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olecular classification of nodal metastasis in primaryarynx squamous cell carcinoma

RANCESCO CARINCI, DIEGO ARCELLI, LORENZO LO MUZIO, FRANCESCA FRANCIOSO,AVIDE VALENTINI, RITA EVANGELISTI, STEFANO VOLINIA, ANNA D’ANGELO,ERMANA MERONI, MASSIMO ZOLLO, ANTONIO PASTORE, FRANCO IONNA,

ILIBERTO MASTRANGELO, PIO CONTI and STEFANO TETÈ

ERRARA, ROME, FOGGIA, NAPOLI, AND CHIETI, ITALY

Classification and prognosis of larynx squamous cell carcinoma (LSCC) depends onclinical and histopathological examination. Currently, expression profiling harbors thepotential to investigate, classify, and better manage cancer. Gene expression profilesof 22 primary LSCCs were analyzed by microarrays containing 19,200 cDNAs. GOALfunctionally classified differentially expressed genes, and a novel “in silico” procedureidentified physical gene clusters differentially transcribed. A signature of 158 genesdifferentiated tumors with nodal metastasis. A novel statistical method allowed cate-gorization of metastatic tumors into 2 distinct subgroups of differential gene expressionpatterns. Among genes correlated to nodal metastatic progression, we verified in vitrothat NM23-H3 reduced cell motility and TRIM8 were a growth suppressor. Six chromo-somal regions were specifically downregulated in metastatic tumors. This large-scalegene expression analysis in LSCC provides information on changes in genomic activityassociated with lymphonodal metastasis and identifies molecules that might proveuseful as novel therapeutic targets. (Translational Research 2007;150:233–245)

Abbreviations: CGH � comparative genomic hybridization; DMEM � Dulbecco’s modifiedEagle’s medium; FCS � fetal calf serum; FDR � false discovery rate; GO � gene ontology;HNSCC � head and neck squamous cell carcinoma; LSCC � larynx squamous cell carci-noma; MAPK � mitogen-activated protein kinase; RT-PCR � reverse-transcriptase polymerase

chain reaction; TNM � tumor, node, mestasis.

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ead and neck squamous cell carcinoma(HNSCC) represents the sixth most commoncancer in the world and can affect diverse an-

tomical regions: the oral cavity, oropharynx, larynx,nd hypopharynx. The prognosis of HNSCC is influ-nced by many factors, such as performance status,

rom the Department of Maxillofacial Surgery, University of Ferrara,errara, Italy; the IDI IRCCS, Dermopatic Institute of the ”Immaco-

ata,” Rome, Italy; the Department of Surgical Sciences, Universityf Foggia, Foggia, Italy; the Functional Genomics Laboratory, De-artment of Morphology and Embryology, University of Ferrara,errara, Italy; the TIGEM, Telethon Institute of Genetics and Med-

cine, Napoli, Italy; the ENT Clinic, University of Ferrara, Italy; thestituto dei Tumori “Pascale,” Naples, Italy; and the Department ofral Sciences and the Immunology Division, University of Chieti,hieti.

upported by an AIRC-FIRC Fellowship (to A.D) and by grants from

IRC-FIRC [2002] (to M.Z.), Compagnia S. Paolo Torino 2002 (to d

umor, node, metasis (TNM) staging, and pathologicrading of differentiation. Currently, these factors areot sufficient for predicting outcome, and many studiesave focused on the identification of molecular biomar-ers with prognostic significance for metastasis, treat-ent response, or survival.1

.Z.), TIGEM-Telethon Regione Campania [2001] (M.Z.), CARIFEto A.P.), and Ministero della Salute [Prot n. DRS/CRS/T.17.2003/45] (to F.C.).

ubmitted for publication November 22, 2006; revision submittedarch 12, 2007; accepted for publication March 13, 2007.

eprint requests: Pio Conti, PhD, MD, Director of Immunologyivision, University of Chieti, Via dei Vestini, 66100 Chieti, Italy,

-mail: pconti@unich.it

931-5244/$ – see front matter

2007 Mosby, Inc. All rights reserved.

oi:10.1016/j.trsl.2007.03.011

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Translational Research234 Carinci et al October 2007

Currently, it is widely accepted that cancer is caused byequential accumulation of genetic aberrations, and cyto-enetic abnormalities have been shown to be useful mark-rs for the diagnosis and prognosis of malignancies. InNSCC, the karyotypes are extremely complex and make

t difficult to identify the genetic rearrangements occurringn tumor development. However, the most common cyto-enetic imbalances are 2q34-qter, 3p, 4p, 4q28-qter, 8p,p-pter, 10p, 13, 14, 17q23-qter, and 18q21-qter deletionsnd 3q, 7, 8q, and 11q13 amplifications.2

Recently, a high-throughput technique based on mi-roarray experiments has enabled genome-wide analy-is of gene expression. The extensive analysis of humanranscriptome in tumor tissues can represent an essen-ial tool to clarify mechanisms of carcinogenesis anddentify the molecular markers and the therapeutic tar-ets for the improvement of patient management. Sev-ral studies have demonstrated the utility of this tech-ique to reveal cancer subtypes based on heterogeneityn transformation mechanisms, differentiation states, orell types.3,4 In HNSCC, most microarray analysis haseen performed in heterogeneous biopsy collectionsrom diverse anatomical sites of the head and neck.hese studies have identified some genes differentiat-

ng cancer from normal tissues or keratinocytes but notlinical subtypes.5-7 More recently, gene expressionignature has been associated with the incidence ofocally recurrent disease8 and, in hypopharyngeal can-er, with different clinical outcomes.9

In this article, we describe the first transcriptome-widenalysis of larynx squamous cell carcinoma (LSCC),hich is the most frequent neoplasm of the head and neck

egion. The aim of our study was to identify genes in-olved in larynx tumorigenesis and gene expression pat-erns associated with lymph node metastasis. We havedentified novel genes associated with metastatic progres-ion, and among those, NM23-H3 and TRIM8 have beenroven to be effective in vitro. Furthermore, we haveerformed an automated gene ontology analysis to func-ionally classify differential expression profiles and haveeveloped a novel method that extends the statisticalcores of the differential expression onto the human ge-ome map and identifies physical gene clusters differen-ially transcribed in LSCC clinical subtypes.

