Analysis of genomic DNA alterations and mRNA expression patterns in a panel of human pancreatic...

RESEARCH ARTICLE

Analysis of Genomic DNA Alterations and mRNAExpression Patterns in a Panel of HumanPancreatic Cancer Cell Lines

Stephan Gysin,1 Paula Rickert,2 Kumar Kastury,2 and Martin McMahon1*

1Cancer Research Institute and Departmentof Cellular andMolecular Pharmacology,Universityof California,San Francisco Comprehensive Cancer Center,San Francisco,California2Incyte Genomics,Palo Alto,California

Genomic alterations influencing the expression and/or activity of tumor suppressors or oncogenes such as KRAS2, CDKN2A,

TP53, and DPC4 have been directly implicated in the initiation and progression of human pancreatic adenocarcinoma. In an

effort further to systematically characterize the genomic alterations that occur in this disease, we conducted a genome wide

analysis of alterations in gene copy number using array-based comparative genomic hybridization (CGH). For this analysis, we

utilized a panel of 25 human pancreatic cancer cell lines derived from either primary or metastatic tumors. This panel also

included a metastatic progression series of cell lines derived from COLO 357 cells. Array CGH permitted the identification of

alterations in the copy number of genes that might participate in the aberrant behavior of pancreatic cancer cells. In addition,

the acquisition of invasive and metastatic potential by derivatives of COLO 357 cells was accompanied by additional focal

genomic alterations including point mutations and amplification of KRAS2. To complement the array CGH analysis, we also

conducted an analysis of mRNA expression patterns in a subset of these cells using cDNA microarrays. By this means, we

identified a set of candidate genes, including those regulated by RAS signaling, that may contribute to the process of cancer cell

invasion and metastasis. Supplementary material for this article can be found on the Genes, Chromosomes, and Cancer website

at http://www.interscience.wiley.com/jpages/1045–2257/suppmat/index.html. VVC 2005 Wiley-Liss, Inc.

INTRODUCTION

Adenocarcinoma of the pancreas is the fifth lead-

ing cause of death from cancer in the United

States, claiming the life of �30,000 patients per

year. Treatment of this disease is severely ham-

pered by the lack of tools for early diagnosis and

treatment and also by the propensity of the pancre-

atic cancer cell to invade early and metastasize

(Jaffee et al., 2002; Kern et al., 2002). Conse-

quently, median survival and the 5-year survival

rate for pancreatic cancer are very low (�6 months

and �4%, respectively; Hruban et al., 2001; Kern

et al., 2001).

Significant progress has been made in catalogu-

ing the genetic alterations that accompany the ini-

tiation and progression of pancreatic cancer

(Hruban et al., 2000; Bardeesy and DePinho,

2002). The most frequently mutated somatic genes

in pancreatic cancer are RAS genes (�70%–90%),

mainly KRAS2 (Grunewald et al., 1989; Motojima

et al., 1993; Wilentz et al., 1998a; Slebos et al.,

2000). Also showing frequent mutations in pan-

creastic cancer are the INK4A/ARF (�90%), TP53(�70%), and DPC4 (�50%) tumor-suppressor

genes (Moore et al., 2001). However, it remains

unclear how such genetic alterations precisely

cooperate in order to promote the aberrant physiol-

ogy of the pancreatic cancer cell.

Genomic instability is a feature common to a

wide range of human malignancies and is likely to

be the foundation upon which the cancer cell

develops its propensity for clonal evolution, which

likely contributes to the emergence of cells with

an altered capacity for proliferation, survival, angio-

genesis, invasion, and metastasis (Hanahan and

Weinberg, 2000; Albertson et al., 2003; Albertson

and Pinkel, 2003). One of the most powerful tools

for profiling DNA copy number abnormalities

(CNA) in cancer cells and primary tumor speci-

mens is array-based comparative genomic hybrid-

*Correspondence to: Martin McMahon, Cancer Research Insti-tute and Department of Cellular and Molecular Pharmacology, Uni-versity of California, San Francisco Comprehensive Cancer Center,CCRB, 2340 Sutter St., Box 0128, San Francisco, CA 94115.E-mail: [email protected]

Supported by: UCSF Cancer Center; Lustgarten Foundation forPancreas Cancer Research (to M.M.); Black Foundation (to M.M.);Swiss National Science Foundation (postdoctoral fellowship toS.G.); Novartis Foundation (postdoctoral fellowship to S.G.).

Received 6 January 2005; Accepted 11 April 2005

DOI 10.1002/gcc.20216

Published online 31 May 2005 inWiley InterScience (www.interscience.wiley.com).

VVC 2005 Wiley-Liss, Inc.

GENES, CHROMOSOMES & CANCER 44:37–51 (2005)

ization (CGH; Albertson et al., 2003; Snijders

et al., 2003). Array CGH readily allows sensitive

detection of changes in gene copy number such

that the gain or loss of a single copy of a gene may

be detected (Snijders et al., 2001). Consequently,

we used array CGH to conduct a systematic analy-

sis of copy number abnormalities in a panel of

human pancreatic cancer–derived cell lines. A sub-

set of these cells represented a progression series

from low to high invasive/metastatic potential.

These cells were isolated by serial passage of

COLO 357 cells through nude mice (Vezeridis

et al., 1990; Vezeridis et al., 1992; Bruns et al.,

1999). We also identified regions of the genome

that showed consistent copy number abnormalities

in many of the cell lines. Interestingly, the acquisi-

tion of invasive/metastatic potential by the COLO

357–derived cell lines was accompanied by point

mutations of KRAS2 and a focal increase in KRAS2gene copy number.

We also conducted mRNA expression analysis

with the COLO 357-derived progression series of

cells by using cDNA microarrays. By comparing

mRNA expression profiles of cells with either low-

or high-invasive/-metastatic potential, we were able

to identify a set of candidate genes, the expression

of which correlates with increased metastatic

potential.

MATERIALS ANDMETHODS

Cell Lines and Culture Conditions

The MIAPaCa-2, Panc-1, CFPAC-1, HPAF II,

Capan-2, Hs766T, and BxPC-3 cell lines were a

generous gift from Dr. Paul Kirschmeier and Dr.

Chandra Kumar (Schering Plough Research Insti-

tute). The NOR-P1 cells were obtained from Dr.

N. Sato (Kyushu University, Japan). The HPAC,

SW1990, MPanc-96, Panc-02.03, Panc-08.13,

PL45, and SU86.86 cell lines were purchased from

ATCC. The Panc-02.13, Panc-03.27, Panc-04.21,

Panc-05.04, Panc-06.03, and Panc-10.05 cell lines

were a generous gift from Dr. Elizabeth Jaffee

(Johns Hopkins University). The COLO 357,

L3.3, L3.6sl, and L3.6pl cell lines were gifts from

Dr. Lance M. Tibbetts, Brown University, and Dr.

