identification of gastric cancer–related genes using a cdna … · identification of gastric...

Identification of Gastric Cancer–Related Genes Using a cDNA

Microarray Containing Novel Expressed Sequence

Tags Expressed in Gastric Cancer Cells

Jeong-Min Kim,1,5 Ho-Yong Sohn,4

Sun Young Yoon,1 Jung-Hwa Oh,1 Jin Ok Yang,1

Joo Heon Kim,2 Kyu Sang Song,3 Seung-Moo Rho,2

Hyan Sook Yoo,1 Yong Sung Kim,1 Jong-Guk Kim,5

and Nam-Soon Kim1

1Genome Research Center, Korea Research Institute of Bioscience andBiotechnology; 2Department of Pathology, Eulji University School ofMedicine; and 3Department of Pathology, College of Medicine,Chungnam National University, Daejeon, Korea; 4Department of Foodand Nutrition, Andong National University, Andong, Korea; and5Department of Microbiology, College of Natural Sciences, KyungpookNational University, Daegu, Korea

ABSTRACT

Purpose: Gastric cancer is one of the most frequently

diagnosed malignancies in the world, especially in Korea and

Japan. To understand the molecular mechanism associated

with gastric carcinogenesis, we attempted to identify novel

gastric cancer–related genes using a novel 2K cDNA micro-

array.

Experimental Design: A 2K cDNA microarray was

fabricated from 1,995 novel expressed sequence tags (ESTs)

showing no hits or a low homology with ESTs in public

databases from our 143,452 ESTs collected from gastric

cancer cell lines and tissues. An analysis of the gene expression

for human gastric cancer cell lines to a normal cell line was

done using this cDNA microarray. Data for the different

expressed genes were verified using semiquantitative reverse

transcription-PCR,Western blotting, and immunohistochem-

ical staining in the gastric cell lines and tissues.

Results: Forty genes were identified as either up-

regulated or down-regulated genes in human gastric cancer

cells. Among these, genes such as SKB1 , NT5C3 , ZNF9 ,

p30, CDC20 , and FEN1 , were confirmed to be up-regulated

genes in nine gastric cell lines and in 25 pairs of tissue

samples from patients by semiquantitative reverse tran-

scription-PCR. On the other hand, genes such as MT2A

and CXX1 were identified as down-regulated genes. In

particular, the SKB1 , CDC20 , and FEN1 genes were

overexpressed in z68% of tissues and the MT2A gene

was down-expressed in 72% of the tissues. Western blotting

and immunohistochemical analyses for CDC20 and SKB1

showed overexpression and localization changes of the

corresponding protein in human gastric cancer tissues.

Conclusions: Novel genes that are related to human

gastric cancer were identified using cDNA microarray

developed in our laboratory. In particular, CDC20 and

MT2A represent a potential biomarker of human gastric

cancer. These newly identified genes should provide a

valuable resource for understanding the molecular mecha-

nism associated with tumorigenesis of gastric carcinogenesis

and for the discovery of potential diagnostic markers of

gastric cancer.

INTRODUCTION

Gastric cancer is one of the most frequently diagnosed

malignancies in the world (1). It is particularly prevalent in

Korea and Japan and is one of the leading causes of cancer death

in these regions (2). Although the incidence and mortality have

been decreasing during the last several years, gastric cancer still

has a notorious position, with the first incidence and the second

cause of mortality in Korea (3).

Advances in diagnostic and treatment technologies have

enabled us to offer excellent long-term survival results for early

gastric cancer, but the prognosis of advanced gastric cancer still

remains poor (4). Recent molecular analyses revealed that gastric

cancers are closely related to genetic alterations in several genes,

such as p53, APC , E-cadherin , b-catenin , TGF-a , c-met , trefoilfactor 1 , and Runx3 (5–7). However, the common pathways of

carcinogenesis and the subsequent progression of gastric cancer

remained to be elucidated.

A cDNA microarray was used to simultaneously study

the expression profiles of a number of genes at specific

conditions in a single hybridization (8, 9). Many reports on

gene expression profiles of various cancers and diseases using

cDNA microarray techniques have been reported (10–14).

Among them, changes in gene expression in gastric cancer

cell lines and malignant tissues have been reported. In gastric

adenocarcinomas, genes such as S100A4 , CDK4 , MMP1 , and

b-catenin genes have been reported as being up-regulated

genes, the GIF gene was reported to be a down-

regulated gene (15). Ji et al . (16) has also reported the first

comprehensive review of gene expression patterns in gastric

cancer cell lines on a genomic scale. In this study, they

analyzed global gene expression patterns of 27 human cell

lines, including 12 gastric carcinoma cell lines and compared

heterogeneity between gastric cancer cell lines. In addition, a

comparison of the gastric cancer–related genes using gastric

cancer tissues and surrounding gastric mucosa tissues has been

reported, as well as a connection between the clinical

phenotypes of patients (17).

Received 4/20/04; revised 9/25/04; accepted 10/5/04.Grant support: 21C Frontier Functional Human Genome Project fromthe Ministry of Science and Technology of Korea.The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely toindicate this fact.Requests for reprints: Nam-SoonKim, Laboratory of HumanGenomics,Genome Research Center, Korea Research Institute of Bioscience andBiotechnology, P.O. Box 115, Yusong, Daejeon, Korea. Phone: 82-42-879-8112; Fax: 82-42-879-8119; E-mail: [email protected].

D2005 American Association for Cancer Research.

Vol. 11, 473–482, January 15, 2005 Clinical Cancer Research 473

Research. on August 8, 2020. © 2005 American Association for Cancerclincancerres.aacrjournals.org Downloaded from Research. on August 8, 2020. © 2005 American Association for Cancerclincancerres.aacrjournals.org Downloaded from Research. on August 8, 2020. © 2005 American Association for Cancerclincancerres.aacrjournals.org Downloaded from

http://clincancerres.aacrjournals.org/



In a previous study, we collected an entire set of genes that

are expressed in gastric cancer cell lines or tissues using full-

length enriched cDNA libraries, subtracted cDNA libraries, and

normalized cDNA libraries from gastric cancer cell lines and

tissues from Korean patients and identified the genes associated

with gastric cancer by examining their expression profiles (18).

Using this process for identifying novel gastric cancer-related

genes in which there were no hits or a low homology with known

genes in public databases, we isolated 1,995 novel genes from the

collected gastric expressed sequence tags (ESTs) and fabricated a

cDNA microarray containing these genes. However, some of the

ESTs were identified as known genes in recent updated public

databases. Using the cDNA microarray, a gene expression anal-

ysis of these genes in gastric cancer cell lines and tissues was

done. Here, we report on the identification of novel genes that are

differentially expressed in gastric cancer cell lines and tissues.

