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Genome-Wide Screening of Genomic Alterations andTheir Clinicopathologic Implications in Non^SmallCell Lung CancersTae-Min Kim,1Seon-Hee Yim,2 Jung-Sook Lee,1Mi-Seon Kwon,3 Jae-Wook Ryu,4

Hyun-Mi Kang,1Heike Fiegler,5 Nigel P. Carter,5 and Yeun-Jun Chung1

Abstract Purpose: Although many genomic alterations have been observed in lung cancer, their clinico-pathologic significance has not been thoroughly investigated. This study screened the genomicaberrations across the whole genome of non ^ small cell lung cancer cells with high-resolutionand investigated their clinicopathologic implications.Experimental Design:One-megabase resolution array comparative genomic hybridizationwasapplied to 29 squamous cell carcinomas and 21adenocarcinomas of the lung.Tumor and normaltissues were microdissected and the extracted DNAwas used directly for hybridization withoutgenomic amplification.The recurrent genomic alterations were analyzed for their associationwiththe clinicopathologic features of lung cancer.Results: Overall, 36 amplicons, 3 homozygous deletions, and 17 minimally altered regionscommon to many lung cancers were identified. Among them, genomic changes on 13q21,1p32, Xq, and Yp were found to be significantly associated with clinical features such as age,stage, and disease recurrence. Kaplan-Meier survival analysis revealed that genomic changes on10p, 16q, 9p, 13q, 6p21, and 19q13 were associated with poor survival. Multivariate analysisshowed that alterations on 6p21, 7p, 9q, and 9p remained as independent predictors of pooroutcome. In addition, significant correlations were observed for three pairs of minimally alteredregions (19q13 and 6p21, 19p13 and 19q13, and 8p12 and 8q11), which indicated their possiblecollaborative roles.Conclusions: These results show that our approach is robust for high-resolution mapping ofgenomic alterations.The novel genomic alterations identified in this study, alongwith their clinico-pathologic implications, would be useful to elucidate the molecular mechanisms of lung cancerand to identify reliable biomarkers for clinical application.

Lung cancer is the most common incident form of malignancyand is also the leading cause of cancer death worldwide (1, 2).A primary lung cancer is classified into four major histologicsubtypes; squamous cell carcinomas, adenocarcinomas, large

cell and small cell lung cancers. The former three classes, whichare grouped as non–small cell lung cancers (NSCLC), make upalmost 80% of all total lung cancer cases. Among the NSCLC,squamous cell carcinomas and adenocarcinomas are the twomajor subtypes. Histologically different subtypes have differentclinical courses, and might require individual therapeuticapproaches.

Some genomic aberrations in tumors have been suggestedto be prognostic markers or can be used to identify the targetgenes for treatment or prevention (3, 4). Likewise, in othersolid tumors, chromosomal aberrations are thought to becritical molecular events in the pathogenesis of lung cancer(5, 6). However, clinically applicable screening tools or prog-nostic markers are still underdeveloped. Because the lack ofefficient screening methods and therapy accounts for the pooroutcome of lung cancer, genome-wide assessment of aberra-tions could help in developing more accurate diagnostic andtherapeutic strategies.

For this reason, previous cytogenetic studies using conven-tional comparative genomic hybridization (CGH) or fluores-cence in situ hybridization have focused on identifying thechromosomal aberrations associated with NSCLC. Recurrentgenomic alterations have been observed in NSCLC, includingthe gains of partial or whole chromosomal arms on 1q, 3q, 5p,

Human Cancer Biology

Authors’Affiliations: 1Department of Microbiology, College ofMedicine, CatholicUniversity of Korea, Socho-gu, Seoul; 2Korea National Cancer Center, ResearchInstitute, Division of Cancer Control and Epidemiology, Gyeonggi-do; Departmentsof 3Pathology and 4Thoracic and Cardiovascular Surgery, College of Medicine,Dankook University, Cheonan, Chungnam, Republic of Korea; and 5The WellcomeTrust Sanger Institute, Hinxton, Cambridge, United KingdomReceived 5/31/05; revised 8/3/05; accepted 9/1/05.Grant support: Korea Health 21R&D Project, Ministry of Health andWelfare,Republic of Korea (01-PJ3-PG6-01GN07-0004).The costs of publication of this article were defrayed in part by the payment of pagecharges.This article must therefore be hereby marked advertisement in accordancewith18 U.S.C. Section1734 solely to indicate this fact.Note:T-M. Kim and S-H.Yim contributed equally to this paper.Supplementary data for this article are available at Clinical Cancer Research Online(http://clincancerres.aacrjournals.org/).Requests for reprints:Yeun-Jun Chung, Department of Microbiology, College ofMedicine, Catholic University of Korea, 505 Banpo-dong, Socho-gu, Seoul 137-701, Republic of Korea. Phone: 82-2590-1214; Fax: 82-2596-8969; E-mail:[email protected].

