaBalpha gene in the malignant cells in Hodgkin's lymphoma. J Exp Med.

2000;191:395-402.

12. Leoncini L, Spina D, Megha T, Gallorini M, Tosi P, Hummel M, Stein H,

Pileri S, Kraft R, Laissue JA, Cottier H. Cell kinetics, morphology, and molecular IgVH

gene rearrangements in Hodgkin's disease. Leuk Lymphoma. 1997;26:307-316.

13. Leoncini L, Spina D, Close P, Megha T, Pacenti L, Tosi P, Pileri S, De Vivo

A, Kraft R, Laissue JA, Cottier H. Abortive mitoses and nuclear DNA fragmentation in

CD30+ large cells of Hodgkin's disease. Leuk Lymphoma. 1996;22:119-124, follow.

186, color plate XI.

14. Erdkamp FL, Schouten HC, Breed WP, Janssen WC, Hoffmann JJ, Schutte

B, Blijham GH. DNA aneuploidy in Hodgkin's disease: a multiparameter flow cytometric

analysis. Leuk Lymphoma. 1994;12:297-306.





15. Weber-Matthiesen K, Deerberg J, Poetsch M, Grote W, Schlegelberger B.

Numerical chromosome aberrations are present within the CD30+ Hodgkin and Reed-

Sternberg cells in 100% of analyzed cases of Hodgkin's disease. Blood. 1995;86:1464-

1468.

16. Kim SH, Shin YK, Lee IS, Bae YM, Sohn HW, Suh YH, Ree HJ, Rowe M,

Park SH. Viral latent membrane protein 1 (LMP-1)-induced CD99 down-regulation in B

cells leads to the generation of cells with Hodgkin's and Reed- Sternberg phenotype.

Blood. 2000;95:294-300.

17. Gerdes J, Schwarting R, Stein H. High proliferative activity of Reed

Sternberg associated antigen Ki-1 positive cells in normal lymphoid tissue. J Clin

Pathol. 1986;39:993-997.

18. Stein H, Mason DY, Gerdes J, O'Connor N, Wainscoat J, Pallesen G,

Gatter K, Falini B, Delsol G, Lemke H, et al. The expression of the Hodgkin's disease

associated antigen Ki-1 in reactive and neoplastic lymphoid tissue: evidence that Reed-

Sternberg cells and histiocytic malignancies are derived from activated lymphoid cells.

Blood. 1985;66:848-858.

19. Messineo C, Jamerson MH, Hunter E, Braziel R, Bagg A, Irving SG,

Cossman J. Gene expression by single Reed-Sternberg cells: pathways of apoptosis

and activation. Blood. 1998;91:2443-2451.

20. Re D, Hofmann A, Wolf J, Diehl V, Staratschek-Jox A. Cultivated H-RS

cells are resistant to CD95L-mediated apoptosis despite expression of wild-type CD95.

Exp Hematol. 2000;28:31-35.

21. Kallioniemi OP, Wagner U, Kononen J, Sauter G. Tissue microarray

technology for high-throughput molecular profiling of cancer. Hum Mol Genet.

2001;10:657-662.

22. Nocito A, Kononen J, Kallioniemi OP, Sauter G. Tissue microarrays (TMAs)

for high-throughput molecular pathology research. Int J Cancer. 2001;94:1-5.

23. Torhorst J, Bucher C, Kononen J, Haas P, Zuber M, Kochli OR, Mross F,

Dieterich H, Moch H, Mihatsch M, Kallioniemi OP, Sauter G. Tissue microarrays for

rapid linking of molecular changes to clinical endpoints. Am J Pathol. 2001;159:2249-

2256.

24. Hedvat CV, Jaffe ES, Qin J, Filippa DA, Cordon-Cardo C, Tosato G, Nimer

SD, Teruya-Feldstein J. Macrophage-derived chemokine expression in classical

Hodgkin's lymphoma: application of tissue microarrays. Mod Pathol. 2001;14:1270-

1276.

25. Harris NL, Jaffe ES, Diebold J, Flandrin G, Muller-Hermelink HK, Vardiman

J, Lister TA, Bloomfield CD. World Health Organization classification of neoplastic





diseases of the hematopoietic and lymphoid tissues: report of the Clinical Advisory

Committee meeting-Airlie House, Virginia, November 1997. J Clin Oncol.

1999;17:3835-3849.

26. Morgan J. A protocol for preparing cell suspensions with formalin fixation

and paraffin embedding which minimises the formation of cell aggregates. Journal of

Cellular Pathology. 2001;5:171-180

27. Bubendorf L, Nocito A, Moch H, Sauter G. Tissue microarray (TMA)

technology: miniaturized pathology archives for high-throughput in situ studies. J

Pathol. 2001;195:72-79.

