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

Small Cell LungClinicopathologic Implications in NonGenome-Wide Screening of Genomic Alterations and Their

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Genome-Wide Screening of Genomic Alterations and

Their Clinicopathologic Implications in Non ^ Small

Cell Lung Cancers

Tae-Min Kim,

1

Seon-Hee Yim,

2

Jung-Sook Lee,

1

Mi-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 genomic

aberrations across the whole genome of non ^ small cell lung cancer cells with high-resolution

and investigated their clinicopathologic implications.

Experimental Design: One-megabase resolution array comparative genomic hybridization was

applied to 29 squamous cell carcinomas and 21adenocarcinomas of the lung.Tumor and normal

tissues were microdissected and the extracted DNA was used directly for hybridization without

genomic amplification.The recurrent genomic alterations were analyzed for their association with

the 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 on

10p, 16q, 9p, 13q, 6p21, and 19q13 were associated with poor survival. Multivariate analysis

showed that alterations on 6p21, 7p, 9q, and 9p remained as independent predictors of poor

outcome. In addition, significant correlations were observed for three pairs of minimally altered

regions (19q13 and 6p21, 19p13 and 19q13, and 8p12 and 8q11), which indicated their possible

collaborative roles.

Conclusions: These results show that our approach is robust for high-resolution mapping of

genomic alterations.The novel genomic alterations identifiedin this study, along with their clinico-

pathologic implications, would be useful to elucidate the molecular mechanisms of lung cancer

and 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 up

almost 80% of all total lung cancer cases. Among the NSCLC,squamous cell carcinomas and adenocarcinomas are the two

major subtypes. Histologically different subtypes have differentclinical courses, and might require individual therapeutic

approaches.Some genomic aberrations in tumors have been suggested

to be prognostic markers or can be used to identify the targetgenes for treatment or prevention (3, 4). Likewise, in other

solid tumors, chromosomal aberrations are thought to be

critical 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 of

efficient 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. Recurrent

genomic alterations have been observed in NSCLC, includingthe gains of partial or whole chromosomal arms on 1q, 3q, 5p,

HumanCancer Biology

AuthorsAffiliations: 1Department of Microbiology, College of Medicine, Catholic

University of Korea, Socho-gu, Seoul; 2Korea National Cancer Center, Research

Institute, Division of Cancer Control and Epidemiology, Gyeonggi-do; Departments

of3

Pathology and4

Thoracic and Cardiovascular Surgery, College of Medicine,

Dankook University, Cheonan, Chungnam, Republic of Korea; and5

The Wellcome

Trust Sanger Institute, Hinxton, Cambridge, United KingdomReceived 5/31/05; revised 8/3/05; accepted 9/1/05.

Grant support: Korea Health 21 R&D Project, Ministry of Health and Welfare,

Republic of Korea (01-PJ3-PG6-01GN07-0004).

The costs of publicationof this article were defrayed inpart by the paymentof page

charges. This article must therefore be hereby marked advertisement in accordance

with18 U.S.C. Section1734 solely to indicatethis 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 of

Medicine, Catholic University of Korea, 50 5 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

www.aacrjournals.org Clin Cancer Res 2005;11(23) December 1, 20058235

http://clincancerres.aacrjournals.org/http://clincancerres.aacrjournals.org/

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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 conventional

CGH 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 and Methods

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. Marys 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 Am

thickness on a gelatin-coated slide using 2800 Frigocut (Reighert-Jung,

Germany). After H&E staining, tumor cellrich area (>60% of tumor

cells) and histologically normal cell area were selected under the

microscope and dissected manually. Microdissected tissues were

transferred into the cell lysis buffer (1% proteinase-K in TE buffer)

and DNA was extracted. DNA from normal tissue was used as

reference DNA for array CGH. Extracted DNA was purified using aDNA purification Kit (Solgent, Daejeon, Korea) and used for dye

labeling reactions.Array comparative genomic hybridization and image analysis. We

used human large insert clone arrays with 1 Mb resolution across the

whole genome printed by the Sanger Institute Microarray Facility (19).

Fig.1. Genome-wide copy numberalterations in 50 cases of NSCLC.A, genomic profiles of 29 squamous cell carcinomas (top) and 21adenocarcinomas (bottom). FiftyNSCLC cases are represented in individuallanes 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 indicatedin the referencecolor bar. A total of 2,987 BAC clones were ordered (x-axis) according to themappositions andthe chromosomalorder from1pter toYqter.B, the genome-wide frequenciesof all significant gains (>0.2 of intensity ratio, topplot) andlosses (

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DNA labeling, prehybridization, hybridization, and posthybridizationprocesses were done as described previously (19, 20). Arrays were

scanned 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 the

web-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 out

of initial 3,014 clones were processed subsequently. All the genomic

coordinates such as cytogenetic bands or gene positions described in

this study are based on the same version of the human genome

available on the UCSC genome browser.