F2005 American Association for Cancer Research.doi:10.1158/1078-0432.CCR-05-1157

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and 8q along with the losses on 3p, 6q, 8p, 9p, 13q, and 17p(7–11). However, the f10 Mb resolution of conventionalCGH is insufficient for the precise identification of submicro-scopic changes (12). As accumulating evidence suggests thatchanges in the genomic dosage contribute to tumorigenesisby altering the expression levels of the cancer-related genes(13, 14), more detailed analyses with sufficient resolution arerequired.

For enhancing the resolution, array CGH using mappedbacterial or P1 artificial chromosomes (BAC/PAC) ratherthan metaphase chromosomes, has been recently developed(15–17). This technique provides a high resolution that isdirectly related to the genomic density and insert size of thearrayed clones. Array CGH has emerged as a useful tool fordetecting and mapping the genomic aberrations, which maycontain putative oncogenes or tumor suppressor genes and forperforming a molecular classification of tumors (18).

To see genomic alterations and their clinicopathologicimplications in NSCLC, we applied genome-wide array CGHto the genomic DNA extracted from the microdissectedtissues of 29 squamous cell carcinoma and 21 adenocarci-noma cases, on which the association study was done. Usingthis strategy, the genomic copy number changes specific toNSCLC including novel minimally altered regions (MAR)were identified. Those genomic alterations are likely tobe related to tumorigenesis or the clinical outcomes of lungcancer.

Materials andMethods

Study materials. Frozen tissues were obtained from 50 NSCLC

patients, who underwent surgical resection at Dankook University

Hospital, Cheonan, Korea. Tissue collection and the full procedure of

genetic analyses were done under the approval of Institutional Review

Board of Kangnam St. Mary’s Hospital, The Catholic University of

Korea. The 50 NSCLC cases were histologically classified into squamous

cell carcinomas (29 cases) and adenocarcinomas (21 cases). Tumor

staging was done according to the standard tumor-node-metastasis

classification in the American Joint Committee on Cancer guidelines.

Of 50 patients whose mean age was 60 years, 88% (44 cases) were male.

Other clinical information on the 50 patients is also available in

Supplementary Table S1.Tissue preparation. After surgical resection, tumor and adjacent

normal tissues from the same patient were collected separately andsnap-frozen in a deep freezer. Frozen sections were prepared of 10 Amthickness on a gelatin-coated slide using 2800 Frigocut (Reighert-Jung,Germany). After H&E staining, tumor cell– rich area (>60% of tumorcells) and histologically normal cell area were selected under themicroscope and dissected manually. Microdissected tissues weretransferred into the cell lysis buffer (1% proteinase-K in TE buffer)and DNA was extracted. DNA from normal tissue was used asreference DNA for array CGH. Extracted DNA was purified using aDNA purification Kit (Solgent, Daejeon, Korea) and used for dyelabeling reactions.

Array comparative genomic hybridization and image analysis. Weused human large insert clone arrays with 1 Mb resolution across thewhole genome printed by the Sanger Institute Microarray Facility (19).