28. Adida C, Haioun C, Gaulard P, Lepage E, Morel P, Briere J, Dombret H,

Reyes F, Diebold J, Gisselbrecht C, Salles G, Altieri DC, Molina TJ. Prognostic

significance of survivin expression in diffuse large B-cell lymphomas. Blood.

2000;96:1921-1925.

29. Soini Y, Raunio H, Paakko P. High-grade malignant non-Hodgkin's

lymphomas differ from low-grade lymphomas in the extent of apoptosis and their

expression of bcl-2, mcl- 1, bax and p53. Tumour Biol. 1998;19:176-185

30. Skinnider BF, Elia AJ, Gascoyne RD, Patterson B, Trumper L, Kapp U, Mak

TW. Signal transducer and activator of transcription 6 is frequently activated in Hodgkin

and Reed-Sternberg cells of Hodgkin lymphoma. Blood. 2002;99:618-626.

31. Bargou RC, Emmerich F, Krappmann D, Bommert K, Mapara MY, Arnold

W, Royer HD, Grinstein E, Greiner A, Scheidereit C, Dorken B. Constitutive nuclear

factor-kappaB-RelA activation is required for proliferation and survival of Hodgkin's

disease tumor cells. J Clin Invest. 1997;100:2961-2969.

32. Tommasino M, Crawford L. Human papillomavirus E6 and E7: proteins

which deregulate the cell cycle. Bioessays. 1995;17:509-518.

33. Zwerschke W, Jansen-Durr P. Cell transformation by the E7 oncoprotein of

human papillomavirus type 16: interactions with nuclear and cytoplasmic target

proteins. Adv Cancer Res. 2000;78:1-29

34. Hollyoake M, Stuhler A, Farrell P, Gordon J, Sinclair A. The normal cell

cycle activation program is exploited during the infection of quiescent B lymphocytes by

Epstein-Barr virus. Cancer Res. 1995;55:4784-4787.

35. Cannell EJ, Farrell PJ, Sinclair AJ. Epstein-Barr virus exploits the normal

cell pathway to regulate Rb activity during the immortalisation of primary B-cells.

Oncogene. 1996;13:1413-1421.

36. Szekely L, Selivanova G, Magnusson KP, Klein G, Wiman KG. EBNA-5, an

Epstein-Barr virus-encoded nuclear antigen, binds to the retinoblastoma and p53

proteins. Proc Natl Acad Sci U S A. 1993;90:5455-5459.





37. Malumbres M, Barbacid M. To cycle or not to cycle: a critical decision in

cancer. Nature Rev Cancer. 2001;1:222-231.

38. Oliner JD, Pietenpol JA, Thiagalingam S, Gyuris J, Kinzler KW, Vogelstein

B. Oncoprotein MDM2 conceals the activation domain of tumour suppressor p53.

Nature. 1993;362:857-860.

39. Montesinos-Rongen M, Roers A, Kuppers R, Rajewsky K, Hansmann ML.

Mutation of the p53 gene is not a typical feature of Hodgkin and Reed- Sternberg cells

in Hodgkin's disease. Blood. 1999;94:1755-1760.

40. Elenitoba-Johnson KS, Medeiros LJ, Khorsand J, King TC. P53 expression

in Reed-Sternberg cells does not correlate with gene mutations in Hodgkin's disease.

Am J Clin Pathol. 1996;106:728-738.

41. Gerdes J, Van Baarlen J, Pileri S, Schwarting R, Van Unnik JA, Stein H.

Tumor cell growth fraction in Hodgkin's disease. Am J Pathol. 1987;128:390-393.

42. Spruck CH, Won KA, Reed SI. Deregulated cyclin E induces chromosome

instability. Nature. 1999;401:297-300.

43. Nigg EA. Mitotic kinases as regulators of cell division and its checkpoints.

Nat Rev Mol Cell Biol. 2001;2:21-32.

44. Kuppers R. Molecular biology of Hodgkin's lymphoma. Adv Cancer Res.

2002;84:277-312

45. Brink AA, Oudejans JJ, van den Brule AJ, Kluin PM, Horstman A,

Ossenkoppele GJ, van Heerde P, Jiwa M, Meijer CJ. Low p53 and high bcl-2

expression in Reed-Sternberg cells predicts poor clinical outcome for Hodgkin's

disease: involvement of apoptosis resistance? Mod Pathol. 1998;11:376-383.