ATERIALS AND METHODS

Tissue specimens. Primary tumor samples were obtainedrom 22 patients, all male, undergoing surgery for larynxquamous cell carcinoma. The research was carried out ac-ording to the principles of the Declaration of Helsinki, andnformed consent was obtained from patients to use theirissue specimens for research purposes.

Part of each sample was used for histopathological analy-

is, which enabled the selection of tumors with no less than i

0% of cancer cells. Patients with positive and negative neckodes were selected by clinical examination, sonography, andistopathologic evaluation of resected lymph nodes. Diseasetaging (TNM) was defined after surgery according to theICC. The primary tumors were equally subdivided in 2roups (11 tumors each) relative to the presence of nodaletastasis (Table I). No patients enrolled in the study exhib-

ted distant metastasis at the time of surgery. Eight controliopsy specimens were harvested from the mucosa of theontrolateral region of the tumor of a clinically unaffected sitend proved to be histologically normal. These non-tumoramples were used to generate a reference RNA pool.

RNA extraction and microarrays assays. RNA extrac-ion and processing, cDNA labeling, and hybridization toNA microarrays containing 19,200 cDNAs (Ontario Cancer

nstitute, Toronto, Ontario, Canada) were performed as pre-iously described.10 All experiments shared a common tissueeference made of 8 pooled non-tumor larynx mucosal RNAs,nd tumor samples could thus be compared to identify genexpression patterns correlated to clinical features. The tumoramples were labeled with Cy5, and the reference non-tumorarynx pool was labeled with Cy3 by using the amino-allylrotocol. Images were derived by an Axon scanner and ana-yzed by using GENEPIX PRO 3.0 (Axon Instruments, Fosterity, Calif). Spots showing no signal or obvious defects werexcluded from the analysis. Local background was subtractedrom the remaining spots, and the ratios of net fluorescencerom the Cy5-specific channel to the net fluorescence fromhe Cy3-specific channel were calculated for each spot, rep-esenting tumor mRNA expression relative to the correspond-

able I. Clinical data of the study participants

ID Sample Sex Stage* Grade

1 FE124 M T2N0M0 G22 FE130T M T2N0M0 G13 FE134 M T2N0M0 G24 FE138T M T2N0M0 N/A5 FE148T M TxN0M0 G26 FE152T M T1NOMO G27 FE156 M T3N0M0 G18 SGR16 M T2N0M0 G29 SGR50 M T2N0M0 G1

10 SGR66 M T1bN0M0 G111 SGR78 M T2N0M0 G212 FE114T M T2N1M0 G113 FE200T M T4N2M0 G214 FE216 M T3N3M0 G215 FE220 M T2N2M0 N/A16 FE230 M T4N2M0 G317 SGR76 M T4N1M0 G118 SGR26 M T3N2aM0 G219 SGR68 M T2N1M0 G120 SGR70 M T1N1M0 G321 SGR74 M T2N1M0 G222 SGR84 M T4N1M0 G2

bbreviation: N/A, not available.According to the TNM staging system.

ng larynx non-tumor tissue. GP3 perl script was used to

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Translational ResearchVolume 150, Number 4 Carinci et al 235

ostprocess raw data files from the scanning procedure.11

-score normalization, a trimmed mean of 75%, and thresholdalue of 3 were used to filter GenePix raw data. Experimentshowing poor hybridizations, as assessed by postprocessingnalysis, were repeated. Replicated cDNA values were aver-ged by using the geometric mean. Overall, 7676 cDNAsith GP3 quality-passed values were present in at least 75%f the biopsies (null values, when present, were set to rowverage to the purpose of statistical analysis).

Statistical analysis and data mining. Expression tablesere assembled from GP3 output files and analyzed by usingierarchical clustering, principal components analysis, andimilarity searches tools in JExpress. When the Cy5-labeledancer profiles were compared with the Cy3-labeled referenceon-tumor profile, a specialized t-test was performed. Essen-ially, the group of cancer samples was compared with aimulated group of similar size, for which the log ratios wereandomly generated inside the limits (�3� standard devia-ion) defined in 3 control experiments (non-tumor larynxNA vs itself). In these control experiments, in fact, the

eference pool of 8 non-tumor larynx RNA was hybridizedersus itself upon Cy3 and Cy5 labeling. The procedure ofenerating random log ratios for the reference group wasterated 100 times, and the mean t for each cDNA wasomputed. To evaluate multiple t-testing effects, we calcu-ated the false discovery rate (FDR), defined as the proportionf cDNAs expected to occur by chance in the permutationassuming genes are independent) relative to the proportion ofdentified cDNAs. To select the cDNAs that distinguish be-ween 2 sample groups (eg, metastatic vs nonmetastatic bi-psies), we performed a t-test in conjunction with permuta-ion analysis as previously described.12 The statisticalignificance of the differential expression of a cDNA wasssessed by computing a P-value for each cDNA, whichepresented the chance of observing a test statistic at least asarge (in absolute value) as the value actually obtained. Nopecific parametric form was assumed for the distribution ofhe test statistics. To determine the P-value, we used a bal-nced permutation procedure in which the class labels of theamples were permuted 50,000 times, and for each permuta-ion, 2-sample t-statistics were computed for each cDNA. The-value for a particular cDNA is the proportion of the per-utations in which the permuted test statistic exceeds the

bserved test statistic in absolute values. Any cDNA forhich this P-value was less than or equal to 0.001 was

onsidered to be differentially expressed. Prediction analysisor microarrays was used to carry out sample classificationrom gene expression data, by the method of nearest shrunkenentroids.13

Gene ontology classification. Regulated biological pro-esses and molecular functions, according to gene ontologyGO; http://www.geneontology.org) Consortium classifica-ion, were identified by using the GOAL Web-based applica-ion,14 and Unigene build 154. The GO project is a collabo-ative effort to annotate genes by using 3 vocabularies thatescribe gene products in terms of their associated biologicalrocesses, cellular components and molecular functions.

riefly for each GO term/s associated with the Unigene g

luster in the expression tables, the mean t-score from the-scores of each corresponding Unigene cluster was calcu-ated. The Unigene clusters t-scores were averaged whenore cDNAs were present for a single Unigene cluster. A

ermutation analysis was performed to assign P-values to theO analysis, with at least 500,000 random data points for

ach permutation. GO terms with P-values lower than 0.05ere selected as differentially regulated. FDR was calculated

s the ratio between the median of the detected positive (P �.05), in a set of balanced permutations within the expressionable, and the number of significant GO terms in the actualxpression table itself. The SOURCE meta-database (http://ource.stanford.edu) was used to measure the normalizedxpression level of IMAGE clones in all Unigene libraries.