Fig. 1. Genome-wide copy number alterations in 50 cases of NSCLC. A, genomic profiles of 29 squamous cell carcinomas (top) and 21adenocarcinomas (bottom). FiftyNSCLC cases are represented in individual lanes with corresponding sample numbers in two subtypes. Intensity ratios are schematically plotted in different color scalesreflecting the extent of genomic gains (red) and losses (green) as indicated in the reference color bar. A total of 2,987 BAC clones were ordered (x-axis) according to themappositions and the chromosomalorder from1pter toYqter.B, the genome-wide frequencies of all significant gains (>0.2 of intensity ratio, topplot) and losses (<�0.2 of intensityratio, bottom plot) for each clone are shown for 29 cases of squamous cell carcinomas (black, above the x-axis) and 21cases of adenocarcinomas (gray, below the x-axis),respectively.The boundaries of individual chromosome and the location of centromere are indicated by vertical bars and dotted lines below the plots, respectively.


www.aacrjournals.orgClin Cancer Res 2005;11(23) December1, 2005 8236



DNA labeling, prehybridization, hybridization, and posthybridizationprocesses were done as described previously (19, 20). Arrays werescanned using GenePix 4100A scanner (Axon Instruments, Union City,CA) and the image was processed using GenePix Pro 6.0.

Data processing, normalization, and mapping of BAC clones. Nor-malization and re-aligning raw array CGH data were done using theweb-based array CGH analysis interface, ArrayCyGHt (http://genomics.

catholic.ac.kr/arrayCGH/; ref. 21). Mapping of large insert clones wasdone according to the genomic location in the UCSC genome browser(May 2004 freeze). In total, 2,987 successfully mapped BAC clones outof initial 3,014 clones were processed subsequently. All the genomiccoordinates such as cytogenetic bands or gene positions described inthis study are based on the same version of the human genomeavailable on the UCSC genome browser.

Table1. Genomic segments representing high copy number changes in NSCLC

Change Clone Cytoband Map position(Mb)

Size(Mb)

Observed cases* Putative cancer-related genes

Amplification RP11-45I3 1p36.13 15.94-16.84 0.9 SqCs4RP11-184I16 1p34.1 43.42-44.18 0.76 SqCs15 PTPRFRP5-881A21 1p12 118.51-118.96 0.45 SqCs17RP4-790G17/RP11-172I6 1q21.2-q22 145.67-152.49 6.81 AdCs1, SqCs23 AF1Q,TPM3, CTSSRP11-440P5/RP11-568N6 2p16.1-p14 59.90-63.96 4.06 AdCs16, SqCs9, SqCs14 RELRP11-251C9 3q25.1 151.88-152.64 0.75 SqCs22RP11-264D7/RP11-416O18 3q26.1-q26.33 168.03-182.82 14.78 SqCs2, SqCs8, SqCs9,

SqCs12, SqCs15, SqCs16,SqCs20, SqCs22

EVI1, SKIL,ECT2, PIK3CA

RP11-110C15/RP11-506F8 3q27.2-3q29 185.80-196.12 10.31 SqCs2, SqCs7, SqCs9,SqCs15, SqCs23, SqCs24

BCL6, HES

CTD-2324F15 5p15.32 6.15-6.47 0.31 AdCs21RP11-360O19 6p24.3 10.16-11.01 0.85 AdCs1RP11-472M19 6p12.1 55.80-57.09 1.29 SqCs1RP11-449P15/RP4-810E6 7p22.3-p22.1 0.69-5.85 5.16 AdCs1, AdCs13 NUDT1RP11-449G3/RP11-339F13 7p11.2 53.47-55.02 1.55 SqCs11RP5-1091E12/RP4-725G10 7p11.2 54.72-55.54 0.82 SqCs5 EGFRRP5-905H7/RP11-340I6 7q11.21-q11.21 62.13-62.49 0.36 AdCs1RP11-107L23 7q11.23 73.42-75.47 2.05 AdCs1RP11-17I10 7q22.3 105.57-106.49 0.91 SqCs25 PIK3CGRP11-115G12 8q12.3 65.01-66.36 1.35 SqCs29RP11-399H11/RP11-83N9 9q34.3 134.47-135.81 1.33 AdCs13RP11-554A11 11q13.3 68.38-68.93 0.55 SqCs9RP11-21D20 11q13.4 69.78-70.34 0.56 SqCs25RP11-45C5/RP11-21G19 11q22.1-q22.2 99.95-100.77 0.82 AdCs21CTD-3245B9 11q23.3 117.67-118.56 0.88 AdCs21 MLL, DDX6RP3-432E18/RP11-89H19 12q13.11 46.13-46.52 0.39 SqCs10RP11-490O6/CTD-2504F3 16p13.13-p13.11 11.11-15.77 4.66 AdCs1RP11-105C19/CTD-2515A14 16p12.1 22.31-24.18 1.87 AdCs1RP5-906A24/RP11-94L15 17q12 33.91-35.02 1.1 AdCs1 MLLT6RP11-769O8/RP11-291G24 18p11.32 0.52-1.33 0.8 SqCs10 YES1,TYMSCTD-2547N9/CTC-444D3 19p13.2 8.06-8.78 0.71 AdCs13CTC-260F20 19p13.11 18.59-20.01 1.41 SqCs1 JUNDCTD-2527I21/CTC-246B18 19q13.11-q13.2 39.22-44.14 4.92 SqCs9 HKR, SPINT2RP11-158G19/CTD-2337J16 19q13.42 58.68-59.30 0.62 AdCs21RP4-742J24/RP11-104O6 20p12.2-p12.1 11.17-12.28 1.11 SqCs25RP3-324O17/RP5-857M17 20q11.21 28.92-29.65 0.73 SqCs1CTA-433F6/RP11-50L23 22q11.21-q11.22 16.84-19.20 2.36 AdCs21RP5-925J7/CTA-722E9 22q13.32-q13.33 47.47-47.94 0.46 SqCs1, SqCs3