Isiah Fidler, M.D. Anderson Cancer Center

(Lieber et al., 1975; Owens et al., 1976; Yunis

et al., 1977; Metzgar et al., 1982; Kyriazis et al.,

1983; Tan et al., 1986; Drucker et al., 1988; Dahiya

et al., 1993; Norman et al., 1994; Peiper et al.,

1997; Jaffee et al., 1998; Bruns et al., 1999; Sato

et al., 2000).

The MIAPaCa-2, Panc-1, CFPAC-1, HPAF II,

Capan-2, Hs766T, NOR-P1, PL45, COLO 357,

L3.3, L3.6sl, and L3.6pl cell lines were grown in

DMEM. Cell lines BxPC-3, SU86.86, MPanc-96,

Panc-02.03, Panc-02.13, Panc-03.27, Panc-04.21,

Panc-05.04, Panc-06.03, Panc-08.13, and Panc-

10.05 were grown in RPMI 1640 including ITS

(insulin/transferring/selenium, from Invitrogen,

Carlsbad, CA). Cell line SW1990 was grown in Lei-

bovitz’s L-15 medium, and cell line HPAC was

grown in DMEM/Ham’s F12 (1:1 mixture), which

included ITS, 40 ng/ml hydrocortisone, and 10 ng/

ml EGF. All the media were supplemented with

10% fetal bovine serum and penicillin, streptomy-

cin, and L-glutamine.

DNA and RNA Isolation

Genomic DNA was isolated using a Wizard

Genomic DNAPurification Kit (Promega,Madison,

WI) with slight modifications. Isopropanol-precipi-

tated DNAwas spooled out of solution and washed

in 70% ethanol. The precipitate was then solubi-

lized in TE buffer and subjected to three subse-

quent phenol/chloroform extractions. The final so-

lution was ethanol-precipitated and rehydrated in

TE buffer at 48C overnight. DNA was quantitated

by UV absorption at 260 and 280 nm and also by

fluorometry.

RNA was isolated from 80% confluent COLO

357, L3.3, L3.6sl, and L3.6pl using an RNeasy

Maxi Kit (Qiagen, Valencia, CA). The eluted RNA

was quantitated by UV absorption at 260 and 280

nm and also with Ribogreen dye (Molecular

Probes, Eugene, OR) in a fluorescence assay.

Array CGH

DNA labeling and hybridization of BAC (bacte-

rial artificial chromosomes) arrays was performed as

described previously (Snijders et al., 2003). We

hybridized the labeled DNA samples to the

HumArray 2.0 (Snijders et al., 2001). This array

contained 2,464 BAC clones that were printed on

chromium slides and represent the human genome

at a 1.4-Mbp resolution.

Hybridization was carried out at 378C on a rock-

ing table for 48 hr. Arrays were then washed in

50% formamide containing 2� SSC (pH 7.0) at

488C for 15 min. Finally, the arrays were washed in

PN buffer [0.1 M sodium phosphate and 0.1%

NP40 (pH 8.0)] for an additional 15 min. Arrays

were then mounted in 90% glycerol, 10% PBS, and

1 lM DAPI and sealed with a cover slip.

38 GYSIN ETAL.

Analysis of mRNA Expression Using

cDNA-Based Microarrays

Two hundred nanograms of mRNA was con-

verted to either a Cy3- or a Cy5-labeled cDNA

probe using a custom labeling kit (Incyte

Genomics, Palo Alto, CA). Each reaction contained

50 mM Tris-HCl (pH 8.3), 75 mM KCl, 15 mM

MgCl2, 4 mM DTT, 2 mM dNTPs (0.5 mM each),

2 lg Cy3 or Cy5 random 9mer (Trilink, San Diego,

CA), 20 U RNase inhibitor (Ambion, Austin, TX),

and 200 U wild-type MMLV reverse transcriptase

(Panvera, Madison, WI). Correspondingly labeled

Cy3 and Cy5 cDNA products were combined and

purified on TE-30 columns (Clontech, Palo Alto,

CA) and then concentrated by ethanol precipita-

tion in the presence of different concentrations of

denatured human Cot-1 DNA and poly(A) oligonu-

cleotides. Probe DNA samples were resuspended

in hybridization buffer. Arrays were hybridized in

duplicate for each sample against a pooled refer-

ence consisting of equal amounts of RNA isolated

from all the cell lines being analyzed.

Arrays used for this analysis were UniGEM Ver-

sion 2 (UGV2) human cDNA arrays (Incyte

Genomics), which represent distinct Unigene clus-

ters. The arrays comprised 9,320 spotted cDNAs

(9,128 PCR products from cDNA clones represent-

ing 7,434 genes, plus 192 control spots). There was

no replicate spotting on the arrays.

Hybridization of labeled cDNA probes was per-

formed in 20 ll of 5� SSC, 0.1% (w/v) SDS, and

1 mM DTT at 608C for 6–17 hr. Microarrays were

then washed after hybridization in 1� SSC, 0.1%

(w/v) SDS, and 1 mM DTTat 458C for 10 min and

then in 0.1� SSC, 0.2% (w/v) Igepal (Sigma-

Aldrich, St. Louis, MO), and 1 mM DTT at room

temperature for 3 min.

Image Analysis

For the CGH arrays, 16-bit 1,024 � 1,024 pixel

DAPI Cy3 and Cy5 images were acquired using a

custom-built CCD camera system (Pinkel et al.,

1998). For the CGH images, we used UCSF SPOT

software (Jain et al., 2002) to segment the spots

automatically on the basis of the DAPI images, to

perform local background corrections, and to calcu-

late a variety of measurement parameters, includ-

ing log2 ratios of the total integrated Cy3 and Cy5

intensities for each spot. We used a second custom

program, UCSF SPROC, to associate clone identi-

ties and a mapping information file with each spot

so that the data could be plotted relative to the

position of the BACs on the August 2001 freeze of

the draft human genome sequence (University of

California, Santa Cruz database).

The expression arrays were scanned using an

Axon Genepix 4000B fluorescence reader and

Genepix image acquisition software (Axon, Foster

City, CA) for both Cy3 and Cy5 images. An image

analysis algorithm in GEMTools software (Incyte

Genomics) was used to quantify signal and back-

ground intensities for each target element.