MATERIALS AND METHODS

Cell Culture, Tissues, and RNA Preparation

Human gastric cancer cell lines, SNU-1, SNU-16, SNU-

216, SNU-484, SNU-601, SNU-638, SNU-668, and SNU-719

were cultured in RPMI 1640 (Life Technologies, Grand Island,

NY) and human normal gastric cell lines Hs 677.St (ATCC CRL-

7407) in DMEM (Life Technologies) supplemented with 10%

inactivated fetal bovine serum, 2 mg/mL sodium bicarbonate,

and 1% antibiotic-antimycotic solution (Invitrogen Life Tech-

nologies, Carlsbad, CA). The Hs 677.St cell line was derived

from normal fetal stomach tissue and had a morphology similar

to a fibroblast. All cultured cells were incubated at 37jC in a

humidified incubator maintained with a 5% CO2 atmosphere

(19, 20). When the cells were about 80% to 90% confluent, they

were harvested and used for total RNA isolation. Fifty gastric

tissues containing the tumor and normal regions of 25 gastric

cancer patients were obtained from the College of Medicine,

Chungnam National University, Korea with informed consent.

The tumors were staged according to tumor-node-metastasis

classification of Union Internationale Contre le Cancer. The

obtained tissues were immediately frozen in liquid nitrogen.

Total RNA was extracted from the cultured cells and tissues

using a commercially available RNA isolation kit (Qiagen,

Hilden, Germany) following the procedures recommended by

the manufacturer.

Isolation of Novel Genes from ESTs Collected in Gastric

Cancers

The total 143,452 ESTs collected from human gastric

cancer cell lines and gastric tissues were analyzed by a BLAST

search against human mRNA (Genbank release 126, down-

loaded on Oct. 2001), UniGene (UniGene build 143, down-

loaded on Oct. 2001) and NR databases (downloaded on Oct.

2001). To isolate novel ESTs in which there were no hits or a low

homology in public databases, ESTs having an identity of <90%

for <50 bp with E V 1 � 10�3 against the human mRNA and

UniGene databases, and having an identity of <85% for <20

amino acids with E V 1 � 10�5 against the NR database were

selected. E V 1 � 10�3 indicates that the probability that a query

sequence have accidentally identity with a certain sequences in

database under given condition is V1 � 10�3. These isolated

ESTs were used to fabrication the cDNA microarray.

The novelty of these ESTs were reanalyzed by a BLAST

search against human mRNA (Genbank release 138.0, down-

loaded on Dec. 2003), RefSeq (downloaded on Dec. 2003) under

conditions of an identity of >90% for >50 bp with E V 1 �10�20. The remaining ESTs were analyzed by a BLAT search

against the human genome database (University of California

Santa Cruz6 Golden Path genome database build 15) under the

above conditions. Analysis of the ESTs that were not included in

the above searches were done under conditions of an identity of

>90% for >50 bp with E = 1 � 10�20 to 1 � 10�3 against human

mRNA and RefSeq databases and with E V 1 � 10�1 against the

NR database (downloaded on Dec. 2003).

Fabrication and Hybridization of cDNA Microarray

Clones containing the novel ESTs were grown in 96-well

culture plates and plasmid DNAs were purified using a Millipore

plasmid kit (Millipore Co., Bedford, MA). The inserts of cDNAs

using purified plasmid DNAs were amplified by PCR with the

sense primer 5V-GCAGAGCTCTCTGGCTAAC-3V, which is

localized in the vector region and the antisense primer 5V-CGTGCGGCCGCT21(G/A/C)-3V. After purifying the PCR

products on Sephadex G-50 Superfine (Amersham Pharmacia

Biotech AB, Uppsala, Sweden), they were suspended in a

Microspotting solution (ArrayItTM Brand Products, TeleChem,

Sunnyvale, CA) and spotted on CSS-100 Silyated Slides

(Aldehyde; CEL Associates, Pearland, TX) using a Carte-

sian Prosys 5510 robot (Cartesian, Inc., Irvine, CA) with 32

printing tips. Our cDNA microarray contained a total of 6,912

spots in one slide including triplicates of 1,995 cDNA, control

genes of GAPDH and b-actin , and empty spots for negative

controls.

Twenty micrograms of total RNA from a normal cell line or

cancer cell lines, respectively, were used in the cDNA micro-

array analysis. RNA of the normal cell line, labeled with Cy3,

was used as a reference versus RNAwith Cy5 from each of eight

cancer cell lines as a sample. Probe labeling and hybridization

were done using a 3DNA Array 50 kit (Genisphere, Inc.,

Hatfield, PA) according to the manufacturer’s instructions. After

the hybridization procedure, the slide was scanned at a

wavelength of 532 nm for Cy3 and at 635 nm for Cy5 using

a ScanArray 5000 scanner (Packard BioChip Technologies,

Billerica, MA). To increase the accuracy of the experiment,

each experiment was done in duplicate using two different

cDNA microarrays.

Analysis of Data Obtained from cDNA Microarray

The scanned images were analyzed using the GenePix Pro

4.0 program (Axon Instruments, Inc., Union City, CA) and the

subsequent data were normalized using the scaled print-tip group

Lowess method using the statistics for microarray analysis

package of the R7 statistics software to remove intensity

variances between spots themselves that originate from spotted

locations. If the signal to background ratio was <1.4, the feature

was processed as a null value to reduce bias. Using normalized

M values [M = log2(R/G)], we did a one class analysis using the

6 http://genome.ucsc.edu/7 http://www.maths.lth.se/help/R/com.braju.sma/

Identification of Gastric Cancer–Related Novel Genes474

Research. on August 8, 2020. © 2005 American Association for Cancerclincancerres.aacrjournals.org Downloaded from


significance analysis of microarrays8 program with a median

false discovery rate of 0.10089 and D = 1.40 to select

significantly expressed genes (21). Furthermore, to exclude

spots having a low intensity, genes having an A > 6 [A =

0.5log2(RG)] were selected. In addition, redundant clones were

removed, because our cDNA microarray had triplicate spots.

Finally, differentially expressed genes in gastric cancer cell lines

were selected for further study based on the significance analysis

of microarrays scores.

Bioinformatic Analysis of Up-Regulated or Down-Regulated

Genes

A homology search for the selected genes was done by a

BLASTn analysis against the NR database with the National

Center for Biotechnology Information9 default conditions. The

search for the symbol and function of these genes were done by

SOURCE10 and GeneCards.11 In addition, an analysis for the

chromosomal location of the selected genes was done using the

University of California Santa Cruz Golden Path human genome

database build 15 at conditions of 90% minimum identity.

Semiquantitative Reverse Transcription-PCR

The 1st cDNA was synthesized by the reverse transcription

reaction with 5 Ag of isolated RNA, 2 pmol/L of oligo (dT)20,

1 AL of 10 Amol/L deoxynucleotide triphosphate, 4 AL of 5�buffer, 2 AL of 100 mmol/L DTT, 1 AL of RNaseOUT (40 units/

AL, Invitrogen Life Technologies), and 1 AL of SuperScript II

(200 units/AL, Invitrogen Life Technologies) at 42jC for 1 hour.