Table 1. 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 SqCs4

RP11-184I16 1p34.1 43.42-44.18 0.76 SqCs15 PTPRF

RP5-881A21 1p12 118.51-118.96 0.45 SqCs17

RP4-790G17/RP11-172I6 1q21.2-q22 145.67-152.49 6.81 AdCs1, SqCs23 AF1Q,TPM3, CTSS

RP11-440P5/RP11-568N6 2p16.1-p14 59.90-63.96 4.06 AdCs16, SqCs9, SqCs14 REL

RP11-251C9 3q25.1 151.88-152.64 0.75 SqCs22

RP11-264D7/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 AdCs21

RP11-360O19 6p24.3 10.16-11.01 0.85 AdCs1

RP11-472M19 6p12.1 55.80-57.09 1.29 SqCs1

RP11-449P15/RP4-810E6 7p22.3-p22.1 0.69-5.85 5.16 AdCs1, AdCs13 NUDT1

RP11-449G3/RP11-339F13 7p11.2 53.47-55.02 1.55 SqCs11

RP5-1091E12/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 AdCs1

RP11-107L23 7q11.23 73.42-75.47 2.05 AdCs1

RP11-17I10 7q22.3 105.57-106.49 0.91 SqCs25 PIK3CG

RP11-115G12 8q12.3 65.01-66.36 1.35 SqCs29

RP11-399H11/RP11-83N9 9q34.3 134.47-135.81 1.33 AdCs13

RP11-554A11 11q13.3 68.38-68.93 0.55 SqCs9

RP11-21D20 11q13.4 69.78-70.34 0.56 SqCs25

RP11-45C5/RP11-21G19 11q22.1-q22.2 99.95-100.77 0.82 AdCs21

CTD-3245B9 11q23.3 117.67-118.56 0.88 AdCs21 MLL, DDX6

RP3-432E18/RP11-89H19 12q13.11 46.13-46.52 0.39 SqCs10

RP11-490O6/CTD-2504F3 16p13.13-p13.11 11.11-15.77 4.66 AdCs1

RP11-105C19/CTD-2515A14 16p12.1 22.31-24.18 1.87 AdCs1

RP5-906A24/RP11-94L15 17q12 33.91-35.02 1.1 AdCs1 MLLT6

RP11-769O8/RP11-291G24 18p11.32 0.52-1.33 0.8 SqCs10 YES1,TYMS

CTD-2547N9/CTC-444D3 19p13.2 8.06-8.78 0.71 AdCs13

CTC-260F20 19p13.11 18.59-20.01 1.41 SqCs1 JUND

CTD-2527I21/CTC-246B18 19q13.11-q13.2 39.22-44.14 4.92 SqCs9 HKR, SPINT2

RP11-158G19/CTD-2337J16 19q13.42 58.68-59.30 0.62 AdCs21

RP4-742J24/RP11-104O6 20p12.2-p12.1 11.17-12.28 1.11 SqCs25

RP3-324O17/RP5-857M17 20q11.21 28.92-29.65 0.73 SqCs1

CTA-433F6/RP11-50L23 22q11.21-q11.22 16.84-19.20 2.36 AdCs21

RP5-925J7/CTA-722E9 22q13.32-q13.33 47.47-47.94 0.46 SqCs1, SqCs3

Homozygous

deletion

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

RP11-122K13 10q26.3 134.36-135.11 0.75 SqCs25, SqCs26

CTD25 47N9/CTD4 44D3 19p13.2 8.0 6-9.4 4 1.38 AdCs11

NOTE:The boundary of eachhigh copy number of change is defined by the corresponding insert clone. Cytogenetic bandand map position of clones are based on the

public 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 necessarily

overlapping.

Array CGHAnalysisofNSCLCandClinicopathologic Implications



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Data analysis for chromosomal alterations. To set the cutoff value for

chromosomal alterations of individual large insert clones, we did a

series of four independent normal hybridizations (three sex-matchedand one male versus female hybridizations) as a control. The average

SD value of the control batch was 0.081. Adopting the criteria of a

previous study (22), the cutoff value for the copy number aberrations

was 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 previously

described (23). Regional copy number change was defined as DNA

copy 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. The

boundary of copy number change was assigned to be halfway betweenthe two neighboring clones.