Homozygousdeletion

RP11-765C10 10q23.31 89.79-90.20 0.40 SqCs2 PTEN

RP11-122K13 10q26.3 134.36-135.11 0.75 SqCs25, SqCs26CTD2547N9/CTD444D3 19p13.2 8.06-9.44 1.38 AdCs11

NOTE:The boundary of each high copy number of change is defined by the corresponding insert clone. Cytogenetic band and map position of clones are based on thepublic genome database (UCSC genome, May 2004 freeze).*In case of more than two observed cases, the boundary of high copy number change was defined as the most extended set of clones, so they were not necessarilyoverlapping.

Array CGHAnalysis of NSCLCand Clinicopathologic Implications




Data analysis for chromosomal alterations. To set the cutoff value forchromosomal alterations of individual large insert clones, we did aseries of four independent normal hybridizations (three sex-matchedand one male versus female hybridizations) as a control. The averageSD value of the control batch was 0.081. Adopting the criteria of aprevious study (22), the cutoff value for the copy number aberrationswas set to be F0.2 in log2 ratio in this study, >2-fold of control SD. Theentire chromosome arm gain or loss was determined as previouslydescribed (23). Regional copy number change was defined as DNAcopy number alteration limited to part of a chromosome. High-levelamplification of clones was defined when their intensity ratios were>1.0 in log2 scale, and vice versa for homozygous deletion. Theboundary of copy number change was assigned to be halfway betweenthe two neighboring clones.

Definition of minimally altered regions. To define MARs ofchromosomal gain or loss, we used CGH-Miner (http://www-stat.stanford.edu/fwp57/CGH-Miner/) to smooth the raw intensity ratioand to identify the breakpoints of chromosomal alterations (24). Aseries of four normal hybridizations were combined as a control andthe analysis was done with recommended program variables. Thesignificant gains or losses reported by the program were directly usedfor subsequent aligning procedures. Minimal regions of chromosomalgains and losses were determined by altered segments recurring for atleast seven samples.

Statistical analysis. The significance of the differences in chromo-somal arm changes between squamous cell carcinomas and adenocar-cinomas was tested by two-sided Fisher’s exact test. The correlationsbetween recurrent genetic changes on minimally altered regions wereassessed using univariate pairwise Pearson’s correlation. For multiplecomparisons, the step-down Sidak method was used to adjust theoverall level of significance. In this case, the pairs of genetic changeson the same chromosomal arm were excluded for the concordanceanalysis. The correlations between genetic alterations and clinicalvariables were analyzed by two-sided Fisher’s exact test. All the MARs aswell as chromosomal arm changes were included in the analysis. Forcomparison, four kinds of clinical variables were treated as categoricalvariables such as age (<60 versus z60 years), stage (stages I and II asearly versus stages III and IV as advanced), lymph node status (negativeversus positive), and the disease recurrence (presence versus absence).Kaplan-Meier method was used for survival analysis and the differencebetween survival curves was compared using the log-rank test inunivariate model. To identify independent prognostic factors afteradjusting clinical variables such as age, sex, stage, treatment, metastasis,and recurrence, Cox regression was done. In all statistical analyses,P < 0.05 was considered significant.