46. Laherty CD, Hu HM, Opipari AW, Wang F, Dixit VM. The Epstein-Barr virus

LMP1 gene product induces A20 zinc finger protein expression by activating nuclear

factor kappa B. J Biol Chem. 1992;267:24157-24160

47. van Spronsen DJ, Peh SC, Vrints LW, van Imhoff GW, Poppema S. Clinical

drug-resistant nodular sclerosing Hodgkin's lymphoma is associated with decreased

bcl-2 expression in the surrounding lymphocytes and with increased bcl-2 expression in

the Reed-Sternberg cells. Histopathology. 2000;37:420-426.

48. Fiumara P, Snell V, Li Y, Mukhopadhyay A, Younes M, Gillenwater AM,

Cabanillas F, Aggarwal BB, Younes A. Functional expression of receptor activator of

nuclear factor kappaB in Hodgkin disease cell lines. Blood. 2001;98:2784-2790.

49. Cossman J. Gene expression analysis of single neoplastic cells and the

pathogenesis of Hodgkin's lymphoma. J Histochem Cytochem. 2001;49:799-800.

50. Mitsiades N, Mitsiades CS, Poulaki V, Chauhan D, Richardson PG,

Hideshima T, Munshi N, Treon SP, Anderson KC. Biologic sequelae of nuclear factor-




https://www.researchgate.net/publication/12821818_Mutation_of_the_p53_gene_is_not_a_typical_feature_of_Hodgkin_and_Reed-Sternberg_cells_in_Hodgkin's_disease?el=1_x_8&enrichId=rgreq-130b9142aaa6f705ec4ec0c2669dbae2-XXX&enrichSource=Y292ZXJQYWdlOzExMDY4NjQ2O0FTOjEwMTM0MDY4NDQ4ODcxMUAxNDAxMTcyOTEwNzI5

https://www.researchgate.net/publication/12821818_Mutation_of_the_p53_gene_is_not_a_typical_feature_of_Hodgkin_and_Reed-Sternberg_cells_in_Hodgkin's_disease?el=1_x_8&enrichId=rgreq-130b9142aaa6f705ec4ec0c2669dbae2-XXX&enrichSource=Y292ZXJQYWdlOzExMDY4NjQ2O0FTOjEwMTM0MDY4NDQ4ODcxMUAxNDAxMTcyOTEwNzI5

https://www.researchgate.net/publication/13706082_Low_p53_and_high_bcl-2_expression_in_Reed-Sternberg_cells_predicts_poor_clinical_outcome_for_Hodgkin's_disease_Involvement_of_apoptosis_resistance?el=1_x_8&enrichId=rgreq-130b9142aaa6f705ec4ec0c2669dbae2-XXX&enrichSource=Y292ZXJQYWdlOzExMDY4NjQ2O0FTOjEwMTM0MDY4NDQ4ODcxMUAxNDAxMTcyOTEwNzI5

https://www.researchgate.net/publication/13706082_Low_p53_and_high_bcl-2_expression_in_Reed-Sternberg_cells_predicts_poor_clinical_outcome_for_Hodgkin's_disease_Involvement_of_apoptosis_resistance?el=1_x_8&enrichId=rgreq-130b9142aaa6f705ec4ec0c2669dbae2-XXX&enrichSource=Y292ZXJQYWdlOzExMDY4NjQ2O0FTOjEwMTM0MDY4NDQ4ODcxMUAxNDAxMTcyOTEwNzI5

https://www.researchgate.net/publication/11927531_Nigg_EA_Mitotic_kinases_as_regulators_of_cell_division_and_its_checkpoints_Nat_Rev_Mol_Cell_Biol_2_21-32?el=1_x_8&enrichId=rgreq-130b9142aaa6f705ec4ec0c2669dbae2-XXX&enrichSource=Y292ZXJQYWdlOzExMDY4NjQ2O0FTOjEwMTM0MDY4NDQ4ODcxMUAxNDAxMTcyOTEwNzI5


kappaB blockade in multiple myeloma: therapeutic applications. Blood. 2002;99:4079-

4086.

51. Benharroch D, Levy A, Prinsloo I, Ariad S, Rabinovitch D, Shendler Y,

Sacks M, Gopas J. Apoptotic index as a prognostic factor in Hodgkin's disease. Leuk

Lymphoma. 1999;33:351-359.

52. Smolewski P, Niewiadomska H, Los E, Robak T. Spontaneous apoptosis of

Reed-Sternberg and Hodgkin cells; clinical and pathological implications in patients

with Hodgkin's disease. Int J Oncol. 2000;17:603-609.




Hodgkin and Reed-Sternberg cells harbor alterations in the major tumor suppressor pathways and...

Documents

Transcript of Hodgkin and Reed-Sternberg cells harbor alterations in the major tumor suppressor pathways and...