Defi nition of minim ally alter ed regio ns. To define MARs of

chromosomal gain or loss, we used CGH-Miner (http://www-stat.

stanford.edu/fwp57/CGH-Miner/) to smooth the raw intensity ratio

and to identify the breakpoints of chromosomal alterations (24). Aseries of four normal hybridizations were combined as a control and

the analysis was done with recommended program variables. The

significant gains or losses reported by the program were directly used

for subsequent aligning procedures. Minimal regions of chromosomal

gains 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 Fishers exact test. The correlations

between recurrent genetic changes on minimally altered regions were

assessed using univariate pairwise Pearsons correlation. For multiplecomparisons, the step-down Sidak method was used to adjust the

overall level of significance. In this case, the pairs of genetic changes

on the same chromosomal arm were excluded for the concordance

analysis. The correlations between genetic alterations and clinicalvariables were analyzed by two-sided Fishers exact test. All the MARs as

well as chromosomal arm changes were included in the analysis. For

comparison, four kinds of clinical variables were treated as categorical

variables such as age (

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1p36-p34, which was observed in 12 cases, contains severalputative cancer-related genes such as PAX7, FGR, LCK, and

MYCL1. In addition, another MAR-G on 1p32.3, which was

found 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 of

NSCLC cases. For comparison, all possible combinationsbetween the 17 MARs were considered except for pairs on the

same chromosomal arms. A significantly positive correlationwas observed for three pairs of MARs (see Supplementary

Table 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 association

with the genomic alterations identified (see Supplementary

Table S4). Significant associations were observed for the MAR-Lon 13q21 with cancers from those aged

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(P = 0.0019), and the MAR-Gs on 6p21 and 19q13 (P = 0.0265and 0.0295, respectively). Multivariate analyses using all the

genetic alterations identified, as well as the clinical variablessuch as age, gender, stage, treatment, metastasis, and recurrence

showed that four genetic alterations and three clinical variablesremained independent factors to be significantly associated

with a poor survival outcome (Table 3). One of the four geneticalterations was a MAR-G on 6p21 and the other three were a

loss of 9p, and gains of 7p and 9p.

Discussion

Using whole-genome array CGH strategy, we successfully

identified novel chromosomal aberrations as well as previ-ously identified ones in NSCLC. This study focused on the

potentially meaningful genomic changes such as recurrentsingle copy changes as well as high-level amplifications or

deletions. For this, microdissection was used to remove thenontumor tissues, and the microdissected DNA was hybridized

to 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 a

loss of the Y chromosome in male patients (5, 6). It is notablethat the copy number alterations on the small chromosomes

such 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 described

elsewhere (25). The genomic size of the high copy numberchanges ranged from 0.31 to 14.78 Mb, and most of them were

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were usually observed in one or two cases with the exceptions ofthe amplifications on 3q. They might reflect the individual

nature of the genomic evolution for the respective NSCLC cases.Among the putative cancer-related genes in the high-level

amplification region (Table 1), the expression of the AF1Q,TPM3, REL, SKIL, ECT2, BCL6, MLLT6, YES1 , and HKR genes

have not been reported in lung cancer.A homozygous deletion on 10q23.31 observed in one

squamous cell carcinoma case contains the well-known tumorsuppressor gene, PTEN. PTEN is known to encode lipid

phosphatase, 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 were

found in many more samples, which is indicative of a sharedmechanism common to the earlier stage of NSCLC. Minimal

recurrent gains and losses were successfully identified usinghigh-resolution array CGH. Seventeen MARs of various sizes

were defined. The MAR-Gs on 1p, 2p, 6p, 8p, 19p, and 20palong with MAR-Ls on 5q and 20q are believed to be novel

features 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, 19p13

and 19q13.1, and 8p12 and 8q11-12) showed significant

correlations 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 suggests

that the common single copy changes identified by high-resolution analysis can be useful biomarkers for the clinical

characteristics of lung cancer.Survival analysis revealed that six genetic alterations were

associated with a poor survival outcome in the univariatemodel (Fig. 4). Among those six alterations, a loss of 9p was

reported to be associated with a poor survival outcome (30).However, there has been no report about the association

between the other five genomic alterations and survivaloutcomes in lung cancer. These genomic alterations might be

a novel genetic indicator of the prognosis of NSCLC after theappropriate validation. In particular, two of these alterations

are MARs, which appeared concordantly (P = 0.0482). Thesetwo MARs, MAR-Gs on 6p21 and 19q13, contain cancer-related

genes 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 the

acquisition of resistance to chemotherapy (31). There is no

report 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 the

clinical 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 associated

with the tumorigenesis of lung cancer. Therefore, these resultswill give a clue for further studies to elucidate lung cancer

pathogenesis or to develop biomarkers for predicting theprognosis or treatment response of lung cancer.

Acknowledgments

We thank the Wellcome Trust Sanger Institute Microarray Facility for printing

BAC array slides.

Table 3. Independent predictors of poor survival in

50 NSCLCs

Variable Hazard ratio 95% Confidence interval P

MAR on 6p21 3.961 1.349-11.626 0.0122

Loss of 9p 4.256 1.746-10.373 0.0014

Gain of 7p 15.563 3.399-71.268 0.0004

Gain of 9q 9.546 1.400-65.077 0.0212

Sex (male) 9.528 1.360-66.733 0.0232

Stage 3.916 1.212-12.659 0.0226

Metastasis 4.428 1.763-11.121 0.0015

NOTE: Cox proportional hazards regressionafter adjusting for age, treatment,

and recurrence.

Array CGHAnalysisofNSCLCandClinicopathologic Implications


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