Differentially regulated chromosomal regions. A Perlcript was developed for the identification of chromosomalegions, differentially expressed in LSCC clinical classes.BI was used to interface the Perl script to a MySQL (Mi-

rosoft Corporation, Redmond, Wash) database containinghe genomic coordinates of all cDNAs present on the microar-ays. Statistical evaluation was performed by using the per-utation analysis to generate P-values and FDR.15

Reverse-transcriptase polymerase chain reaction (RT-CR) analysis. Total RNA (1 �g) was reverse-transcribedith 200 units of SuperScript II (Invitrogen, Carlsbad, Calif)

n a 20 �L of reaction volume containing 1 �L of Oligo (dT)2-18 (500 �g/mL), 1 �L of 10 mM dNTP mixture, 10 mMTT2, 40 units of RNaseOUT, and First-Strand Buffer at2°C for 50 min. In total, 1 �L of cDNA mixture wasubjected to PCR amplification with 1 unit of Ampli Taqold (Applied Biosystems, Foster City, Calif) and pairedrimers. The primer sequences used for NMR-H3 were asollows: forward primer TCAAGTTGGTGGCGCTGAA andeverse primer TATACTTGACAAGGCGGCCGT. All sam-les were subjected to PCR amplification with oligonucleo-ide primers specific for the constitutively expressed gene-actin. The PCR products were then separated on anthidium bromide-stained 2% agarose gel and visualized byltraviolet light-transillumination (at 280 nm).

Stable clones analysis. NM23-H3 cDNA was subclonednto the EcoRI/XhoI digested pBABE-puro vector. The MDA-100 breast cancer cell line clone was transfected with theBABE-NM23-H3 expression vector using LipofectAMINEInvitrogen), according to the manufacturer instructions. Trans-ectants were selected in Dulbecco’s modified Eagle’s mediumDMEM) containing 10% fetal bovine serum, 100-Units/mLenicillin, 100-mg/mL streptomycin, and 2-mg/mL puromycinSigma Chemical Co., St. Louis, Mo). For the bulk transfectedines, plates containing 100 puromycin-resistant colonies wererypsinized, and cell lines were established. Thirty individualBABE-h-NM23-H3 puromycin-resistant clones were isolatednd characterized by real-time PCR, by using the follow-ng primers: NM23H3_for TCAAGTTGGTGGCGCTGAA;M23H3_rev TATACTTGACAAGGCGGCCGT.For real-time PCR analysis, individual cell clones were

lated at concentrations of 7–9 � 106 cells in 75-mL flasks.he mRNA was extracted and purified by TRIZOL (Invitro-

en) and then assayed by TaqMan quantitative Real Time

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Translational Research236 Carinci et al October 2007

CR detection analysis using an ABI PRISM 7000 instrumentApplied Biosystems). Several clones were selected and as-ayed for their mRNA levels by quantitative analysis andopy number extrapolation, as compared with gene referenceargets (GAPDH).

In vitro cell motility assay. The control MDA-C100 celline was used in the ”cell motility” assay, as previouslyescribed,16,17 in parallel with the same cell line overexpress-ng NM23-H1 (MDA-H1-C177), and showing an inhibitionf metastasis processes in vivo, and 2 NM23-H3 stable clonalines. Cellular motility was determined using the trans-wellechnology (Corning-Costar; Corning Incorporated, Corning,Y) assay with 0.5% fetal calf serum (FCS), and 5.0-ng/mLbronectin (Sigma Chemical Co.) final concentrations as che-oattractants. In lower wells, we incubated 2.5 mL ofMEM containing 0.1% bovine serum albumin, 100-nits/mL penicillin, 100-mg/mL streptomycin, 5 mM HEPESuffer (motility medium), and the diluted chemoattractant; inpper wells, we incubated 1 � 105 cells in 1.5 mL of motilityedium. The trans-wells were incubated for 3 h at 37°C with

% CO2. After this attraction by FCS and fibronectin, cellsere fixed and stained with Hematoxylin solution Gill n°1

ollowing manufacturer protocol (Corning-Costar); cells werenally counted under the microscope. The assays were per-ormed in quadruplicate.

In vitro colony formation assay. U2OS human cells wereransfected with 1 �g of empty pcDNA3 vector or equimolarmounts of either TRIM8, TRIM29, and NM23-H3 expres-ion vectors by using LipofectAMINE (Invitrogen) and thenelected with G-418. Colonies were stained and counted after

weeks from transfection. The colony formation assay isased on the comparison of the number of colonies originatedy cells transfected with the expression vectors and anquimolar amount of empty vector (pcDNA3). Experimentsere performed in quadruplicate.Additional tables and the expression data can be found at

he following website: http://biotecnologie.unife.it/microar-ays/larynx/.