Results

Comprehensive profiling of genomic alterations in non–smallcell lung cancers. The overall genomic alterations observed inthe 50 NSCLC cases (29 squamous cell carcinomas and 21adenocarcinomas) are illustrated in Fig. 1A. The frequency plotsof the chromosomal changes in the 50 NSCLC cases show thatthey are not randomly distributed but clustered in several hotregions across all the chromosomes (Fig. 1B). Eight chromo-somal arms were frequently gained: 19q (40%, 20 of 50 cases),20q (26%), 22q (24%), 3q (22%), 19p (22%), 1q (20%), 5p(20%), and 17q (20%). Also, six chromosomal arms werefrequently lost: Yp (52%), Yq (46%), 9p (42%), 3p (26%), 17p(24%), and 4q (20%). Six chromosomal changes differentiallydistributed between squamous cell carcinomas and adenocarci-nomas. Gains of 3q and 12p as well as losses of 3p, Yp, and Yqwere found to be specific to squamous cell carcinomas, whereas again of 6p was found to be specific to adenocarcinomas (seeSupplementary Table S2). The array CGH signal intensity ratio

(in log2 scale) data of the 50 NSCLC can be downloaded fromour web site (http://lib.cuk.ac.kr/micro/CGH/lung.htm).High-level amplification and homozygous deletion. In total,

98 large insert clones showed high-level amplifications at leastin one case and they clustered in 36 different genomicsegments. The genomic size of the amplicons ranged from0.31 to 14.78 Mb. All the identified amplicons along with theputative cancer-related genes located in these amplicons aresummarized in Table 1. Figure 2A shows an example of a highcopy number gain observed recurrently around 3q26-q28. Thefirst (3q26), which is as large as 14.78 Mb, harbors severalputative oncogenes such as EVI1, SKIL, ECT2 , and PIK3CA . Theother (3q28), which is 10.31 Mb in size, contains the putativeoncogenes, BCL6 and HES . In all 50 NSCLC cases, only threehomozygous deletions were identified (Table 1). Among them,a homozygous deletion of RP11-765C10 (10q23.31) harborsthe tumor suppressor gene PTEN (Fig. 2B).Minimal regions of recurrent genomic changes. High copy

number changes were relatively rare among the 50 cases.However, single copy number changes were more common andwidespread. In total, 13 MAR gains (MAR-G) and 4 MAR losses(MAR-L) were identified. Table 2 lists the map position, size,and cancer-related genes located in the 17 MARs. Examplesof MAR-G and MAR-L are illustrated in Fig. 3. The MAR-G on

Fig. 2. Individualprofiles of high copynumber changes.A, high-level amplificationson 3q21-q29 for SqCs9 and SqCs22. B, a homozygous deletion on10q23.31forSqCs2. In the intensity ratio profiles, the x-axis represents the map position ofcorresponding clone according to theUCSChumangenome (May 2004 freeze) andthe intensity ratios were assigned to the y-axis.The schematic presentation ofcytogenetic bands as well as a map position is shownbelow the plot.





1p36-p34, which was observed in 12 cases, contains severalputative cancer-related genes such as PAX7, FGR, LCK , andMYCL1 . In addition, another MAR-G on 1p32.3, which wasfound in nine cases, contains the putative cancer-related gene,TTC4 (Fig. 3A). The MAR-L on 5q23.2-q31.1 in seven casesincludes several putative tumor suppressor genes such as IRF1,CDKL3 , and RAD50 (Fig. 3B).Correlation between minimally altered regions. Pairwise

correlation analysis between the MARs was done to determineif such genomic changes appeared concordantly in a set ofNSCLC cases. For comparison, all possible combinationsbetween the 17 MARs were considered except for pairs on thesame chromosomal arms. A significantly positive correlationwas observed for three pairs of MARs (see SupplementaryTable S3). The MAR-G on 19q13.1 correlated with the MAR-Gson 6p21.3-p21.1 (r = 0.549; P = 0.0482) and 19p13.2-p13.1(r = 0.672; P = 0.0016). Another significant association was

found between two MAR-Gs on 8p12.2-p12.1 and 8q11.2-12.1(r = 0.610; P = 0.0370).