The 1st cDNA was quantified using a human b-actin competi-

tive PCR kit (TaKaRa Co., Tokyo, Japan) according to the

manufacturer’s instructions. The PCR conditions were 1 cycle of

2 minutes at 94jC, 25 cycles of 30 seconds at 94jC, and 1

minute at 68jC, and 1 cycle of 1 minute at 72jC with b-actinprimer sets (Table 1). After electrophoresis in a 2% agarose gel,

the DNA concentration of b-actin (275 bp) and actin competitor

(340 bp) were analyzed using the TotalLab software program

(Phoretix Co., Newcastle Upon Tyne, United Kingdom) and the

amount of the 1st cDNA of each sample was adjusted based on

the b-actin concentration. To quantify the expression level of

the selected genes, the same volume of diluted 1st cDNAs

synthesized from gastric cells was used as a template in a PCR

reaction. Each gene was amplified by PCR which consisted of 27

cycles of 40 seconds at 94jC, 50 seconds at 55jC, and 1 minute

at 72jC with specific primer sets (Table 1). The PCR products of

each of the specific genes and b-actin (275 bp) were analyzed by

2% agarose gel electrophoresis and the expression ratio was

calculated using the TotalLab software program (Phoretix).

Western Blotting

When human gastric normal and cancer cell lines which

were cultured in media, were about 80% to 90% confluent,

they were rinsed with PBS, scrapped into 300 AL of cell lysis

buffer containing 50 mmol/L Tris (pH 7.5), 150 mmol/L

NaCl, 0.5% NP40, 1 mmol/L EDTA, 1 mmol/L phenyl-

methylsulfonyl fluoride, 1 Amol/L Pepstatin A, 1 Amol/L

Leupeptin, 1 Amol/L Aprotinin, and placed on ice for 1 hour.

The cells were then centrifuged at 15,000 � g for 15 minutes

and the supernatant was harvested. Aliquots (50 Ag) of

soluble proteins were separated on SDS-polyacrylamide-gels

and transferred to polyvinylidene difluoride membranes

(Millipore). The membranes were incubated with the mouse

monoclonal antibody against CDC20 (Santa Cruz Biotechnol-

ogy, Inc., Santa Cruz, CA), a rabbit polyclonal antibody to

SKB1 (Cell Signaling Technology, Inc., Beverly, MA) and a

mouse monoclonal antibody to h-actin (Sigma, St. Louis,

MO) at a dilution of 1:1,000, 1:1,000, and 1:50,000,

respectively. After the blots were incubated with peroxidase-

conjugated goat anti-rabbit IgG (Jackson ImmunoResearch,

WestGrove, PA) and horseradish peroxidase–conjugated goat

anti-mouse antibody (Promega, Madison, WI), immunoreactive

signals were detected using enhanced chemiluminescence kit

(Amersham Pharmacia, Piscataway, NJ).

Immunohistochemistry

Paraffin sections of gastric cancer tissue from patients

were deparaffinized with xylene and then rehydrated.

Antigenic retrieval was processed by submerging in citrate

buffer (pH 6.0) and microwaving. The sections were then

treated with 3% hydrogen peroxide in methanol to quench

endogenous peroxidase activity, followed by incubation with

1% bovine serum albumin to block nonspecific binding. The

primary anti-CDC20 (1:100 dilution) and anti-SKB1 (1:100

dilution) antibodies that are used in Western blotting were

incubated for 60 minutes at room temperature. After washing,

the tissue section was then reacted with the biotinylated anti-

mouse and anti-rabbit secondary antibodies, followed by

incubation with streptavidin-horseradish-peroxidase complex.

The tissue section was immersed in 3-amino-9-ethyl carba-

zole as a substrate, and counterstained with 10% Mayer’s

hematoxylin, dehydrated, and mounted by crystal mount. In

the negative controls, the nonimmune mouse or rabbit IgG

of the same isotype or the antibody dilution solution was

replaced the primary antibody.

RESULTS

Analysis of cDNA Included in cDNA Microarray

To isolate novel genes associated with stomach cancer, a

cDNA microarray containing novel ESTs which have low

homology or no hits in public databases was fabricated. A total

of 1,995 ESTs contained in microarray were selected as novel

ESTs from our 143,452 ESTs collected from human gastric

cancer cell lines and gastric tissues by analysis of public

databases (collected on Oct. 2001, see MATERIALS AND

METHODS). A reanalysis of these selected genes against

updated above databases, for novelty, (data collected on Dec.

2003) showed that 686 genes (34.4%) could be categorized into

known human genes against the human mRNA and RefSeq

databases with conditions of identity of >90% for >50 bp with E

V 1 � 10�20, and 559 genes (28%) without known human genes

were mapped only on the human genome against University of

California Santa Cruz Golden Path genome database build 15

under above conditions (Table 2). In addition, 690 genes were

8 http://www-stat.stanford.edu/ftibs/SAM/index.html9 http://www.ncbi.nlm.nih.gov/BLAST/10 http://source.stanford.edu/cgi-bin/sourceSearch11 http://bioinformatics.weizmann.ac.il/cards/

Clinical Cancer Research 475



categorized into ESTs of low homology and 60 genes (3.0%)

showing ‘‘no hits’’. Among known human genes, 289 genes

(14.5%) were functionally classified by the Gene Ontology

database.12 From these analyses, 1,309 ESTs excluding Known

human genes were thought to be novel ESTs, although only 60

(3%) represented novel ESTs which were sacrificed by the first

criteria, in which novel ESTs were defined as ESTs having an

identity of <90% for <50 bp with E V 1 � 10�3 against the

human mRNA and UniGene databases.

Identification of Up-Regulated or Down-Regulated Genes in

Gastric Cancer Cells

We compared the gene expression profiles of eight gastric

cancer cell lines with that of a normal gastric cell line using

cDNA microarray. After cDNA microarray hybridization,

normalization, and data analysis, we finally selected a total of

40 genes, 20 genes for up-regulation and 20 genes for down-

regulation, based on significance analysis of microarrays scores,

that showed significant expression changes in gastric cancer

cells.

As shown in Table 3, the up-regulated genes in gastric

cancer cells included known genes such as CKS1B , SCX ,

D1S155E , FKBP4 , SKB1 , NT5C3 , p30, GPI , PRO2000 ,

CDC20 , FEN1, ZNF9 , and RPS16 and functionally unknown

genes such as FLJ31196, FLJ39478 , and FLJ90345 . In

addition, four novel genes NSG-21-D10 , NSG-18-A07 , NSG-

05-E12 , and NSG-08-D09 were included. A search of the

SOURCE and GeneCards database for the function of these

selected genes indicated that their biological functions were

diverse and included genes related to a cell cycle regulator

(CKS1B , SKB1 , and CDC20), transcription (SCX), develop-

ment (D1S155E), protein folding (FKBP4), DNA repair

(FEN1), and biosynthesis (ZNF9 , RPS16). Furthermore, a

search of chromosomal locations for the up-regulated genes

was done by mapping the in University of California Santa

Cruz Golden Path human genome database. The analysis

showed that of the 20 genes, 13 were localized in

chromosome 1 (CKS1B , D1S155E , and CDC20), chromosome

8 (SCX , FLJ39478 , and PRO2000), chromosome 11 (FEN1

and NSG-18-A07), chromosome 17 (FLJ31196 and p30), and

chromosome 19 (GPI , FLJ90345, and RPS16). The genes

localized in chromosome 17 and chromosome 19 were

clustered in 17p11.2 and 19q13, respectively.