ESULTS

Genes involved in tumorigenesis. To select tumor-spe-ific genes, a specialized t-test (see the Materials andethods section) was performed using cDNAs withP3 quality-passed values. A highly discriminating setf 1157 distinct cDNAs (P � 0.001, FDR � 0.001) wasifferentially expressed between tumor and non-tumorarynx, 598 were upregulated and 559 were downregu-ated in tumors (Table II of Web supplement). It isoteworthy that oncogenes ErbB-3, FGFR1, MYBL1,AB21, neuroblastoma-amplified protein NAG, Poloike Kinase, KRAS2, and LIM homeobox protein 2ere significantly overexpressed. Furthermore, in theO annotations of the downregulated set, the “tumor

uppressor” term occurred 11 times, instead of only 1ime in the upregulated set, which suggests that severalnown tumor suppressor genes were inactivated in

SCC. The repressed tumor suppressor genes were t

denovirus 5 E1A binding protein, FUS2, MYB bind-ng protein (P160) 1a, p53 binding protein 1, mitogen-ctivated protein kinase phosphatase X, multiple endo-rine neoplasia I, CCCTC-binding factor (zinc fingerrotein), RAD50 homolog, the putative FHIT interactorit protein 2, candidate tumor suppressor p33, andlutathione S-transferase theta 1.GOAL analysis was performed to select the biolog-

cal processes and molecular functions differently reg-lated in larynx cancer (P � 0,01, FDR � 0,001; TableII of the Web supplement). Most of them were down-egulated in tumors and included the organization andhe biogenesis of cortical actin cytoskeleton, the adhe-ens junctions, and the activity of transcription regula-ors, inositol/phosphatidylinositol kinases, and Rhouanyl-nucleotide exchange factors. Of interest is theresence among the overexpressed functions of thectivation of mitogen-activated protein kinaseMAPK), of Junk, and of a signal transduction pathwaynduced by DNA damage that blocks cell-cyclerogression.Genes expression signature of metastatic tumors. We

sed a t-test coupled to permutation analysis (P �.001, FDR � 0.06) to select 158 genes that differen-iated tumor tissues with lymph node metastasis (N�;1, N2, N3 classes) from those without lymph nodeetastasis (N0) (Fig 1, Table II, and Table V of theeb supplement). All selected genes were underex-

ressed, with the exception of IMAGE clone 491346.his gene is reported in NCBI as highly expressed inepatic adenoma, metastatic chondrosarcoma, andigh-grade serous papillary carcinoma. The downregu-ated genes included the tumor suppressor CUL1, p53-nduced TP53TG1, cell–cell adherens junction proteinsSP and BAIAP1, and proteins of the cellular defense

esponse, such as CD3D and CSF2RA, that suggested aiminished cellular-mediated immune response in met-static tumors. Prediction analysis for microarrays wassed to evaluate metastasis prediction of this geneignature. We obtained an error rate of 0.135, whichas raised to 0.179 when the gene number was reduced

o 126 (Table VII of Web supplement).Then, GOAL was used to generate the list of molec-

lar functions and biological processes that discrimi-ated N� from N0 biopsies (Table VI of the Webupplement). All categories were downregulated in N�iopsies. Those categories with higher score includedhe response to DNA damage stimulus, the induction ofpoptosis by intracellular signals, the actin cytoskeletonrganization and biogenesis, the substrate-bound celligration and cell extension, the adherens junctions,

nd the structural constituents of epidermis.Subtypes expression in metastatic tumors. To explore

he complexity of the expression “phenotype” in met-

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Translational ResearchVolume 150, Number 4 Carinci et al 237

static LSCC, we performed a molecular dissection ofhe expression profiles within the N� patients, lookingor the presence of hidden groups. By using a noveltatistical approach, we carried out a very large numberf t-tests of all N0 tumors versus a random sample of0% of the N� tumors (P � 0.001). All possibleermutations (10K) within the N� class were evalu-ted, for each of them recording the number of geneshits) passing the significance threshold. The frequencyistribution of the recorded hits is shown in Fig I of theeb supplement (mean of 24.89 and standard deviation

f 41.03). The highest number of hits (372 selectedenes) represented a subgroup of N� biopsies (LSCCd: 15, 16, 21, 14, 19; hitherto named group II), whiche compared with the remaining ones (group I). A

ignature of 308 genes differentiated (P � 0.001, FDR0.025) the 2 subgroups of N� biopsies (Table VIII-a

f the Web supplement, clustering analysis shown inig II of the Web supplement). Most differentiallyxpressed genes were downregulated in group II andere involved in cell-cycle (MAPK3, GAK, CDC42),

ell-matrix adhesion (ITGA11, ITGBL1, RHOB,SPG2), formation and remodeling of the extracellularatrix (MMP13, COL6A2, COL5A1, COL5A2,OL1A2), and immune response (IL1B, IL6). Instead,nly a few genes differentiated group I from N0 pri-ary biopsies, and among these, laminin alpha 5 anditogen-responsive phosphoprotein DOC2 were acti-

ated in group I, whereas tumor suppressor CUL1 andP53 target 1 were inhibited (data not shown).All molecular functions identified by GOAL, with

ignificant variations in the 2 subgroups (P � 0.05,DR � 0.0158), were underexpressed in group II (Ta-le VIII-b of the Web supplement). The prominent onesere double-stranded-DNA binding proteins, calcium

hannel regulators including multidrug resistance-re-ated protein sorcin, structural proteins of the extracel-ular matrix, MAPK kinase activity, DNA packaging,

Fig 1. Hierarchical clustering tree of the 158 cmetastasis and without lymph node metastasis.

ctin modulating activity, start control point of the r

itotic cell cycle, components of the Rho signalingathway, retinoid X-receptor, and apoptosis-relatedunctions.

Next, we applied the SAM multiclass option to iden-ify genes with significant changes of expression in the

subgroups of LSCC primary tumors. The analysis of0 versus N� group I versus N� group II samples

elected 74 genes (FDR � 0.0135; Table IX of the Webupplement). Among these genes, TRIM8 and T-cellarkers, CD3D and TAL1, differentiated the sub-

roups. GOAL functional analysis of the SAM-derivedcores selected 35 cellular processes and molecularunctions differentially regulated in the 3 LSCC classesTable X of the Web supplement). They were involvedn actin modulation, cell adhesion, MAPK activity,elomerase activity, NO mediated signal transduction,GF beta pathway, double-stranded DNA binding, de-biquitination, induction of apoptosis by DNA damage,hospholipid binding, DNA packaging, defense re-ponse, and epidermal differentiation.