Analysis and Statistics

For the array CGH data, we used SPROC soft-

ware in order to filter the data by rejecting data

based on a number of criteria, including low refer-

ence/DAPI signal intensity and low correlation of

the Cy3 and Cy5 intensities with a spot. The

SPROC output consists of averaged ratios of the

triplicate spots for each clone, standard deviations

of the triplicates, and plotting position for each

clone on the array, as well as other clone informa-

tion stored in the database, such as STS content.

The data files were edited to remove ratios on

clones for which only one of the triplicates

remained after SPROC analysis and/or the stand-

ard deviation of the log2 ratios of the triplicates was

greater than 0.2.

We used GEMTools software in order to analyze

the image output of the expression arrays. Any spot

that had a signal intensity greater than 2.5 above

absolute background was considered present. As

described above, each sample was analyzed in

duplicate against the reference pool. The dupli-

cates were labeled with the fluorescent dyes in

reverse order. The average signal was used for fur-

ther analysis. GEMTools software also was used to

filter the data by rejecting outliers and data points

that were disqualified statistically. The datasets

were normalized by taking the average for each sig-

nal (Cy3 or Cy5) and by calculating a balance coef-

ficient. Each signal was then multiplied by this bal-

ance coefficient to obtain a normalized signal inten-

sity value. A threefold difference in mRNA ex-

pression was considered statistically significant.

RESULTS

High-molecular-mass genomic DNA was iso-

lated from 25 human pancreatic cancer cell lines

(Table 1). This panel of cell lines was isolated from

either primary tumors or lymph node or liver meta-

stases as indicated. In addition, we analyzed DNA

from the COLO 357 cell line and from its deriva-

tive cell lines L3.3, L3.6sl, and L3.6pl. L3.3 cells

were isolated by serial passage of a fast-growing

variant of COLO 357 cells through mice to select

39DNA ALTERATION AND mRNA EXPRESSION IN PANCREATIC CANCER CELLS

for cells with increased capacity for spleen-to-liver

metastasis (Vezeridis et al., 1990; Vezeridis et al.,

1992). L3.6sl and L3.6pl cells were subsequently

isolated by sequential parallel passage of L3.3 cells

through mice and selection for cells with additional

increased capacity for either spleen-to-liver

(L3.3?L3.4sl?L3.5sl?L3.6sl) or pancreas-to-

liver (L3.3?L3.4pl?L3.5pl?L3.6pl) metastasis

(Bruns et al., 1999).

Fluorescently labeled genomic DNA probes

were hybridized to microarrays comprising a set of

BACs containing human genomic DNA. This array

(HumArray 2.0) comprised 2,464 BACs selected to

encompass the majority of the human genome to a

resolution of about �1.4 Mbp (Snijders et al., 2001,

2004).

The array CGH profiles of the various pancreatic

cancer cell lines displayed a large number of copy

number alterations, as demonstrated in the repre-

sentative analyses of DNA from Panc-4.21 and

SU86.86 cells shown in Figure 1. Panc-4.21 cells

were derived from a primary tumor, and genomic

DNA was isolated from low-passage-number cells

(<20). SU86.86 was derived from a liver metastasis.

In some cases, gain and loss appeared to be focal in

nature, encompassing small regions of a chromo-

some. For example, Panc-4.21 exhibited a homozy-

gous deletion on chromosome 9 (Fig. 1 and Table 2)

encompassing the region of CDKN2A commonly lost

in human pancreatic adenocarcinoma. In addition,

SU86.86 showed three focal amplifications on chro-

mosome 19 (Fig. 1 and Table 3).

Array CGH ratio profiles of cancer cells often

indicate that the vast majority of the cancer cell

genome is composed of approximately the same

DNA copy number as normal cells. Thus, data can

be normalized such that the median log2 ratio is set

to 0, and DNA copy number gain and loss are

defined relative to this value. By contrast, analysis

of the pancreatic cancer cell lines in the present

study indicated that their genome was bimodal in

copy number, split about evenly between two rela-

tively closely spaced ratio values, with additional

small regions of significantly higher or lower ratio.

Such observations make it difficult to assess a

meaningful median DNA copy number for the can-

cer cell genome (i.e., whether the cells under anal-

ysis were largely diploid, triploid, tetraploid, etc).

The small ratio difference between the two modes

indicates that these cell lines were likely to be

polyploid. This bimodal ratio structure makes it

difficult to define a biologically reasonable ‘‘nor-

mal’’ ratio from which to measure copy number

gain or loss. For example, if the lower of the two

most common ratios were normalized, then half the

genome would be considered to show gain,

whereas if the upper ratio were normalized, the

other half of the genome would be classified as lost.

Moreover, even if fluorescence in situ hybridiza-

tion (FISH) were employed to determine the

actual copy number of the various segments of

DNA, it would be difficult to conclude that a given

cell was either largely diploid with a large number

of gains or largely triploid with a large number of

losses, as illustrated in Figure 1. Thus, in analyzing

our results, we normalized the array CGH data to

the median ratio, which typically falls between the

upper and lower modal values, and we therefore

considered loci as gained if the log2 ratio (cancer

cell:normal cell DNA) was � 0.5 and as lost if the

log2 ratio (cancer cell:normal cell DNA) was

� �0.5. These boundaries fall outside the upper

and lower copy number levels for the various cell

lines.

As noted above, pancreatic adenocarcinoma dis-

plays a number of signature genetic alterations,

and so we assessed copy number alterations for all

these genes. Table 4 summarizes our findings for

each cell line. Amplification of somatically mutated

KRAS2 and/or ERBB2 is reported to be an early

event (Hruban et al., 2000). Consistent with

previous observations, we detected an increased

copy number at the KRAS2 locus (12p12.1) in 8 of

TABLE 1. Cell Lines

Cell line Isolated from Reference

BxPC-3 primary site Tan et al., 1986Capan-2 primary site Dahiya et al., 1993MIAPaCa-2 primary site Yunis et al., 1997Panc-1 primary site Lieber et al., 1975Panc-2.03 primary site Jaffee et al., 1998Panc-2.13 primary site Jaffee et al., 1998Panc-3.27 primary site Jaffee et al., 1998Panc-4.21 primary site Jaffee et al., 1998Panc-5.04 primary site Jaffee et al., 1998Panc-6.03 primary site Jaffee et al., 1998Panc-8.13 primary site Jaffee et al., 1998Panc-10.05 primary site Jaffee et al., 1998PL45 primary site Jaffee et al., 1998HPAC primary site Norman et al., 1994MPanc-96 primary site Peiper et al., 1997NOR-PI metastatic site Sato et al., 2000SW1990 metastatic site Kyriazis et al., 1983SU 86.86 metastatic site Drucker et al., 1988CFPAC-1 metastatic site Schoumacher et al., 1990HPAF II metastatic site Metzgar et al., 1982Hs766T metastatic site Owens et al., 1976COLO 357 metastatic site Morgan et al., 1980L3.3 metastatic site Bruns et al., 1999L3.6 sl metastatic site Bruns et al., 1999L3.6 pl metastatic site Bruns et al., 1999

40 GYSIN ETAL.

25 cell lines. This observation is consistent with

elevated expression of mutationally activated

KRAS2 being selected for in other human cancers

(Grunewald et al., 1989). We also observed fre-

quent gain of ERBB2 (17q12) in 7 of 23 of cell

lines, 2 of which also displayed an increased copy

number of the KRAS2 gene.