Genes representing a down-regulated expression in gastric

cancer cells included known genes such as LGALS1 , OAZ1 ,

PEA15 , SEC61A1 , LGP1 , MT2A , MAGED2 , NPDC1 , CXX1 ,

FKBP8 , and PGR1 and functionally unknown genes such as

DXS9879E , FLJ34386 , FLJ20920 , and FLJ30061 and five

novel genes (Table 4). The functional analysis of these selected

genes showed that the genes related with apoptosis (LGALS1),

polyamine biosynthesis (OAZ1), protein targeting (SEC61A1),

and protein folding (FKBP8) were included. In addition, many

of the down-regulated genes were localized in chromosome 17,

chromosome 19, and chromosome X. Among them, two genes

LGP1 and FLJ20920 were clustered in 17q21.

Verification of mRNA Levels for Selected Genes Using

Semiquantitative Reverse Transcription-PCR

To more quantitatively verify the data obtained from our

DNA microarray, we randomly selected seven up-regulated

genes (CKS1B , SKB1 , NT5C3 , ZNF9 , p30, CDC20 , and FEN1)

and five down-regulated genes (LGALS1 , OAZ1 , DXS9879E ,

MT2A , and CXX1) in gastric cancer and did semiquantitative

reverse transcription-PCR (RT-PCR) in nine normal and gastric

cancer cell lines, and in 25 pairs of gastric normal and tumor

tissues in the I to IV stages.

As shown in Fig. 1A , the expression of all the up-regulated

genes were higher in most of the cancer cell lines than in

normal cell lines, Hs 677.St. All of these genes were also highly

Table 1 Primer sequences and the product size of selected genes used in RT-PCR

Gene Sense (5V!3V) Antisense (5V!3V) Size (bp)

CKS1B ACGACGACGAGGAGTTTGAG CCGCAAGTCACCACACATAC 584SKB1 CAAGTTGGAGGTGCAGTTCA GCCCACTCATACCACACCTT 1,074NT5C3 TGATGCCAGAATTCCAGAAA CAACATTGGCCACTCCATCT 723ZNF9 TTCAAGTGTGGACGATCTGG TTGCTGCAGTTGATGGCTAC 437P30 CTTCTCGCTTCAAGCTCCTG TGTTCTTGATGGTCTTGTGCTC 249CDC20 GTACCTGTGGAGTGCAAGC GTAATGGGGAGACCAGAGG 618FEN1 CATGGACTGCCTCACCTTC CGGTCACCTTGAAGAAATC 508LGALS1 GACGCTAAGAGCTTCGTGCT GTAGTTGATGGCCTCCAGGT 282MT2A ATGGATCCCAACTGCTCCT CTTTGCAGATGCAGCCTTG 154CXX1 GGAGGAGGACGAGGACTTCT TGGGCAGAATGATGTAGTCG 418Actin CAAGAGATGGCCACGGCTGCT TCCTTCTGCATCCTGTCGGCA 275

Table 2 Contents of the cDNA microarray

Categories Novel genes (%)

Known human genes* 289 (14.5)Known functiony 397 (19.9)Unknown functiony 397 (19.9)

Human genomez 559 (28.0)ESTs (low homology)x 690 (34.6)No hitsk 60 (3.0)Total 1,995 (100)

*An identity of >90% for >50 bp with a E V 1 � 10�20 againsthuman mRNA and RefSeq databases.

yAccording to the Gene Ontology consortium http://www.geneon-tology.org).

zNot categorized in known human genes, but mapped on humanGolden Path build 15 at condition of >90% identity.

xNot categorized in known human genes and human genome, buthave an identity of above 90% with E = 1 � 10�20 to 1 � 10�3 againsthuman mRNA and RefSeq database and an E V 1 � 10�1 against NRdatabase.

kNot found in any databases under the above conditions.12 http://www.geneontology.org/




expressed in most of the tumor tissues compared with their

normal tissues (Fig. 1B). These genes were highly expressed in

tumor tissues with a frequency of 40% to 88% in 25 tissue pairs

that were classified as containing I to IV stages of gastric

cancer. Among these genes, the CDC20 gene was the most

highly expressed in 22 tumor tissues of the 25 tissue pairs with

a high frequency of 88% which covered all stages of gastric

cancer. The SKB1 and FEN1 genes were also detected at high

Table 3 Up-regulated genes in gastric cancer cells in comparison to gastric normal cell

No.* Clone name Homology search Gene symbol Functiony Chromosome location Accession no.z

1 NSG-19-G11 Hypothetical protein FLJ31196 FLJ31196 — 17p11.2 BQ0824342 NSG-03-F01 CDC28 protein kinase regulatory

subunit 1BCKS1B cell cycle control 1q22 CB104710

3 NSG-06-C08 Homo sapiens class II bHLHproteinscleraxis (SCX) gene

SCX transcription 8x —

4 NSG-11-H11 cDNA FLJ39478 FLJ39478 — 8q13.2 BM8382625 NSG-11-H08 NRAS-related gene D1S155E development 1p13.2 BM7499716 NSG-17-H01 FK506-binding protein 4

(59 kDa)FKBP4 protein folding 12p13.33 —

7 NSG-06-C12 SKB1 homologue(Schizosaccharomyces pombe)

SKB1 cell proliferation 14q11.2 —

8 NSG-07-G05 5V nucleotidase, cytosolic III NT5C3 nucleotide metabolism 7p14.3 BQ0820239 NSG-16-G09 nuclear proteinp30 p30 — 17p11.2 BM76448110 NSG-14-A11 glucose phosphate isomerase GPI Glycolysis 19q13.11 BM83747711 NSG-08-D03 cDNA clone FLJ90345 FLJ90345 — 19q13.32 BQ08218212 NSG-21-D10 unknown — — 7q36.1 BM79225613 NSG-13-A06 PRO2000 protein PRO2000 nucleotide binding 8q24.13 BM74683514 NSG-11-G05 cell division cycle 20 homologue

(Saccharomyces cerevisiae)CDC20 regulation of cell cycle 1p34.2 BM742641

15 NSG-16-F01 flap structure–specific endonuclease 1 FEN1 DNA repair 11q12.2 —16 NSG-14B06 zinc finger protein 9 ZNF9 cholesterol biosynthesis 3q21.3 BM83731117 NSG-18-A07 unknown — — 11p15.5 BM82655418 NSG-05-E12 Unknown — — — BM74280719 NSG-12-F03 ribosomal protein 16 RPS16 protein biosynthesis 19q13.2 BM76456520 NSG-08-D09 unknown — — — BM759098

*Number represents the order of genes selected from a significance analysis of microarrays.yGene function according to SOURCE and GeneCards.zGenbank accession no.xKnown as only the chromosome number.