Genes quantitatively correlated to N progression. Weooked for genes quantitatively correlated to the N stagerogression, ie, whose expression increases from N0 to3 tumors or vice versa. The SAM quantitative func-

ion selected 481 genes (FDR � 0.12, Table XI of theeb supplement), most of them being inversely corre-

ated to N, ie, less transcribed at increasing lymph nodeetastatic stages. Among the only 7 genes positively

orrelated to N stages progression, we identified UDP-lucose ceramide glucosyltransferase-like 2 (UGCGL2),ranscriptional repressor NAC1, inositol polyphosphatehosphatase-like 1 SHIP2, nudix, and nuclear bodies coi-in. UGCGL2 is reported in SOURCE to be highly tran-cribed in liposarcoma, pituitary tumor, Burkitt’s lym-homa, metastatic melanoma, pheochromocytoma, andhondrosarcoma. The signature inversely correlated to Ntage contained genes that regulate cytoskeleton organi-ation, cell adhesion and death, and genes coding for

at discriminate between LSCC with lymph node

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Translational Research238 Carinci et al October 2007

able II. Annotated genes differentially expressed in lymph node positive versus lymph node negativerimary tumors (P � 0.001, FDR � 0.06)

Name Symbol GenBank Gene Ontology

pregulatedSTs, Weakly similar to hypothetical proteinFLJ11267 [Homo sapiens] [H.sapiens]

BQ021555 unannotated

ownregulated=-nucleotidase, cytosolic II NT5C2 NM_012229 cytosol|5=-nucleotidasenkyrin 3, node of Ranvier (ankyrin G) ANK3 NM_020987 cytoskeletal anchoring|Golgi apparatus|structural

protein|endoplasmic reticulumnnexin A5 ANXA5 NM_001154 calcium binding|phospholipid binding|phospholipase inhibitornnexin A9 ANXA9 NM_003568 phospholipid binding|calcium-dependent phospholipid

bindingAI1-associated protein 1 BAIAP1 NM_004742 cell adhesion|intercellular junction|cell surface receptor linked

signal transductioniphenyl hydrolase-like (serine hydrolase;breast epithelial mucin-associatedantigen)

BPHL NM_004332 detoxification response|amino acid and derivative metabolism

D3D antigen, delta polypeptide (TiT3complex)

CD3D NM_000732 T cell receptor|cellular defense response|cell surface receptorlinked signal transduction

olony stimulating factor 2 receptor, alpha,low-affinity (granulocyte-macrophage)

CSF2RA NM_006140 receptor|antimicrobial humoral response|integral plasmamembrane protein

ullin 1 CUL1 NM_003592 tumor suppressor|mitotic G1/S transition|negative control ofcell proliferation|induction of apoptosis by intracellularsignals

ysteine knot superfamily 1, BMPantagonist 1

CKTSF1B1 NM_013372 neurogenesis|protein binding|extracellularspace|developmental processes

ytochrome P450, subfamily IIIA(niphedipine oxidase), polypeptide 5

CYP3A5 NM_000777 microsome|monooxygenase|cytochrome P450|steroidmetabolism

esmoplakin (DPI, DPII) DSP NM_004415 intermediate filament|epidermal differentiation|cell-celladherens junction

imethylglycine dehydrogenase precursor DMGDH NM_013391 mitochondrion|electron transfer flavoproteinouble-stranded RNA specific adenosinedeaminase

ADAR3 NM_018702 mRNA editing|adenosine deaminase|double- and single-stranded RNA binding

ual specificity phosphatase 3 (vacciniavirus phosphatase VH1-related)

DUSP3 BC008286 protein dephosphorylation|protein tyrosine phosphatase

ms1 sequence (mammary tumor andsquamous cell carcinoma-associated(p80/85 src substrate)

EMS1 NM_005231 cytoskeleton|soluble fraction|peripheral plasma membraneprotein

atty acid desaturase 1 FADS1 NM_013402 C-5 sterol desaturase|fatty acid desaturation|integralmembrane protein

ormyl peptide receptor 1 FPR1 NM_002029 chemotaxis|plasma membrane|activation ofMAPK|inflammatory response|integral membrane protein|NO mediated signal transduction|G-protein linked receptorprotein signalling pathway

lycoprotein M6B GPM6B BC008151 integral plasma membrane proteinlypican 5 GPC5 NM_004466 glypican|integral plasma membrane proteoglycanRB2-associated binding protein 1 GAB1 NM_002039 cell proliferation|SH3/SH2 adaptor protein|EGF receptor and

insulin receptor signalling pathwayron-responsive element binding protein 2 IREB2 M58511 cytosol|cytoplasm|RNA binding|RNA catabolism|translational

regulationeucine zipper-EF-hand containing

transmembrane protein 1LETM1 NM_012318 calcium binding|signal transduction|developmental

processes|integral plasma membrane proteinajor histocompatibility complex, class I, E HLA-E NM_005516 class I major histocompatibility complex antigenannose receptor, C type 1 MRC1 NM_002438 receptor mediated endocytosis|integral plasma membrane

proteinetaxin 1 MTX1 NM_002455 integral membrane protein

uclear domain 10 protein NDP52 NM_005831 nucleus|invasive growth|viral life cycleuclear factor I/B NFIB NM_005596 nucleus|transcription factorrostaglandin D2 synthase 21kDa (brain) PTGDS NM_000954 membrane|prostaglandin-D synthaserotein disulfide isomerase-related protein P5 NM_005742 protein folding|protein disulfide isomerase

utative nucleic acid binding protein RY-1 RY1 BC017890 DNA binding

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Translational ResearchVolume 150, Number 4 Carinci et al 239

o-receptor of IL-1RI. In the pool of genes whose expres-ion negatively correlated to metastatic potential, we se-ected NM23-H3 and TRIM8. The NM-23 gene is con-idered to have metastasis-suppressive function in animalodels and in human carcinomas.18,19 Furthermore, itas suggested that tumor NM23-H1 expression could beprognostic factor for predicting better survival in oral

quamous cell carcinoma.20 The TRIM8 sequence wasdentified by Vincent et al21 in a contiguous regionapped to chromosome 10q24.3, which is a region show-

ng frequent deletion or loss of heterozygosity in glioblas-omas. To substantiate the possible role of NM23-H3 andRIM8 in carcinogenesis, we looked for their normalizedene expression as reported in SOURCE.22 NM23-H3as found to be absent from adenocarcinoma, hepatocar-

inoma, large cell carcinoma, ovarian, and other tumors.RIM8 was also absent from adenocarcinoma, large cellarcinoma, chondrosarcoma, epithelioid carcinoma, andlioblastoma. For the NM23-H3 gene, we confirmed find-ngs of expression profiles by RT-PCR, which demon-trated a reduced level of transcript in metastatic tumorsFig 2). Then, to verify the possible anti-metastatic andnti-proliferative involvement of NM23-H3 and TRIM8,e performed 2 different in vitroassays, the cell motility

nd the colony formation assay. Two different NM23-H3lones reduced motility of stably transfected MDA-C100

able II. Annotated genes differentially expressed inrimary tumors (P � 0.001, FDR � 0.06) - continued