Inactivation of the tumor suppressor CDKN2A(9p21), which encodes the cyclin-dependent kinase

4 inhibitor p16INK4A, is one of the most frequent

alterations in tumor-suppressor genes, occurring in

approximately 90% of all pancreatic cancers

(Wilentz et al., 1998b). Consistent with this obser-

vation, we detected loss of CDKN2A in 10 of 25 cell

lines. Some of these losses reflected homozygous

deletion (log2 ratio of cancer cell:normal cell DNA

was approximately �2) of both CDKN2A alleles (3

of 10), and others reflected heterozygous deletions

(7 of 10). These data are consistent with the hypoth-

esis that CDKN2A expression can be silenced by

both genetic and epigenetic mechanisms such as

DNA methylation (Geradts et al., 2000). Finally,

losses of the tumor-suppressor genes TP53(17p31.1) andDPC4/SMAD4 (18q21) are reported to

occur later in pancreatic cancer progression (Hru-

ban et al., 2000). Interestingly, we detected reduced

copy numbers in the region of TP53 in only 2 of 24

pancreatic cancer cell lines. In contrast to this find-

ing of a modest rate of TP53 loss, we detected a very

high rate of loss of the DPC4/SMAD4 locus in 20 of

25 cell lines. Again, some of these appeared to be

homozygous deletions (6 of 20), and others were

heterozygous deletions (14 of 20).

Recurrent Genomic Alterations in

Pancreatic Cancer Cell Lines

Next, we turned our attention to the most

frequent additional CNAs observed in the 25

pancreatic cancer cell lines, as illustrated in the

genome frequency plot (Fig. 2). As outlined above,

gain and loss were defined as alterations in which

the log2 ratio was � 0.5 (gain) or � �0.5 (loss). We

detected in at least 30% of the cell lines copy num-

ber gains on regions of chromosome arms 3q, 5p,

7p, 8q, 10p, 11q, 12p, 17q, and 20q. In certain

cases, these copy number gains corresponded to

one or a small number of BACs, suggesting a focal

or relatively localized increase in gene copy num-

ber. In addition to copy number gains, we detected

recurrent DNA copy number losses on chromo-

some arms 3p, 4q, 6pq, 8p, 9p, 13pq, 15q, 16q, 17p,

18q, 21p, Xp, and Xq.

We then focused on recurrent regions of higher

gene copy number gain or loss. We defined a recur-

rent higher-level gain of copy number as a region in

which at least two cell lines showed a log2 ratio � 1

(i.e., �2-fold change in copy number). Similarly, we

defined recurrent heterozygous or homozygous dele-

tions as having occurred when a genomic region had

at least two cell lines that exhibited a log2 ratio of ��1 (heterozygous) or � �2.0 (homozygous; Tables 2

and 3). When two or more cell lines displayed an

overlapping copy number abnormality at the same

genomic locus, we have indicated the region (in kilo-

base pairs) where this occurred.

The most highly recurrent abnormalities were

detected around 8q24, where 13 of 25 cell lines

Figure 1. CGH profiles of cell lines Panc-4.21(primary) and SU86.86 (metastatic). For Panc-4.21and SU 86.86, profiles of chromosomes 9 (homozy-gous deletion) and 19 (3 focal amplifications),respectively, are shown. For the whole-genomeprofiles, the X axis designates chromosomes 1–22and the X chromosome. The coordinates alongchromosomes 9 and 19 are shown in megabasepairs. The Y axes represent the log2 of the meanraw ratios.


TABLE 2. Recurrent Deletions

FISHa BAC clonesb Distancec (kbp) log2 > �1d log2 > �0.5e Candidate gene

3p21–3p14 CTD-2199G5–RP1l-154H23

53680–71654 SW1990 13/24 FHIT, fragile histidine triadBxPC-3COLO 357L3.6slMIAPaCa-2HPAF II

4q34–4q35 RP1l -244K2–RP1l-13O14

183090–185921 Panc-8.13 4/24 ?Hs766T

6p24 RP1l-168G4 6939–7074 COLO 357 8/24 ?SU86.86

6q26 RP1l-43B19 160895–160990 PL45Capan-2

5/24 LPA, lipoprotein

8p23.2–8p22 RP1l-121F7–RP1l-287P18

3284–7328 Panc-1 13/23 CSMDI, CUB, and sushimultiple domains protein 1Panc-2.13

Panc-3.27Panc-6.03Panc-8.13Panc-10.05CFPAC-1Capan-2

9p21 CTB-65D18–RP1l-55P9

24208–25574 BxPC-3f 10/25 CDKN2A, p16INK4A

MIAPaCa-2

Panc-4.21

MPanc-96Panc-1

9q21 RP1l-57N18 73439–73612 Panc-4.21 4/25 ?SW1990

9q32 RP1l-16A3 112785–112946 BxPC-3 1/25 TNFSF15, tumor necrosisfamily member 15

10q22.1 RP1l-50K4 72570–72726 BxPC-3 2/24 CDH23, cadherin related 2311p15.1–11p14 RP1l-13O19–

R1l-62G1819261–19772 Capan-2 3/25 NAV2, helicase

13q31–13q32 RP1l-86C3–RP1l-165N12

87949–90880 Panc-2.03 9/21 GPC5, glypican 5HPAF II

16q23 RPl1-284G2–RPl1-61L1

78534–78567 L.3.6sl 11/23 WWOX, WW domain cont.oxidoreductase isoform 2L.3.6pl

HPAF II

18q21.1 DPC4 46809–46858 CFPAC-1 20/25 DPC4, SMAD4BxPC-3

Panc-4.21

Panc-5.04

Panc-6.03

SW1990SU86.86MPanc-96Hs766T

21q22.1–21q22.2 RP1l-8P19–RP11-66C14

34528–38716 PL45 4/25 CLDN14, claudin 14SW1990HPAC

Xp22.3 GS-118K5–RP4-677NI

6599–8011 BxPC-3 10/12 ARSCI, arylsulfatase CHPACPanc-2.13Panc-4.21

Xp27 CTD-2082H4 146288–146778 HPAC 7/12 FMR2, fragile X mentalrelardation 2Panc-3.27

Panc-4.21

aOverlapping recurrent region given in FISH coordinates.bFirst and last BAC clones at the borders of the overlapping recurrent region.cOverlapping recurrent region given in kilobase pairs according to the location of the first and last BAC clones (July 2003 freeze, UCSC).dCell lines having deletions in the overlapping recurrent region.eMaximal number of cell lines showing losses in the overlapping recurrent region.fCell lines in boldface indicates a homozygous deletion.