Table 4 Down-regulated genes in gastric cancer cells in comparison to gastric normal cell

No.* Clone name Homology search Gene symbol Functiony Chromosome location Accession no.z

1 NSG-18-B07 lectin, galactoside-binding, soluble, 1 LGALS1 apoptosis/cell differentiation 22q13.1 BM7405712 NSG-05-G04 ornithine decarboxylase antizyme 1 OAZ1 polyamine biosynthesis 19p13.3 BM7457273 NSG-21-C09 unknown — — 2q22.3 CB1048814 NSG-03-B06 phosphoprotein enriched in

astrocytes 15PEA15 small molecular transport 1q23.2 —

5 NSG-14-F03 DNA segment on chromosome X(unique) 9879 expressed sequence

DXS9879E — Xq28 M827357

6 NSG-15-D02 FLJ34386 fis, clone HCHON1000166 FLJ34386 — 12q13.2 BM7639097 NSG-02-E05 protein transport protein SEC61 alpha

subunit isoform 1SEC61A1 protein targeting 3q21.3 —

8 NSG-21-B09 H. sapiens D11lgp1e-like, fragment LGP1 — 17q21.2 BM7900489 NSG-21-E10 hypothetical protein FLJ20920 FLJ20920 — 17q21.33 BM79535810 NSG-15-D03 metallothionein-II gene MT2A metal ion binding 16q12.2 BQ08215911 NSG-17-B05 melanoma antigen, family D, 2 MAGED2 — Xp11.21 BM79047012 NSG-12-D11 neural proliferation, differentiation

and control, 1NPDC1 Integral to membrane 9q34.3 —

13 NSG-05-G03 unknown — — — —14 NSG-21-F08 unknown — — — —15 NSG-15-C07 CAAX box 1 CXX1 — Xq26.3 BM76306316 NSG-21-D05 FK506 binding protein 8 FKBP8 protein folding 19q13.11 BM79040417 NSG-19-A04 T-cell activation protein PGR1 — 4p16.1 BM77167418 NSG-08-C02 unknown — — — BM75744119 NSG-07-F01 unknown — — — BQ08195820 NSG-07-F02 cDNA FLJ30061 FLJ30061 — 7q32.3 BQ081959

*Number represents the order of genes selected from a significance analysis of microarrays.yGene function according to SOURCE and GeneCards.zGenbank accession no.




Fig. 1 Semiquantitative RT-PCR of selected genes from the cDNA microarray. Total RNAs isolated from gastric cell lines and tissues were used astemplates for semiquantitative RT-PCR, according to the manufacturer’s instructions (for details, see MATERIALS AND METHODS). The RT-PCRproducts were electrophoresised on a 2% agarose gel. A, expression levels of target genes in gastric cell lines. Hs677.St, gastric normal cell line; SNUseries, gastric cancer cell lines established from Korean patients. The b-actin gene was used as a reference. B, expression levels of target genes in gastrictumor and normal tissues. The transcriptional levels of the target genes were calculated relative to the amount of b-actin gene. a-f, up-regulated genes inthe cancer cells; g-h, down-regulated genes in the cancer cells; 5, normal tissues from gastric cancer patients; n, tumor tissues from gastric tumorpatients; IA, IB, II, IIIA/B, and IV: stages of gastric cancer tissues according to tumor-necrosis-metastasis classification of Union Internationale Contrele Cancer.




levels in the IB and II stages of tumor tissues for SKB1 and in

II and III A/B stages for FEN1 with a frequency of 68% (17

in 25 cases) and 72% (18 in 25 cases), respectively. All of the

up-regulated genes detected in tissues were highly detected in

most of the II stage gastric cancers. However, CKS1B was not

detected in any of the gastric tissues, though it was detected in

very low amounts in cancer cell lines. On the other hand, three

down-regulated genes, except for OAZ1 and DXS9879E , were

detected at low levels in many of the cancer cell lines compared

with the normal cell line, Hs 677.St, as shown in Fig. 1A . When

the expression levels of three genes, LGALS1 , MT2A , and

CXX1 , were examined in gastric tissues, MT2A was found to be

detected at low levels in the tumor tissues, but had high

expression levels in normal tissues with a frequency of 72% (18

of 25 cases). Its higher expression was detected over a wide

stage from IB to IV in normal gastric tissues. The other gene,

CXX1 , was highly expressed in normal tissues with frequencies

of about 32% in various stages. However, LGALS1 was not

detected in any of the gastric tissues, because of very low

amounts in tissues. These results indicate that the mRNA levels

of target genes in gastric tissues were largely consistent with

those of the cell lines. Additionally, these results from

semiquantitative RT-PCR are in relatively good agreement with

the DNA microarray data.

Verification of Protein Levels for Selected Genes Using

Western Blotting and Immunohistochemistry

We verified the protein levels for genes that had been

confirmed by RT-PCR using Western blotting for nine gastric

normal and cancer cell lines, and immunohistochemistry for six

gastric tissues. Because antibodies for only CDC20 and SKB1

were available, these two proteins were selected as targets.

As shown in the Western blotting of Fig. 2A , high levels of

protein for CDC20 were detected in the gastric cancer cell lines

in comparison with the normal cell line, especially for SNU-601,

SNU-638, and SNU-719. The immunohistochemistry also

showed that CDC20 was highly detected in gastric tumor tissue,

although it was present in normal tissue from the patient samples

(Fig. 2B , a-c). However, differently from normal tissue, it was

localized in perinuclear region of the cell in tumor tissues and the

localization change was more strongly detected in poorly

differentiated gastric tumors. Otherwise, when the protein level

for SKB1 was checked by Western blotting, it was also detected

Fig. 2 Western blotting and immunohisto-chemistry for selected genes identified by thecDNA microarray. A, Western blot analysis ofCDC20 and SKB1 in gastric cell lines. Equalamounts of cell lysates (50 Ag) were resolvedby SDS-PAGE, transferred to PVDF mem-brane, and probed with specific antibodies(anti-CDC20 and anti-SKB1) and anti-h-actinantibody as control for protein level. B,immunohistochemical staining for CDC20and SKB1 in the gastrointestinal tumortissues. These photographs depict representa-tive areas from the normal gastrointestinaltissues (a and d), moderately differentiated (band e) and poorly differentiated gastrointes-tinal tumor tissues (c and f ). a-c, CDC20; d-f, SKB1. Bars, 100 Am (a-f ).




at high levels in gastric cancer cell lines. In particular, the

amounts expressed were dramatically high in SNU-1, SNU-16,

SNU-216, and SNU-638 (Fig. 2A). It is also noteworthy that a

large band, higher than the 70 kDa band, corresponding to

SKB1, was detected for SNU-216, which is thought to be the

result of the post-modification of SKB1 or an alternative

transcript. This band was also faintly detected in Hs 677.St.

Figure 2B (d-f) shows immunohistochemical results for SKB1 in

gastric normal and tumor tissues from the patient samples. As

predicted, it was highly expressed in gastric tumors compared

with normal tissue. As shown in CDC20, a change in

localization for SKB1, mainly in the nuclear region, also

detected in tumor tissues. These results indicate that an increase

in the mRNA level for CDC20 and SKB1 in gastric tumor

tissues coupled with that of the protein level and the change in

the amount produced and their localization are associated with

carcinogenesis in gastric tumors.