Name Symbol Ge

erologically defined colon cancer antigen16

SDCCAG16 NM_

H3-domain GRB2-like 3 SH3GL3 NM_

olute carrier family 22 (organic aniontransporter), member 7

SLC22A7 NM_

hioredoxin reductase 2 TXNRD2 NM_P53 target gene 1 TP53TG1 NM_biquitin carboxyl-terminal esterase L1(ubiquitin thiolesterase)

UCHL1 NM_

inc finger protein 297 ZNF297 NM_

ote: This table is a subset of the 158 cDNA detected in the LSCC eere eliminated from the downregulated final list.

Fig 2. RT-PCR analysis for NM23-H3 mRNA trans1–11) and from lymph node negative (N0) tumor tistranscripts from the same samples. M, DNA marke

ell line at levels similar to those of the known anti- f

etastatic family member NM23-H1 (Fig 3). Further-ore, the colony formation assay demonstrated that2OS cells stably transfected with TRIM8 cDNA were

uppressed in the capability of forming colonies. As neg-tive control in the assay, we included an additional TRIMamily member, TRIM29 (Fig 4). With regard to nodeositive tumors subclasses, group I had levels of TRIM8nd NM23-H3 similar to non-metastatic LSCC; therefore,e named group I as TRIM8/NM23-H3 positive androup II as TRIM8/NM23-H3 negative.Genomic localization of genes differentially regulated.s cDNA microarrays also have intrinsic genomicalue, we developed a novel bioinformatics method toranslate the expression profile into genomic coordi-ates. We took advantage of the high density of genesn our experiment (mean physical distance of approxi-ately 390 Kb) to measure differential RNA expres-

ion at a genome-wide level. To perform this analysis,e plotted the differential expression t-score, as an

verage value in a sliding window along the humanhromosomes. Permutation analysis was performed inarallel to define P-values and FDR. The deregulatedenomic regions and the representative genes are listedn Table III. The plots of the differential expressionlong chromosomes are shown in the Web supplement.ur procedure identified 7 chromosomal regions dif-

node positive versus lymph node negative

Gene Ontology

tumor antigen

cytoplasm|signal transduction|central nervous systemdevelopment

sodium-independent organic anion transporter |integralplasma membrane protein

mitochondrion|thioredoxin reductase (NADPH)stress response|signal transductionubiquitin-dependent protein degradation

nucleus|DNA binding

analysis. Clones for which no functional information was available

m lymph node positive (N�) larynx biopsies (laness 12–22). The bottom panel shows PCR for �-actin

lymph

nBank

006649

003027

006672

006440007233005935

005453

cripts frosues (lane

erentially transcribed in LSCC when compared with

Translational Research240 Carinci et al October 2007

Fig 3. Cell motility inhibition by NM23-H3. The control MDA-C100 breast cancer cell line was used in the ”cellmotility” assay, in parallel with the same cell line overexpressing NM23-H1 (MDA-H1-C177), which shows anin vivo inhibition of metastasis processes, and 2 newly established stable transfectants of NM23-H3 (nm23-H3#5, nm23-H3#6). Cellular motility was determined using the trans-well technology assay with 0.5% FCS and5.0-ng/mL fibronectin (Sigma Chemical Co.) final concentrations as chemoattractants, as described in theMaterial and Methods section. After the attraction by FCS and fibronectin, cells were fixed stained, and counted.Data represent the mean � standard deviation of quadruplicate determinations. Statistical analysis was per-formed using the Student t-test. Statistical significance versus control MDA-C100 cell was P � 0.0006 for

nm23-H3#5, P � 0.003 for nm23-H3#6, and P � 0.001 for nm23-H1.

Fig 4. Growth suppression by TRIM8. U2OS cells were transfected with equimolar amounts of pcDNA3-TRIM8, pcDNA3-TRIM29, pcDNA3-NM23-H3, or vector alone and selected with G-418; emerging colonieswere stained and counted. TRIM8 transfectants produced significantly less colonies than did either TRIM29 andNM23-H3 transfectants or empty vector (P � 0.0001, Student t-test). Data represent the mean � standard

deviation of quadruplicate determinations.

nbdAgdoTempskdqra

m5Sid1g

21gp1(vctd

D

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1211

1111

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Translational ResearchVolume 150, Number 4 Carinci et al 241

on-tumor tissues (P � 0.001): 4 upregulated (cyto-ands 3q28, 9q31.3, 15q26.1, and 17q21.33) and 3ownregulated (cytobands 1p35.2, 2q13, and 3q26.1).t 3q upregulated locus, 1 of the most frequent geneticains in HNSCC, spanned claudin1 and related clau-in16. Claudin1 encodes an integral protein componentf tight junctions and is involved in the beta-catenin/cf signaling pathway. This protein is frequently over-xpressed in primary colorectal cancers, whereas otherembers of claudin gene family have also been re-

orted to be deregulated in HNSCC.23 At 17q21.33panned integrin alpha3 (top panel of Fig 5), which isnown to play a role in extracellular matrix remodelinguring tumorigenesis and cell invasion.24-26 The fre-uently deleted PTEN gene was significantly down-egulated (P � 0.01) and mapped in the most repressedrea of chromosome 10.Six chromosomal regions were underexpressed inetastatic tumors (P � 0.001), including 2p13.3,