42 GYSIN ETAL.

exhibited copy number gain. The candidate gene

in this region is c-MYC, and classical amplification

of this gene has been reported in pancreatic and

other types of human cancer (Armengol et al.,

2000; Nagy et al., 2001; Schleger et al., 2002). Two

regions of frequently altered copy number also

were found on chromosome 11. Eleven of 25 cell

lines showed gains of cyclin D1 (CCND1), at

11q13, of which four showed an increase in CCND1copy number that was greater than twofold. COLO

357 and its derivatives and eight additional cell

lines displayed gains at 11q22 in a region that

includes the gene BIRC3. Four cell lines showed

higher copy number gains at the KRAS2 locus.

Regions of higher copy number gain not previously

reported in pancreatic cancer were detected on

chromosome 5. Three cell lines had copy number

gains between 5p14.3 and 5p15.1. COLO 357 and

one of its derivatives showed copy number gains

between 5q33 and 5q34. Each region was gained in

an additional five cell lines. Two other regions of

higher gain were detected on 10p14 (9 of 25 cell

lines) and 17q21.3 (10 of 25 cell lines). The largest

magnitude of increase in gene copy number was an

11-fold increase, which occurred in the locus

encompassing AKT2 (19q13.1–19q13.2) in Panc-1

cells and in the locus including TRRAP (7q21.1) in

MPanc-96 cells. Given the magnitude of the

TABLE 3. Recurrent High-Level Gains

FISHa BAC clonesb Distance (kbp)c log2 > 1d log2 > 0.5e Candidate gene

5p14.3–5p15.1 RP11-88L18 17465–17646 L3.3 8/25 BASP1, brain acidsoluble proteinHPAC

Hs766T5q33–5q34 RP11-4J6 158183–158321 COLO 357 5/23 EBF, early b-cell factor

L3.6 sl6p21.2–6p21.1 CTD-2130B14–

RP11-91H1431649–43984 SW1990 5/25 TNF, tumor necrosis

factorSU86.868p23.1–8p22 RP11-24l14–

RP11-254E1010209–11165 COLO 357 2/25 MSRA, methionine

sulfoxide reductase APanc-6.038q24.1–8q24.2 RP11-145G10–

RP11-237F24128500–128710 CFPAC-1 13/25 MYC

Panc-2.13Panc-6.03Panc-8.13

10p14 RP11-35I11 8923–9011 COLO 357 9/25 ?Panc-6.03

11q13 CTD-2192B11–RP11-120P20

69229–70130 COLO 357 11/25 CCND1, cyclin D1L3.3L3.6plPanc-6.03

11q22 RP11-134G19–RP11-817J15

101595–102128 COLO 357 9/23 BIRC3, baculoviral IAPrepeat containing 3L3.3

L3.6slL3.6pl

11q23.1–11q24 CTD-2222B22–RP11-35M6

116613–122938 COLO 357 5/25 TRIM29, tripartite motifprotein 29L3.3

Hs766T12p12.1–12p11.2 RP11-64J22–

RP11-78F1625789–30761 L3.6sl 8/25 KRAS2

L3.6plSU86.86HPAF II

17q21.3 RP5-1071I14–RP5-32P19

47929–48415 Panc-10.05 10/25 LOC81558PL45

19q13.1–19q13.2 RP11-92J4–RP11-133A7

41164–46089 SU86.86 4/25 AKT2Panc-1

19q13.3–19q13.4 RP11-236B14–RP11-12C9

55230–62624 SU86.86 2/20 VRK2, ser-/thr proteinkinasePanc-2.13

20q11.2–20qtel RP11-134I8–RP1-81F12

31323–63742 Hs766T 13/25 NCOA3, nuclear receptorco-activator 3, isoform bPanc-1

aOverlapping recurrent region given in FISH coordinates.bFirst and last BAC clones at the borders of the overlapping recurrent region.cOverlapping recurrent region given in kilobase pairs according to the location of the first and last BAC clones (July 2003 freeze, UCSC).dCell lines having high-level gains in the overlapping recurrent region.eMaximal number of cell lines showing gains in the overlapping recurrent region.


change in copy number, these alterations may

reflect classical gene amplification. Although AKT2copy number also was gained in SU86.86 cells,

TRRAP amplification was not observed in any

other cell line. Furthermore, we also confirmed

copy number gain in 13 of 25 cell lines on chromo-

some arm 20q that had been reported by others

previously (Heidenblad et al., 2002; Mahlamaki

et al., 2002).

Recurrent loss of copy number was detected

between chromosome bands 3p21 and 3p14 in

13 of 24 cell lines tested. The plausible candidate

gene in this region is FHIT, which has been impli-

cated as a tumor suppressor in other cancers

(Pekarsky et al., 2002). Eight of 25 cell lines

showed heterozygous deletions between 8p23.2

and 8p22. Although the significance of this is

unclear, 7 of these 8 cell lines were derived from

primary tumors. Finally, 9 of 25 cell lines sustained

deletions in the region encompassing DPC4, on

chromosome 18. In addition, we noted apparent

homozygous deletions of regions on chromosomes

9, 10, 11, 16, and 18 and the X chromosome. The

cell line BxPC-3 was affected in five locations that

had already been reported (Table 2). Novel find-

ings were the homozygous deletions on chromo-

TABLE 4. Loci Commonly Altered in Pancreatic Adenocarcinoma

LociFISH and

kbp position Frequencya Cell lines

KRAS2 12p12.1 (25,249 kbp) gains in 8/25 L3.6 sl L3.6 plCFPAC-1 Panc-3.27SU 86.86 MIAPaCa-2Panc-1 HPAF II

ERBB2 17q12 (38,260 kbp) gains in 7/23 L3.6 pl Panc-10.05CFPAC-1 PL45Panc-2.03 Panc-1SW1990

P16INK4A 9p21 (22,823 kbp) losses in 10/25 BxPC-3 MPanc-96Panc-2.13 Capan-2SU 86.86 MIAPaCa-2Panc-6.03 Panc-1Panc-4.21 HPAF II

TP53 17p13.1 (7,802 kbp) losses in 2/24 PL45Capan-2

DPC4 18q21 (46,839 kbp) losses in 20/25 COLO 357 Panc-2.03L3.3 Panc-2.13L3.6 sl Panc-3.27L3.6 pl Panc-4.21CFPAC-1 Panc-5.04BxPC-3 Panc-8.13Panc-10.05 Panc-6.03PL45 Hs766TSW1990 Capan-2SU 86.86 Mpanc-96

aA cutoff of 6 0.5 (log2) was chosen (see text).