Association between genomic aberrations and clinical charac-teristics. Four types of clinical variables (age, stage, lymphnode, and recurrence) were analyzed for their associationwith the genomic alterations identified (see SupplementaryTable S4). Significant associations were observed for the MAR-Lon 13q21 with cancers from those aged <60 and an advancedstage (stages III and IV). The chromosomal gain of Xq was alsofound to be associated with an advanced stage and diseaserecurrence. The MAR-G on 1p32 and a chromosomal gain of Ypwere associated with being lymph node–negative.

Survival analysis was done to assess the prognostic valuesof the genetic aberrations identified. Using Kaplan-Meiermethods, we identified that six genetic aberrations associatedwith a relatively poor survival (Fig. 4); gain of 10p (P = 0.0091)and 16q (P = 0.0262), loss of 9p (P = 0.0082) and 13q

Table 2. Minimal regions of recurrent copy number changes

Change Clone Cytoband Map position Size (Mb) Frequency*(squamous cellcarcinomas/adenocarcinomas)

Putative cancer-related genes

Gain RP4-560M15/RP4-534D1 1p36.21-p34.1 14.94-45.92 30.97 12 (6/6) PAX7, FGR, LCK,MYCL1RP5-1070D5 1p32.3 54.77-56.08 1.31 9 (4/5) TTC4RP4-706A17/RP11-137A12 1q21.1-q23.3 142.95-158.14 15.19 9 (3/6) BCL9, AF1Q,TPM3, PRCC, NTRK1RP11-260K8/RP11-335E8 2p16.1-p12 58.65-76.8 18.15 7 (4/3) REL,MEISRP11-498P15/RP11-525C11 3q26.1-q28 162.86-192.98 30.11 17 (17/0) EVI1, SKIL, ECT2, PIK3CA,BCL6RP11-269G2/RP1-137K24 5p15.2-p15.1 12.75-15.75 2.99 9 (3/6)RP3-349A12/RP11-501I18 6p21.31-p21.1 34.46-43.44 8.97 7 (2/5) PIM1, CCND3RP11-350N15/RP11-44K6 8p12 37.82-40.24 2.42 8 (6/2) FGFR1RP11-137L15/RP11-513O17 8q11.21-q12.1 48.33-58.91 10.58 7 (4/3) MOS, LYNRP11-67N21/RP11-349C2 8q24.11-q24.3 117.89-145.77 27.88 9 (6/3) NOV,MYC,WISP1, PTK2CTD-2547N9/CTD-3149D2 19p13.2-p13.11 8.06-18.59 10.53 9 (3/6) LYL1, BRD4, ICAM1, JAK3,TYK2RP11-9B17 19q13.12 42.52-43.38 0.85 13 (5/8) HKR1, SPINT2RP5-1107C24/RP13-152O15 20q13.33 59.71-62.16 2.44 7 (3/4) BIRC7, EEF1A2, PTK6,TNFRSF6B

Loss RP11-434D11/CTB-28J9 5q23.2-q31.1 125.7-135.73 10.03 7 (5/2) CDKL3,RAD50, IRF1RP11-478B20/RP11-516G5 13q21.1 54.6-56.16 1.55 7 (2/5)RP11-480K16 13q34 111.9-112.49 0.58 8 (4/4)RP4-715N11 20q13.2 49.82-51.19 1.37 9 (6/3)

NOTE: Gain and loss in the first column represent MAR-G andMAR-L, respectively.*The frequency represents the number of samples with the corresponding genomic changes in two kinds of NSCLC subtypes.

Fig. 3. Examples of minimal regions of genomicgain or loss. MARwas defined as a commonlyaltered segment recurring for at least seven cases.Each sample is represented as an individual lane.MARs are schematically shown as a colored boxbelow the cytogenetic bands: red, copy numbergain; green, copy number loss; black, no change.A, twominimally gained regions on chromosome1pwith different genomic sizes in16 cases. B, minimalregion of losses on chromosome 5q common toseven NSCLC samples.