q31.1, 6p21.1, 11q24.2, 17q21.33, and 22q11.21.ome genes found in these regions are known to be

nvolved in cell adhesion (CDON), cell growth andivision (PPP2A, CDKL3), and apoptosis (BID). At7q21.33 locus the anti-metastatic NM23-H1 and H2

able III. Genomic deregulation of gene expression

Cytoband Mb Cancer-related ge

q28 191-193 Claudin 1q31.3 104-106 Not found5q26.1 85.5-87.5 Not found7q21.33 50-52 integrin, alpha 3p35.2 31-33 PTP4A2q13 110-112 BUB1, BCL2-like 11 (apoptoq26.1 167-168 SERPIN I2, programmed celp13.3 68-70 MADq31.1 133-134.5 TCF7, PPP2CA, CDKL3p21.1 42-44 VEGF1q24.2 125-127 CDON7q21.33 48.0-49.5 NM23-H1 and -H26p13.3 NM23-H32q11.21 16-17.5 BCL2-like 13 (apoptosis facil

(BH3-interacting domain dq21.2 150-152 MCL1p13.3 68-70 MAD1q12.3 63-65 GNG32q13.2 54-56 Integrin alpha 7, CD63, BMP

CDK2, MMP197q21.33 48.0-49.5 NM23-H1 and -H26p13.3 NM23-H39p13.3 1-2 APCL9q13.2 42-44 melanoma inhibitory activity,

E1BAP5q28 150-152 DKC1, MPP1, MTCP1

ote: The table shows the highest scoring gene clusters detectedisted (P � 0.001). The expression trend is displayed along with som

enes were located (bottom panel of Fig 5) and at h

p13.3 the candidate tumor suppressor MAD. The7q21.33 and 2p13.3 downregulation was maximal inroup II of lymph node positive biopsies. Lymph nodeositive group I and group II were also divergent atq21.2, 11q12.3, 12q13.2, 19p13.3, 19q13.2, and Xq28P � 0.001). Genes detected in these regions are in-olved in cell survival (MCL1), interaction with theytoskeleton (MPP1), breakdown of extracellular ma-rix (MMP19), and mediating migratory signal trans-uction that could affect the metastasis (CD63).

ISCUSSION

Epithelial carcinogenesis is a multistep process, begin-ing with precancerous conditions proceeding throughtages of cell hyperplasia and dysplasia and ending inully malignant transformation. The transformation mech-nism of a normal into a malignant cell involves variouslterations at the cellular, molecular, and genetic lev-ls.27-33 Recently, the emerging technology of cDNA mi-roarray, combined with bioinformatics, has revolution-zed the study of genes providing clinicians with tools tonvestigate thousands of genes simultaneously and todentify differentially expressed molecules.

Most studies of expression-array profiling in HNSCC

C

Expression Clinical subtype

Up CancerUp CancerUp CancerUp CancerDown Cancer

ator) Down CancerDown CancerDown Lymph node positiveDown Lymph node positiveDown Lymph node positiveDown Lymph node positiveDown Lymph node positiveDown Lymph node positive

IDnist)

Down Lymph node positive

Down Lymph node positive Group II vs. IDown Lymph node positive Group II vs. IDown Lymph node positive Group II vs. I

5B, Down Lymph node positive Group II vs. I

Down Lymph node positive Group II vs. IDown Lymph node positive Group II vs. IDown Lymph node positive Group II vs. IDown Lymph node positive Group II vs. I

Down Lymph node positive Group II vs. I

mic analysis of differential expression in clinical LSCC classes arer-related ESTs present in the genomic area observed.

in LSC

nes

sis facilitl death 10

itator), Beath ago

11, RAB

AXL,

ave so far examined mixed tumor cohorts from dif-

ficMpasoabuoTcf

GsifSHduJs

it

fpmcpmeywccmsgdfsiNcpg

etastatic

Translational Research242 Carinci et al October 2007

erent sites of head and neck region. Alevizos et al5

dentified 600 oral cancer associated genes using 5ancer samples from diverse anatomical locations.endez et al7 also distinguished cancer from normal

rofiles in tumors of oropharynx, oral cavity, larynx,nd hypopharynx. Belbin et al6 could detect 2 tumorubgroups with variations in survival rate in 17 heter-geneous HNSCC. As the genetic alterations at variousnatomical locations of HNSCC are strongly influencedy the tumor site,34 we only focused on the larynx andsed DNA microarrays with at least twice the numberf cDNAs used in the previously published reports.his approach allowed us to select a higher number ofancer associated genes and, more interestingly, a dif-erent signature associated with LSCC metastasis.

GOAL analysis, using novel algorithms to integrateO information into the expression profiles, demon-

trated in LSCC overexpression of signal pathwaysnvolved in cell-cycle control, and downregulation ofunctions involved in cell adhesion, shape, and motility.uch alterations, which are recently reported inNSCC, are considered critical transforming events forisease progression.35-40 In addition, other importantpregulated processes were activation of MAPK andUNK. MAPK pathways have been shown to regulate

Fig 5. Plot of the genomic distribution of differenti17. The dark line plot indicates the t-score (100-KAsterisks indicate significantly regulated loci (P � 0The top panel indicates the genes regulation whenlated genes have scores above the light gray line, wdownregulated genes have scores below the gene debetween lymph node positive and lymph node negathe area of loss of expression at 48 Mb in nodal m

everal physiologic and pathologic cellular phenomena, i

ncluding inflammation, apoptotic cell death, oncogenicransformation, tumor cell invasion, and metastasis.