Figure 2. Frequency plot of the pancreatic cancercell line genome showing the frequency of gain andloss in the 25 human pancreatic cancer cell lines. TheX axis designates the coordinate along the genome(chromosome numbers) and the Y axis indicates fre-quencies (%). The value 6 0.5 (log2) was chosen asthe cutoff. The X chromosome showed frequent gainor loss only in the female cell lines (12).

44 GYSIN ETAL.

some 11 in Capan-2 cells and on chromosome 16 in

HPAF II cells. The latter is potentially interesting

because HPAF II cells were isolated from a meta-

stasis, and the same region also was lost specifically

in L3.6sl and L3.6pl, two derivatives of COLO 357

that were selected to have increased invasive/

metastatic potential (see below).

Copy Number Alterations in Metastatic

Derivatives of COLO 357 Cells

To assess whether continued genomic instability

may contribute to the acquisition of greater inva-

sive/metastatic potential, we conducted array CGH

analysis of COLO 357 cells and their derivative

cell lines L3.3, L3.6sl, and L3.6pl. These cells

were selected for an enhanced capacity for invasion

and metastasis by serial passage of parental COLO

357 cells through nude mice (Vezeridis et al., 1990;

Vezeridis et al., 1992; Bruns et al., 1999). Array

CGH analysis of these cells revealed that their

acquisition of enhanced metastatic capacity was

accompanied by only modest alteration in gene

copy number. The array CGH patterns of all four

cell lines (Fig. 3) indicated them to be very closely

related to one another. However, there were a

number of interesting differences in gene copy

number detected in these cells. Major differences

were observed on chromosomes 11, 12, 16, 19, and

20, and more subtle differences could be found on

chromosomes 3, 7, 8, 10, 13, 21, and 22. We

hypothesized that these regions might contain

interesting candidate genes involved in the proc-

esses of invasion and metastasis. Some of the dif-

ferences that we observed in the array CGH profile

between COLO 357, L3.3, and the more meta-

static variants L3.6sl and L3.6pl were detected on

chromosome 11. The genomic regions and the

genes within these intervals are listed in Table 5.

We also noted interesting focal changes in a

region on chromosome segment 12p12.1 that

encompasses the KRAS2 gene (Fig. 4 and Table 5).

The region contains three peaks that exhibited

copy number gain in the L3.6sl and L3.6pl cells

relative to the copy number in the COLO 357 and

L3.3 cells. The first region encompasses not only

the KRAS2 gene, but also neighboring genes such

as Sarcospan (KRAS oncogene associated gene), a

basic helix–loop–helix domain containing protein

and ITPR2 (inositol-1,4,5-triphosphate (IP3) recep-

tor). These genes have been reported to be coam-

plified with KRAS2 in other human malignancies

(Heighway et al., 1996). There is also a second

region of copy number gain approximately 400 kbp

distant from the KRAS2 gene in the region of

importin 8 and a hypothetical open-reading frame,

KIAA1873. Furthermore, the array CGH data dem-

onstrated that cell lines L3.6sl and L3.6pl dis-

played reduced copy number in the vicinity of the

telomere of the q arm of chromosome 16 (Fig. 4

and Table 5). This region encompasses the WWOXgene (WW domain containing oxidoreductase) and

was lost in approximately 50% of all pancreatic

cancer cell lines analyzed in the present study.

The protein encoded by the WWOX gene is

reported to have a WW domain and a domain

related to oxidoreductase, but its precise biochemi-

cal function and putative role as a tumor-suppres-

sor gene remain unclear (Bednarek et al., 2001;

Paige et al., 2001; Ishii et al., 2003; Ludes-Meyers

et al., 2003; Watanabe et al., 2003; Kuroki et al.,

2004; Park et al., 2004; Watson et al., 2004).

Mutation of KRAS2 in L3.6sl and L3.6pl Cell Lines

We found it provocative that the derivative cell

lines L3.6sl and L3.6pl appeared to display focal

increases in gene copy number around the KRAS2gene. Published reports have suggested that

COLO 357 cells express either mutationally active

Figure 3. CGH profiles of the human pancreatic cancer cell linesCOLO 357 and L3.3 and derivatives L3.6sl and L3.6pl. The X axis desig-nates the chromosome numbers and the Y axes represent the log2 ofthe mean raw ratios (see Fig. 1).


KRAS or BRAF (Kalthoff et al., 1993; Ellenrieder

et al., 2001; Calhoun et al., 2003; Sipos et al., 2003).

Consequently, we sequenced both exon 1 of the

KRAS2 gene and exon 15 of the BRAF gene from

COLO 357, L3.3, L3.6pl, and L3.6sl cells. In con-

trast to the findings in the published reports, we

found that neither the COLO 357 nor the L3.3

cells displayed point mutations in KRAS2, whereasthe L3.6sl and L3.6pl cell lines both had a point

mutation in codon 12 (GGT?GAT), encoding a

mutationally activated (G12D) KRAS2. None of

the cell lines displayed mutations in exon 15 of

BRAF. These data suggest that the serial passage

of COLO 357 cells through mice to derive more

invasive/metastatic variants led to the selection of

cells that express mutationally activated KRAS2.This hypothesis is consistent with the observation

that the L3.6sl and L3.6pl cell lines display ele-

vated levels of phosphorylated ERK1/2 and AKT

compared to the parental COLO 357 and L3.3 cell

lines (data not shown).

Alterations in mRNA Expression Accompanying

Acquisition of Increased Metastatic Potential

Array CGH analysis suggested that the increased

metastatic potential of L3.6sl and L3.6pl cells was

accompanied by modest alterations in gene copy

number. Hence, to complement the analysis of

genomic DNA, we assessed alterations in mRNA

expression patterns that accompanied the acquisi-

tion of increased metastatic potential. We com-

pared the expression profiles of 7,437 mRNAs in

COLO 357, L3.3, L3.6sl, and L3.6pl cell lines by

using cDNA microarrays as described in the Mate-

rials and Methods section. Table 6 lists those

mRNAs that displayed differential expression

(�3-fold) when comparing L3.6pl to COLO 357

cells. Remarkably few mRNAs displayed a greater

than threefold change in expression. Of the

mRNAs assessed, expression was up-regulated in

18 and down-regulated in 24 in L3.6pl cells com-

pared to COLO 357 cells.