(P = 0.0019), and the MAR-Gs on 6p21 and 19q13 (P = 0.0265and 0.0295, respectively). Multivariate analyses using all thegenetic alterations identified, as well as the clinical variablessuch as age, gender, stage, treatment, metastasis, and recurrenceshowed that four genetic alterations and three clinical variablesremained independent factors to be significantly associatedwith a poor survival outcome (Table 3). One of the four geneticalterations was a MAR-G on 6p21 and the other three were aloss of 9p, and gains of 7p and 9p.

Discussion

Using whole-genome array CGH strategy, we successfullyidentified novel chromosomal aberrations as well as previ-ously identified ones in NSCLC. This study focused on thepotentially meaningful genomic changes such as recurrentsingle copy changes as well as high-level amplifications ordeletions. For this, microdissection was used to remove thenontumor tissues, and the microdissected DNA was hybridizedto arrays without performing whole genome amplification,which reduced any possible bias due to a random amplification.

The frequent chromosomal changes in this study are largelyconsistent with previous cytogenetic analysis (7–11), including aloss of the Y chromosome in male patients (5, 6). It is notablethat the copy number alterations on the small chromosomessuch as 19, 20, and 22 were much more frequent in our study.This might be due to the differences in the analytic methods.However, it is more likely to reflect the potential of array CGH toimprove the low resolution of conventional CGH as describedelsewhere (25). The genomic size of the high copy numberchanges ranged from 0.31 to 14.78 Mb, and most of them were<5 Mb. Genomic changes <5 Mb are likely to be novel becausethey cannot be detected using conventional CGH (12).

To date, two array-based CGH analyses of lung cancer havebeen published (26, 27). Our results are in general agreementwith the previous array CGH results. For example, the 30-Mb

sized recurrently gained region around 3q26 reported byMassion et al. (26) overlapped with the MAR-G on 3q26-q28in this study. Other metaphase CGH studies have also shownfrequent amplifications around the same region in squamouscell carcinomas (9–11). However, some of the MARs identifiedwere not consistent with them. Gain of 3q26 was the onlyrecurrent alteration in Massion et al.’s study, whereas weidentified not only 3q26 but also 16 more MARs across variouschromosomes. The difference is thought to be due to theresolution. This study placed 2,987 large insert clones in 1 Mbintervals (average of 125 clones per chromosome), whereasthey used 348 BAC clones (average of 15 clones per chro-mosome, at most 78 clones on chromosome 3). That mightexplain why more MARs could be defined. In Jiang et al.’s study(27), the recurrent genomic alterations were only partlycompatible with this result, and there was no clear minimalrecurrent gain on 3q. They used a cDNA microarray rather thana BAC/PAC array for CGH analysis. Despite its advantages, thesensitivity and reliability for detecting copy number changes,particularly single copy changes, is known to be limited (18).

Several interesting cancer-related genes are located in thegenomic alteration regions identified in this study. For example,PIK3CA on 3q26-q28, which is one of the genes in the mostcommon MAR-G in this study, is believed to contribute to thetumorigenesis of squamous cell carcinomas by involving inthe phosphoinositide-3-OH kinase signaling pathway (26). TheECT2 oncogene, which is located in the same locus, is known toactivate the Rho signaling pathway leading to a malignanttransformation (28). In our unpublished data,6 ECT2 is fre-quently overexpressed in primary lung cancers. Although, therehas been no report of ECT2 overexpression in lung cancer, thissuggests the involvement of ECT2 in malignant transformationor the progression of lung cancer. Most high-level amplifications

6 M.S. Kwon, H.M. Kang, and Y.J. Chung, manuscript in preparation.

Fig. 4. Kaplan-Meier survival curves.The survivalcurves for the cases with (thick line) or without(thin line) specific genomic changes are plottedusing the Kaplan-Meier method.The chromosomalchanges associatedwith relatively poor survival arepresented with the significance level; gain of10p(A) and16q (B), loss of 9p (C) and13q (D), andMAR-Gs on 6p21 (E) and19q13 (F).





were usually observed in one or two cases with the exceptions ofthe amplifications on 3q. They might reflect the individualnature of the genomic evolution for the respective NSCLC cases.Among the putative cancer-related genes in the high-levelamplification region (Table 1), the expression of the AF1Q,TPM3, REL, SKIL, ECT2, BCL6, MLLT6, YES1, and HKR geneshave not been reported in lung cancer.