DISCUSSIONcDNA microarray technologies aid in analyses of the

expression levels of several thousands of genes for multiplesamples at the same time. Numerous attempts to identify genesrelated to carcinogenesis of various cancers including gastriccancer using a DNA microarray have been reported (10–17, 22).We selected ESTs having a low homology or no hits with ESTsin public databases from our Korean UniGene Information ESTsclone bank and used this as a DNA source for the fabrication of amicroarray in order to identify novel genes that are associatedwith gastric cancer. All of the selected 1,995 ESTs were novelESTs at the first stage. However, because a considerable amountof EST data has been recently submitted to public databases byrapid advances in high-throughput sequencing, of these ESTs,only 60 genes (3%), in a homology analysis against updatedpublic databases represented novel ESTs which are sacrificedwith the first criteria. However, as shown in Table 2, 1,309 ESTsexcluding known human genes were classified as novel genes.When 2K microarray experiments using 1,995 cDNAwere done,the signal intensities obtained were generally lower than those ofa 14K cDNA microarray fabricated from our 143,452 ESTs (datanot shown). In addition, the results of RT-PCR for the targetgenes indicated that the mRNA levels of many of the genes werevery low or not detectable. These results indicate that the genesincluded in the 2K microarray were rarely expressed in cells andthat the difference in expression of these genes also can be easilyexcluded, compared with those of abundantly expressed genes.Therefore, our 2K microarray might be potentially useful inidentifying rare genes related to stomach cancer.

When the expression profiles of the gastric cancer cells and

the normal cells were compared using our 2K microarray, 40

genes showing significant differences were found. Difference in

the expression of these genes was also confirmed by semiquan-

titative RT-PCR data, collected from gastric cell lines and tissues

from patients. Among the selected genes, several genes related to

the cell cycle, CKS1B , CDC20 , and SKB1 , were identified as

up-regulated genes. Interestingly, the CDC20 and SKB1 genes

were highly represented with a very high frequency of 88% and

68% in gastric tumor tissues in comparison with normal tissues,

although the CKS1B transcript was not detected in gastric tissues

because of the low expression. Furthermore, a higher expression

of two genes in gastric cancers was also detected by their protein

level using Western blotting and immunohistochemistry. These

results indicate that the up-regulation of two genes coupled

transcription to translation. These results also showed changes in

the localization of these proteins in tumor tissues, from the

cytosol to the perinuclear region for CDC20 and to the nucleus

for SKB1, respectively. These findings indicate that the amount

of change of these genes that encoded transcript and protein as

well as the change in localization is correlated with the

oncogenesis of human gastric cancer.

CDC20 is known to directly bind to the anaphase-

promoting complex with hCDH1 and activates anaphase-

promoting complex by which anaphase is initiated and mitosis

is terminated (23). The overexpression of CDC20 has previously

been reported in human pancreatic cancer (24) and its alteration

has also been detected in early-stage lung adenocarcinoma (25).

The up-regulation of CDC20 in gastric cancer was confirmed by

gene expression data linked to SOURCE in which CDC20 and

CKS1B has been reported to be up-regulated in gastroesophageal

adenocarcinomas (26). Meanwhile, the up-regulation of CDC20

has been reported to be related to apoptosis in Taxol-induced

HeLa cells and NIH3T3 (27), myeloid cells (28, 29). Therefore,

it is likely that function of the CDC20 in cells may depend on the

stage, type and environments of the cells. CKS1B has been

known to be a CDC28 protein kinase regulatory subunit 1B. The

overexpression of CKS1B has been previously reported in gastric

cancer (15, 22) and in pancreatic cancer (12). CKS1B has also

been proposed to facilitate the transcription of the CDC20 gene

through the remodeling of transcriptional complexes or chroma-

tin that is associated with the CDC20 gene (30). These finding

suggest that CDC20 and CKS1B may act sequentially in the

tumorigenesis of gastric cancer, although it has not been reported

that CDC20 is related to gastric cancer. It has previously been

reported that SKB1 in fission yeast plays a role in the control of

cell polarity (31), in the negative regulation of mitosis (32), and

in the coordination of cell cycle progression (33). It has also

been proposed to act as a mediator of the hyperosmotic stress

response (34), but its relation to oncogenesis has not yet been

reported.

Genes involving nucleotide metabolism, DNA repair, and

cholesterol biosynthesis such as NT5C3 , p30 , FEN1 , and

ZNF9 are also up-regulated in gastric cancer cells, as evidenced

from the microarray data as well as semiquantitative RT-PCR.

In particular, FEN1 was highly expressed with a high

frequency of 72% in gastric tumor tissues, compared with

normal tissues. These observation are consistent with the

finding that increased FEN1 expression leads to rapid tumor

progression of mouse gastrointestinal tract cancer in a haplo-

insufficient manner (35). The up-regulation of the gene has also

been reported in human lung cancer cell lines (36). It has been

reported that a deficiency in NT5C3 causes an autosomal

recessive hemolytic anemia (37) and ZNF9 involve in

myotonic dystrophy 2 (38). p30 has been identified as a

component of a purified nucleoporin fraction from rat liver nuclei

(39). Although these genes have not been reported to be related to

human gastric cancer, they do, in fact, seem to be new candidates

for gastric cancer, on based on the results herein, because the up-

regulation of these genes was detected in gastric tumor tissues

with a high frequency of 40% to 72%.




On the other hand, of the down-regulated genes in gastric

cancer, MT2A was down-expressed with a high frequency of

72% in tumor tissues from the IB to IV stages. It is known to be

involved in the regulation of carcinogenesis and apoptosis such

as an activator of cell proliferation and an inhibitor of apoptosis,

as well as various other physiologic processes (40, 41). Although

this gene has been reported to be up-regulated in human breast

cancers (42) and esophageal cancer (41), its expression is known

to be down-regulated in gastroesophageal adenocarcinomas in

gene expression data linked to SOURCE (26). Thus, it is likely

that MT2A expression in tumor cells may depend on the

developmental stage or the specific type of tumor. Genes such as

LGALS1 and CXX1 were also down-regulated. LGALS1 is

known to regulate cell apoptosis and to act as an autocrine-

negative growth factor that regulates cell proliferation. Our data

indicated that it represents a high priority candidate among the

down-regulated genes in stomach cancer cell lines in comparison

with normal cell lines, although it was not detected in stomach

tissue because of its low abundance. However, contrary to our

data, the up-regulation of LGALS1 has been reported in several

tumors such as head and neck squamous carcinoma (43), human

colon cancer (44, 45), and human pancreatic cancer (46). These

observations imply that the mechanism of LGALS1 in human

gastric cancer might be different from that reported for other

cancers. Reports concerning CXX1 being down-regulated in

tumor tissues with a frequency of about 32%, except having a

CAAX box 1 have not yet appeared.