Among the mRNAs that were up-regulated in

the L3.6pl cells were those encoding a6-integrin,vascular endothelial growth factor C (VEGF-C),

and caveolin 1. These proteins may facilitate can-

cer cell metastasis by promoting cell migration and

invasion, by promoting angiogenesis, or by influ-

encing a variety of cell signaling pathways (Cross

et al., 2003; Guo and Giancotti, 2004; Patlolla

et al., 2004). It is also interesting that some of the

genes, such as a6-integrin, caveolin-1, dual-specif-icity phosphatase 6, and glucosaminyl transferase

3, are found to be RAS-regulated through the

RAF?MEK?ERK pathway, as their expression

was altered by treatment of cells with a pharmaco-

logic inhibitor of MEK (U0126, data not shown).

TABLE 5. Relative Changes in the CGH Profiles of COLO 357 and L 3.6 pl and sl

FISH BAC clone CGH position (kbp)a Candidate gene symbol Candidate gene

11q14.1 RPl1-7H7 78025 GAB2 Grb2 associated-binding protein11q14 RPl1-34L12 to

RPl1-119M2382259–85395 RAB30 ras family protein

11q14–11q22 RPl1-29H11 toRPl1-258CI

86775–99843 MGC5306 hypothetical proteinKIAA0092 hypothetical proteinMTMR2 myotubularin-related

protein 211q22.2 CTD-2039C11 101746 YAP; BIRC3; BIRC2 Yes associated-protein,

65 kDa; baculoviral 1AP repeatcontaining 3 and 2;matrixtalloproteinases1, 3, 7, 8, 10, 12, 13, 27

MMP1, 3, 7, 8, 10, 12, 13, 27

11q23–11q24 RPl1-8K10 toRPl1-35M6

119095–122910 DDX6; UBE4A DEAD box polypeptide 6;ubiquitin conjugation factor E4

12p12.1 GS-490C21 25249 KRAS2 ras family, oncogeneRPl1-53C3 26255 SSPN; BHLH; lTPR2 sarcospan (KRAS associated gene);

basic helix-loop-helix containingprotein; inositol trisphosphatereceptor 2

12p11.2 RPl1-78F16 30741 IPO8; KIAA1873 importin 8; hypothetical proteinRPl1-56J24 31959 BICD1 cytoskelcton like bicaudal D

protein homolog16q23 RPl1-284G2 78534 WWOX; v-maf WW containing oxidoreductase;

oncogene

aIndicates start-mapping position of the first BAC clone according to the July 2003 UCSC databse.

46 GYSIN ETAL.

Among the mRNAs that were down-regulated

were those encoding YAP, MMP7, BIRC2, and

BIRC3. Some of these genes are in regions that

displayed reduced copy number as assessed by

array CGH. However, the role of these genes in

the acquisition of metastatic potential remains to

be further elucidated.

DISCUSSION

Alterations in gene expression, in part influ-

enced by genomic instability, most likely contrib-

ute to the phenotypic variation that occurs in the

cells in a tumor. Such alterations in gene expres-

sion can promote the optimal proliferation and sur-

vival of the cancer cell in its primary environment

by promoting the cell-division cycle, by inhibiting

apoptosis, or by promoting angiogenesis and inva-

sion (Fidler, 2003). Moreover, alterations in gene

expression also may promote the generation of

cells with an enhanced capacity for invasion and

metastasis.

In the present study, we used high-resolution

array CGH to analyze a large set of human pancre-

atic cancer cell lines, many of which are used rou-

tinely for cancer research. This analysis confirmed

the presence of many of the signature alterations

observed previously by others in pancreas cancer

cell lines and in primary pancreatic cancer speci-

mens. Moreover, these data confirmed and

extended previous genomic analysis of pancreatic

cancer cell lines and primary specimens published

by others (Fukushige et al., 1997; Mahlamaki

et al., 1997, 2002, 2004; Aguirre et al., 2004; Hei-

denblad et al., 2004; Holzmann et al., 2004).

Indeed, Mahlamaki et al. (2004) and Aguirre et al.

(2004) both conducted high-resolution array CGH

and mRNA expression analysis using a common

cDNA-based microarray. This approach facilitates

a comparison of the effects of alterations in gene

copy number to the effects on mRNA expression.

Given that pancreatic cancer cells exhibit a large

number of copy number abnormalities, it remains

unclear what role a single gene in any particular

CNA might play in the initiation and/or progres-

sion of pancreatic cancer. Consequently, it would

be of considerable interest to monitor the appear-

ance of copy number alterations during the earliest

phases (PanIN1-3) of pancreatic cancer develop-

ment. Moreover, it would also be useful to obtain

additional primary pancreas cancer specimens for

genetic analysis. However, the dense desmoplastic

infiltration of non cancer cells into pancreatic

tumors renders such an analysis fraught with tech-

nical difficulties. However, recent comparisons

between cancer cell lines and primary pancreatic

cancer specimens suggest that many, but not all,

CNAs detected in cell lines can also be found in

primary tumors (Aguirre et al., 2004). The recent

development of laser capture microdissection tech-

niques combined with linear amplification strat-

egies to generate CGH probes from small amounts

of DNA will likely facilitate more extensive analy-

sis of primary cancer specimens. Moreover, recent

developments in modeling pancreatic cancer in the

mouse may assist in the identification of genes

involved in the progression of this disease (Aguirre

et al., 2003; Hingorani et al., 2003). It is possible

that these models may be used for identifying can-

didate pancreas cancer progression genes that can

then be confirmed using primary human speci-

mens. However, it should be noted that not all

genetic abnormalities observed in human pancreas

cancer have been recapitulated in the mouse

model of this disease (Aguirre et al., 2003; Hingor-

ani et al., 2003).

Figure 4. Differences in CGH profiles of COLO 357 (dark blue),L3.3 (red), L3.6sl (yellow), and L3.6pl (light blue) on chromosomes 12and 16. The X axes show the coordinates of the individual BAC clones(in megabase pairs); the Y axes represent the log2 of the mean rawratios. The centromere position is also indicated, and the arrows indi-cate peaks of amplification (chromosome 12) and of deletion (chromo-some 16).


One of the most lethal features of pancreatic

cancer is its apparent capacity for early invasion

and metastasis to the liver and other organs. We

have used COLO 357 and its more invasive/meta-

static derivatives (L3.6sl and L3.6pl) to explore

pancreas cancer cell metastasis. Array CGH analy-

sis of this panel of cells revealed that the cells were

closely related to one another but displayed focal

alterations in copy number. It remains unclear

what contribution such focal alterations in copy

number might play in influencing the expression

of genes involved in invasion and metastasis.