This article mainly aims at generating extensive in-ormation, based on genome-wide transcriptional ex-ression profiles, about the molecular basis of LSCCetastasis. As lymphonodal metastasis is a major indi-

ator of aggressive behavior of tumor, we comparedrimary tumors with and without lymph node involve-ent. One hundred fifty-eight genes were differentially

xpressed between metastatic and non-metastatic lar-nx tumors, and among these the IMAGE clone 491346as the only gene overexpressed. Functional gene

lasses downregulated in metastatic larynx tumors in-luded genes involved in differentiation, cell shape andotility, cell adhesion, and death. This finding is con-

istent with the notion that cells involved in invasiverowth are instructed to stop terminal differentiation,isrupt intercellular junctions, and initiate detachmentrom primary site of accretion. Recently, by applying aupervised classification approach, Roepman et al41

dentified 108 genes capable of discriminating between� and N0 primary tumors of the oropharynx and oral

avity. They found this gene signature could predict theresence of lymph node metastasis at the time of sur-ery.41-44 The predictive performance of this gene set

ion, as assessed by t-score, on human chromosomeg average over a 500-Kb chromosome segment).alues are calculated by using permutation analysis.compared with non-tumor larynx tissues. Upregu-icates the density of the measured genes, whereas. The bottom panel indicates expression differencesC biopsies. NM23-H1and H2 genes are located inprimary tumors.

al expressb slidin

.001). P-vLSCC ishich ind

nsity linetive LSC

ncreased as more recently removed tumors of the col-

ld

mcTttadgmNntnmihihmtdbHcCHratmsc

rcfmNmNlobTpptm

ae

tsohicapmemfpamatdlwcmbfiugSlmaipttm

tmyLbrahtc

CC

R

Translational ResearchVolume 150, Number 4 Carinci et al 243

ection were analyzed and outperformed current clinicaliagnosis.It is common knowledge that clinically similar tu-ors can be genetically heterogeneous with different

onsequences for both disease prognosis and treatment.o characterize the diversity of node positive primary

umors, we used a novel statistical approach and iden-ified 2 distinct genotypic subtypes, named N� group Ind N� group II, which shows the greatest pattern ofivergence in gene expression. Most interestingly,enes involved in cell-cycle control, cell adhesion, im-une response, and apoptosis were less expressed in� group II. Furthermore, N� group I differed fromon-metastatic tumors for few genes, which suggestshat group I could be closer to tumors with no lymphode metastasis. The finding that laminin alpha 5 isore expressed in N� group I than in N0 tumors is

nteresting, as it is thought that laminins promote ad-esion and migration of cells into tissues. These activ-ties are deregulated in cancer, and a laminin isoformas been identified as 1 of the 8 upregulated genes inetastasis of adenocarcinoma.45 Therefore, classifica-

ion of metastatic LSCC into 2 groups might reflectifferent stages of malignancy. Previous microarray-ased studies suggested there might be subtypes ofNSCC. Belbin et al6 identified 375 genes that dis-

riminated tumors into 2 clinically distinct subtypes.hung et al46-48 described 4 distinct subtypes ofNSCC and showed these subtypes had differences in

ecurrences-free survival and overall survival. Jean etl35 classified 17 HNSCC cell lines into 2 subgroupshat did not correlate either with clinical staging oretastatic feature of tumors. They suggested the 2

ubgroups might have undergone different pathways ofarcinogenesis.35

Among the genes with expression profile inversely cor-elated to N stage progression (from N0 to N3 tumors), weonsidered NM23-H3 and TRIM8 potentially interestingor a successive analysis. Indeed, unlike its related familyembers (NM23-H1 and NM23-H2), previouslyM23-H3 isoform has never been correlated to anti-etastatic potential. We verified that 2 differentM23-H3 clones reduced motility of the MDA-C100 cell

ine at levels similar to those of the NM23-H1 isoform. Tour knowledge, this report is the first one on NM23-H3 toe implicated in metastasis or cell motility. We provedRIM8 inhibited colony formation in vitro. The TRIM8rotein structure is similar to those of some tumor sup-ressors, and its gene maps to a locus thought to containumor suppressor genes, which thus suggests TRIM8ight be a new tumor suppressor gene.19

Genomic analysis of cancer associated genes is anlternative and fundamental procedure to attain a deep

valuation of molecular mechanisms associated with

umor genesis. LOH has been an important technique totudy chromosomal material loss during cancer devel-pment. More recently, microarray-driven techniquesave evolved to include comparative genomic hybrid-zation (CGH), which holds a great potential to detecthromosomal alterations.49 In this study we developedbioinformatics procedure to translate the LSCC ex-

ression profile into a genomic-wise analysis. Ourethod displayed the differential expression, as an av-

raged t-score, along a sliding window over the chro-osomes and calculated P-values and FDR. Differently

rom true genomic analysis, such as LOH or CGH, thisrocedure measured gain or loss of RNA expressionnd not of DNA. The upregulation of a genome regionay therefore be caused by each one of either DNA

mplification, transactivation, or epigenetic modifica-ions. Using this methodology we identified severalifferentially regulated genome regions associated witharynx cancer and metastatic progression. Consistentith our findings, 3of the 4 upregulated regions in

ancer (3q, 9q and 17q) have already been identified asajor regions of gene amplification in heterogeneous

iopsies of HNSCC by CGH,50 and this validates thending of our study. Gain of 3q is known to be partic-larly important for the progression of HNSCC51,52 andain of 17q for pharyngeal squamous cell carcinoma.52

ix genome regions were downregulated in tumors withymph node metastasis. These regions mapped the anti-etastatic NM23-H1 and NM23-H2 genes (17q21.33)

nd the candidate tumor suppressor MAD (2p.13.3). Its interesting to note that group II of lymph nodeositive tumors displayed the lowest expression level ofhese 2 regions. Therefore, it is tempting to speculatehat the subdivision into 2 classes of metastatic tumorsight reflect different stages of tumorigenesis.In summary, this work has identified several impor-

ant biological differences among metastatic and non-etastatic LSCC. In addition, based on statistical anal-

sis, we have identified 2 distinct subtypes of primarySCC with nodal metastasis revealing the complexiology that underlies metastasis. Finally, 2 genes, cor-elated to lymph nodal stage, proved to reduce motilitynd inhibit growth in vitro; however, these data willave to be confirmed by further research and by func-ional assays to ascertain their validity and potentiallinical application.

The authors thank Dr. PS Steeg for MDA-C100 and MDA-H1-177 cell lines; Dr. G Raschellà for nm23-H3 cDNA clone; and Dr.arotenuto (TIGEM) for real-time PCR analysis.

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