Some tumor suppressor genes and oncogenes under the

control of genomic change were clustered in specific chromo-

somal regions. The data herein indicate that some of the up-

regulated genes were clustered in chromosome 17p11.2 and

chromosome 19q13, and some of the down-regulated genes

in chromosome 17q21. These observations are supported by

previous findings showing that the amplification and rearrange-

ment of chromosome 17p11.2 occurred at a high frequency in

Birt-Hogg-Dube syndrome (47), osteosarcoma (48, 49), and

glioma (50), and the breakpoint of chromosomal abnormalities

at band chromosome 19q13 is frequently found in primary

gastric cancer (51). The presence of tumor suppressor genes on

chromosome 17q21 is also supported by the proposal that chro-

mosome 17q21, including the BRCA1 locus, may contain a

candidate for tumor suppressor genes in gastric cancer (52).

These reports and our data imply that the up-regulated genes

clustered on chromosome 17p11.2 and chromosome 19q13

might be candidates for an oncogene, and the down-regulated

genes on chromosome 17q21 candidates for a tumor suppressor.

Several groups have recently reported on the results of

expression profile analyses in gastric cancers using high-density

microarrays (15–17, 22, 53–59). The candidate genes reported

by these groups were mostly abundantly or intermediately

expressed genes in gastric cancers, whereas many of our

candidate genes are rarely expressed genes or novel genes

which were seldom selected by other groups. By combining

these results, as mechanisms related to gastric cancer pathogen-

esis and progression, we propose that up-regulated CKS1B in

gastric cancer cells might promote the expression of CDC20, the

highly induced the CDC20 would also increase the activation of

anaphase-promoting complex and the initiation of anaphase and

the progression of the cell cycle then be accelerated. In addition,

of hypoxia related proteins induced by HIF-1a, glycolytic

enzymes such as GAPD, ENO1, PKM2, PGK1, and LDHA have

been reported to up-regulated in gastric cancer (18, 60). GPI, an

enzyme involved in glycolysis, is known to be a hypoxia-

inducible factor in other forms of cancer (61). The findings here

indicate that this gene is up-regulated in gastric cancer cell lines.

From these results, one possibility is that the HIF-1a signaling

pathway might be related to the pathogenesis and progression of

gastric cancer. These newly identified genes should provide

valuable resources for developing an understanding of the

molecular mechanism associated with tumorigenesis of gastric

cancer and for discovering potential diagnostic markers for

gastric cancer.

ACKNOWLEDGMENTSWe thank Dr. Young-il Yeom for spotting the DNAs on the slides.

REFERENCES

1. Mitelman F. Catalogue of chromosome aberrations in cancer.Cytogenet Cell Genet 1983;36:1–515.

2. Neugut AI, Hayek M, Howe G. Epidemiology of gastric cancer.Semin Oncol 1996;23:281–91.

3. Lee HJ, Yang HK, Ahn YO. Gastric cancer in Korea. Gastric Cancer2002;5:177–82.

4. Roukos DH. Current status and future perspectives in gastric cancermanagement. Cancer Treat Rev 2000;26:243–55.

5. Werner M, Becker KF, Keller G, Hofler H. Gastric adenocarcinoma:pathomorphology and molecular pathology. J Cancer Res Clin Oncol2001;127:207–16.

6. Park WS, Oh RR, Park JY, et al. Somatic mutations of the trefoilfactor family 1 gene in gastric cancer. Gastroenterology 2000;119:691–8.

7. Li QL, Ito K, Sakakura C, et al. Causal relationship between the lossof RUNX3 expression and gastric cancer. Cell 2002;109:113–24.

8. DeRisi J, Penland L, Brown PO, et al. Use of a cDNA microarrayto analyse gene expression patterns in human cancer. Nat Genet1996;14:457–60.

9. Duggan DJ, Bittner M, Chen Y, Meltzer P, Trent JM. Expressionprofiling using cDNA microarrays. Nat Genet 1999;21:10– 4.

10. Ross DT, Scherf U, Eisen MB, et al. Systematic variation in geneexpression patterns in human cancer cell lines. Nat Genet 2000;24:227–35.

11. Wikman H, Kettunen E, Seppanen JK, et al. Identification ofdifferentially expressed genes in pulmonary adenocarcinoma by usingcDNA array. Oncogene 2002;21:5804–13.

12. Han H, Bearss DJ, Browne LW, Calaluce R, Nagle RB, Von Hoff DD.Identification of differentially expressed genes in pancreatic cancer cellsusing cDNAmicroarray. Cancer Res 2002;62:2890–6.

13. Jiang Y, Harlocker SL, Molesh DA, et al. Discovery of differentiallyexpressed genes in human breast cancer using subtracted cDNA librariesand cDNA microarrays. Oncogene 2002;21:2270–82.

14. Yang SH, Kim JS, Oh TJ, et al. Genome-scale analysis ofresveratrol-induced gene expression profile in human ovarian cancercells using a cDNA microarray. Int J Oncol 2003;22:741–50.

15. El-Rifai W, Frierson HF Jr, Harper JC, Powell SM, Knuutila S.Expression profiling of gastric adenocarcinoma using cDNA array. Int JCancer 2001;92:832–8.

16. Ji J, Chen X, Leung SY, et al. Comprehensive analysis of the geneexpression profiles in human gastric cancer cell lines. Oncogene2002;21:6549–56.

17. Lee S, Baek M, Yang H, et al. Identification of genes differentiallyexpressed between gastric cancers and normal gastric mucosa withcDNA microarrays. Cancer Lett 2002;184:197–206.

18. Kim NS, Hahn Y, Oh JH, et al. Gene cataloging and expression




profiling in human gastric cancer cells by expressed sequence tags.Genomics 2004;83:1024–45.

19. Park JG, Frucht H, LaRocca RV, et al. Characteristics of cell linesestablished from human gastric carcinoma. Cancer Res 1990;50:2773–80.

20. Park JG, YangHK,KimWH, et al. Establishment and characterizationof human gastric carcinoma cell lines. Int J Cancer 1997;70:443–9.

21. Tusher VG, Tibshirani R, Chu G. Significance analysis of micro-arrays applied to the ionizing radiation response. Proc Natl Acad SciU S A 2001;98:5116–21.

22. Hippo Y, Taniguchi H, Tsutsumi S, et al. Global gene expressionanalysis of gastric cancer by oligonucleotide microarrays. Cancer Res2002;62:233–40.

23. Fang G, Yu H, Kirschner MW. Direct binding of CDC20 proteinfamily members activates the anaphase-promoting complex in mitosisand G1. Mol Cell 1998;2:163–71.

24. Li D, Zhu J, Firozi PF, et al. Overexpression of oncogenic STK15/BTAK/Aurora A kinase in human pancreatic cancer. Clin Cancer Res2003;9:991–7.

25. Singhal S, Amin KM, Kruklitis R, et al. Alterations in cell cyclegenes in early stage lung adenocarcinoma identified by expressionprofiling. Cancer Biol Ther 2003;2:291–8.

26. Su AI, Welsh JB, Sapinoso LM, et al. Molecular classification ofhuman carcinomas by use of gene expression signatures. Cancer Res2001;61:7388–93.