A homozygous deletion on 10q23.31 observed in onesquamous cell carcinoma case contains the well-known tumorsuppressor gene, PTEN. PTEN is known to encode lipidphosphatase, which negatively controls the signaling proteinsactivated in the phosphoinositide-3-OH kinase pathway (29).This suggests a potential role of the phosphoinositide-3-OHkinase signaling pathway in NSCLC pathogenesis.

In contrast to the high copy number changes that werelargely limited to a few samples, single copy changes werefound in many more samples, which is indicative of a sharedmechanism common to the earlier stage of NSCLC. Minimalrecurrent gains and losses were successfully identified usinghigh-resolution array CGH. Seventeen MARs of various sizeswere defined. The MAR-Gs on 1p, 2p, 6p, 8p, 19p, and 20palong with MAR-Ls on 5q and 20q are believed to be novelfeatures in lung cancer, which shows the advantage of genome-wide, high-resolution mapping of the genomic alterations.Interestingly, three pairs of MAR-Gs (19q13.1 and 6p21, 19p13and 19q13.1, and 8p12 and 8q11-12) showed significantcorrelations among themselves, suggesting a possible collabo-rative role in the tumorigenesis of NSCLC. Further investiga-tions will be needed to confirm the functional consequences of

the associations between the MARs. Some of the MARs showedsignificant correlations with the clinical features. This suggeststhat the common single copy changes identified by high-resolution analysis can be useful biomarkers for the clinicalcharacteristics of lung cancer.

Survival analysis revealed that six genetic alterations wereassociated with a poor survival outcome in the univariatemodel (Fig. 4). Among those six alterations, a loss of 9p wasreported to be associated with a poor survival outcome (30).However, there has been no report about the associationbetween the other five genomic alterations and survivaloutcomes in lung cancer. These genomic alterations might bea novel genetic indicator of the prognosis of NSCLC after theappropriate validation. In particular, two of these alterationsare MARs, which appeared concordantly (P = 0.0482). Thesetwo MARs, MAR-Gs on 6p21 and 19q13, contain cancer-relatedgenes such as PIM1, CCND3 (both in 6p21), and HKR1(19q13). The high expression level of HKR1 after administeringplatinum drugs has been reported to be associated with theacquisition of resistance to chemotherapy (31). There is noreport demonstrating an alteration of CCND3 and PIM1 proto-oncogene in lung cancer. However, both genes are well knownto be involved in the tumorigenesis pathways of varioustumors. Therefore, further investigations will be needed toevaluate their specific implications in lung cancer.

Subsequent Cox regression analysis identified seven factors,including four genomic alterations such as MAR-G on 6p21, 9ploss, 7q gain, and 9q gain, to be independent indicators of apoor survival outcome. This indicates that in addition to theclinical factors, precisely defined recurrent genetic alterationscan be useful biomarkers for the prognosis of NSCLC.However, due to the limited number of samples in this study,further studies with a larger sample size will be needed toconfirm the prognostic implication of these genomic alter-ations and to identify further reliable prognostic markers.

This study showed that a well-designed high-resolution arrayCGH could define more novel regions possibly associatedwith the tumorigenesis of lung cancer. Therefore, these resultswill give a clue for further studies to elucidate lung cancerpathogenesis or to develop biomarkers for predicting theprognosis or treatment response of lung cancer.

Acknowledgments

We thank the Wellcome Trust Sanger Institute Microarray Facility for printingBAC array slides.

Table 3. Independent predictors of poor survival in50 NSCLCs

Variable Hazard ratio 95% Confidence interval P

MARon 6p21 3.961 1.349-11.626 0.0122Loss of 9p 4.256 1.746-10.373 0.0014Gain of 7p 15.563 3.399-71.268 0.0004Gain of 9q 9.546 1.400-65.077 0.0212Sex (male) 9.528 1.360-66.733 0.0232Stage 3.916 1.212-12.659 0.0226Metastasis 4.428 1.763-11.121 0.0015

NOTE: Cox proportional hazards regression after adjusting for age, treatment,and recurrence.



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2005;11:8235-8242. Clin Cancer Res Tae-Min Kim, Seon-Hee Yim, Jung-Sook Lee, et al. Cancers

Small Cell Lung−Clinicopathologic Implications in Non Genome-Wide Screening of Genomic Alterations and Their

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