Although genomic instability is a feature of many

metastatic tumors, cancer cells with only modest

alterations in genomic integrity can be highly

metastatic (Clark et al., 2000). Furthermore, in

breast cancer, metastatic cells may disseminate

early from the primary site and acquire more

genetic alterations once they reach the target organ

(Schmidt-Kittler et al., 2003). Finally, in a mouse

model of MYC-induced lymphoid malignancy, loss

of TP53 promoted tumor cell invasion accompa-

TABLE 6. Genes Differentially Expressed between L 3.6 Pl and COLO 357

Accession# Gene name FISH Fold change L.3.3a L.3.3slb

Genes at least 3-fold up-regulated in L 3.6 pl relative to COLO 357X59512 integrin, alpha 6 2p14 3.6 þ �NM_018894 EGF-containing fibulin like ECM protein 1 2p16 3.9 � þAL553735 interleukin 1 receptor-llike 1 2q12 3.5 þ �BG491883 minichromosome maintenance deficient 2 3q21 3.1 � �M13699 ceruloplasmin (ferroxidase) 3q23 3.1 � �NM_005429 vascular endothelial growth factor C 4q34 5.5 � þB1760179 claudin 4 7q11 3.2 � �NM_001753 caveolin l 7q31 3.3 � �S76474 neurotrophic tyrosine kinase, receptor, type 2 9q22 3.8 � �A1421214 prostaglandin E synthase 9q34 5.9 � þBC005127 adipose differentiation–related protein 9p22 12.2 � �NM_001946 dual specificity phosphatase 6 12q22 3.4 þ þNM_004751 glucosaminyl transferase 3, mucin type 15q21 3.6 þ þB1752945 cathepsin H 15q24 3.5 � þBF130769 metallothionein IX 16q13 3.8 � þM14764 nerve growth factor receptor (TNFR family) 17q21 8.2 � þBF979102 lectin, galactoside binding (galectin 1) 22q13 3.8 þ �M69226 monoamine oxidase A Xp11 3.8 þ �Genes at least 3-fold down-regulated in L 3.6 pl relative to COLO 357B1754211 ephrin A1 1q21 4.5 � �AL137583 xenotropic and polytropic retrovirus receptor 1q25 3.3 � �AV652811 complement component 4-binding protein, beta 1q32 3.9 � þBE877502 putative lymphocyte G0/G1 switch gene 1q32 4.7 � þAV704811 ras homolog gene family, member B 2pter 4.0 � þBG761337 carbamoyl-phosphate synthetase 1, mitochondr. 2q35 7.6 þ �AU141656 sialyltransferase 1 3q27 4.0 � þA1148603 S100 calcium-binding protein P 4p16 3.9 � �BG620346 glycoprotein hormones, alpha polypeptide 6q12 3.2 þ �BC015061 RAB32, member ras family 6q24 3.2 � �AF036268 SH3-domain GRB2-like 2 9p22 4.7 � þA1937230 calcitonin-related polypeptide, beta 11p15 3.3 þ þAA433865 Yes-associated protein 1, 65 kDa 11q13 3.2 � �NM_002423 matrix metalloproteinase 7 (matrilysin, uterine) 11q21 3.7 � þA1581499 baculoviral IAP repeat-containing 3 11q22 4.6 � �U37547 baculoviral IAP repeat-containing 2 11q22 5.5 � �AW874086 epithelial V-like antigen 1 11q24 3.1 � �BG546606 microfibril-associated glycoprotein-2 12p13 5.3 � þJ04970 carboxypeptidase M 12q15 6.5 þ �B1711468 integral membrane protein 2B 13q14 3.2 � þAL574127 mesothelin 16p13 3.4 þ þNM_006919 serine (or cysteine) protease inhibitor, clade B 18q21 3.4 � �NM_003661 apolipoprotein L 22q13 4.0 � þBF792356 melanoma antigen, family A, 6 Xq28 5.8 � þaDifferential regulation between L3.6pl and L3.3.bDifferential regulation between L3.6sl and COLO 357.

48 GYSIN ETAL.

nied by genomic instability. However, in the same

model, loss of ARF (instead of TP53) also pro-

moted tumor cell invasion, but the invading cells

did not display widespread genomic instability

(Schmitt et al., 1999).

Perhaps surprisingly, we found that the L3.6sl

and L3.6pl cell lines both possessed an activated

KRAS2 gene and displayed elevated levels of

pERK1/2 and pAKT compared to the parental

COLO 357 and L3.3 cell lines (not shown). That

the L3.3 cell line, the progenitor of both cell lines,

did not possess an activated KRAS2 gene suggests

that there may have been a separate selection for

the presence of activated KRAS2 by passage of the

cells through nude mice. Although it is unclear

when cells with activated KRAS2 emerged during

the selection process, it should be possible to ascer-

tain the timing of this event by analysis of KRAS2in the intermediate cell lines L3.4sl/pl and L3.5sl/

pl cells (Vezeridis et al., 1992). Finally, it remains

to be determined whether activated KRAS2 con-

tributes to pancreas cancer cell metastasis.

To complement the analysis of genomic DNA in

COLO 357 and its derivatives, we also conducted

an analysis of mRNA expression profiles and iden-

tified genes with altered expression in the more

metastatic derivatives. Several of these genes are

of direct interest, but perhaps the most provocative

is a6-integrin. Giancotti and colleagues previously

demonstrated that a6-integrin plays a role in can-

cer cell motility, invasion, and metastasis (Guo and

Giancotti, 2004). Interestingly, we previously

showed that a6-integrin is regulated by the RAS-

activated RAF?MEK?ERK pathway (Woods

et al., 2001). Hence, activated KRAS2 may contrib-

ute to pancreas cancer cell invasion and metastasis

through the regulated expression of a6-integrin, ahypothesis that is currently under investigation.

ACKNOWLEDGMENTS

The authors thank all the members of the

McMahon laboratory for advice, suggestions, and

constructive criticism of this work. We are espe-

cially grateful to Dr. Donna Albertson, Dr. Ajay

Jain, and Dr. Dan Pinkel for advice on the use of

array CGH and data analysis and for critical

appraisal of this manuscript. We also thank Dr.

Margaret Tempero, Dr. Joe Gray, and Dr. Graeme

Hodgson for advice, reagents, and a review of the

manuscript. M.M. acknowledges the generous phi-

lanthropic support of Koerner and Joan Rombauer

and Don and Lynn Noren for making this research

possible.

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