27. Makino K, Yu D, Hung MC. Transcriptional upregulation andactivation of p55Cdc via p34(cdc2) in Taxol-induced apoptosis.Oncogene 2001;20:2537–43.

28. Kao CT, Lin M, O’Shea-Greenfield A, Weinstein J, Sakamoto KM.Over-expression of p55Cdc inhibits granulocyte differentiation andaccelerates apoptosis in myeloid cells. Oncogene 1996;13:1221–9.

29. Lin M, Mendoza M, Kane L, Weinstein J, Sakamoto KM. Analysisof cell death in myeloid cells inducibly expressing the cell cycle proteinp55Cdc. Exp Hematol 1998;26:1000–6.

30. Morris MC, Kaiser P, Rudyak S, Baskerville C, Watson MH,Reed SI. Cks1-dependent proteasome recruitment and activation ofCDC20 transcription in budding yeast. Nature 2003;424:1009–13.

31. Wiley DJ, Marcus S, D’urso G, Verde F. Control of cell polarity infission yeast by association of Orb6p kinase with the highly conservedprotein methyltransferase Skb1p. J Biol Chem 2003;278:25256–63.

32. Gilbreth M, Yang P, Bartholomeusz G, et al. Negative regulationof mitosis in fission yeast by the shk1 interacting protein skb1 andits human homolog, Skb1Hs. Proc Natl Acad Sci U S A 1998;95:14781–6.

33. Krapivinsky G, Pu W, Wickman K, Krapivinsky L, Clapham DE.pICln binds to a mammalian homolog of a yeast protein involved inregulation of cell morphology. J Biol Chem 1998;273:10811–4.

34. Bao S, Qyagng Y, Yang P, et al. The highly conserved proteinmethyltransferase, Skb1, is a mediator of hyperosmotic stress responsein the fission yeast Schizosaccharomyces pombe . J Biol Chem 2001;276:14549–52.

35. Kucherlapati M, Yang K, Kuraguchi M, et al. Haploinsufficiency ofFlap endonuclease (Fen1) leads to rapid tumor progression. Proc NatlAcad Sci U S A 2002;99:9924–9.

36. Sato M, Girard L, Sekine I, et al. Increased expression and nomutation of the Flap endonuclease (FEN1) gene in human lung cancer.Oncogene 2003;22:7243–6.

37. Marinaki AM, Escuredo E, Duley JA, et al. Genetic basis ofhemolytic anemia caused by pyrimidine 5V nucleotidase deficiency.Blood 2001;97:3327–32.

38. Liquori CL, Ricker K, Moseley ML, et al. Myotonic dystrophy type2 caused by a CCTG expansion in intron 1 of ZNF9. Science 2001;293:864–7.

39. Cronshaw JM, Krutchinsky AN, Zhang W, Chait BT, Matunis MJ.Proteomic analysis of the mammalian nuclear pore complex. J Cell Biol2002;158:915–27.

40. Huang G, Zhou S, Du H. Study on role of metallothionein inanticancer effect of copper green on treatment of experimental

hepatocarcinoma in mice. Zhongguo Zhong Xi Yi Jie He Za Zhi2000;20:368–70.

41. Cui Y, Wang J, Zhang X, et al. ECRG2, a novel candidate of tumorsuppressor gene in the esophageal carcinoma, interacts directly withmetallothionein 2A and links to apoptosis. Biochem Biophys ResCommun 2003;302:904–15.

42. Jin R, Chow VT, Tan PH, Dheen ST, Duan W, Bay BH.Metallothionein 2A expression is associated with cell proliferation inbreast cancer. Carcinogenesis 2002;23:81–6.

43. Gillenwater A, Xu XC, Estrov Y, Sacks PG, Lotan D, Lotan R.Modulation of galectin-1 content in human head and neck squamouscarcinoma cells by sodium butyrate. Int J Cancer 1998; 75:217–24.

44. Ohannesian DW, Lotan D, Lotan R. Concomitant increases ingalectin-1 and its glycoconjugate ligands (carcinoembryonic antigen,lamp-1, and lamp-2) in cultured human colon carcinoma cells by sodiumbutyrate. Cancer Res 1994;54:5992–6000.

45. Hittelet A, Legendre H, Nagy N, et al. Upregulation of galectins-1and -3 in human colon cancer and their role in regulating cell migration.Int J Cancer 2003;103:370–9.

46. Berberat PO, Friess H, Wang L, et al. Comparative analysis ofgalectins in primary tumors and tumor metastasis in human pancreaticcancer. J Histochem Cytochem 2001;49:539–49.

47. Schmidt LS, Warren MB, Nickerson ML, et al. Birt-Hogg-Dubesyndrome, a genodermatosis associated with spontaneous pneumothoraxand kidney neoplasia, maps to chromosome 17p11.2. Am J Hum Genet2001;69:876–82.

48. van Dartel M, Cornelissen PW, Redeker S, et al. Amplification of17p11.2 approximately p12, including PMP22, TOP3A, and MAPK7, inhigh-grade osteosarcoma. Cancer Genet Cytogenet 2002;139:91–6.

49. Lau CC, Harris CP, Lu XY, et al. Frequent amplification andrearrangement of chromosomal bands 6p12-p21 and 17p11.2 inosteosarcoma. Genes Chromosomes Cancer 2004;39:11–21.

50. van Dartel M, Leenstra S, Troost D, Hulsebos TJ. Infrequent buthigh-level amplification of 17p11.2 approximately p12 in human glioma.Cancer Genet Cytogenet 2003;140:162–6.

51. Ochi H, Douglass HO Jr, Sandberg AA. Cytogenetic studies inprimary gastric cancer. Cancer Genet Cytogenet 1986;22:295–307.

52. Semba S, Yokozaki H, Yasui W, Tahara E. Frequent microsatelliteinstability and loss of heterozygosity in the region including BRCA1(171) in young patients with gastric cancer. Int J Oncol 1998;12:1245–51.

53. Kim B, Bang S, Lee S, et al. Expression profiling and subtype-specific expression of stomach cancer. Cancer Res 2003;63:8248–55.

54. Tay ST, Leong SH, Yu K, et al. A combined comparative genomichybridization and expression microarray analysis of gastric cancerreveals novel molecular subtypes. Cancer Res 2003;63:3309–16.

55. Boussioutas A, Li H, Liu J, et al. Distinctive patterns of geneexpression in premalignant gastric mucosa and gastric cancer. CancerRes 2003;63:2569–77.

56. Hasegawa S, FurukawaY, Li M, et al. Genome-wide analysis ofgene expression in intestinal-type gastric cancers using a complementaryDNA microarray representing 23,040 genes. Cancer Res 2002;62:7012–7.

57. Inoue H, Matsuyama A, Mimori K, Ueo H, Mori M. Prognosticscore of gastric cancer determined by cDNA microarray. Clin Cancer Res2002;8:3475–9.

58. Sakakura C, Hagiwara A, Nakanishi M, et al. Differential geneexpression profiles of gastric cancer cells established from primarytumour and malignant ascites. Br J Cancer 2002;87:1153–61.

59. Chen X, Leung SY, Yuen ST, et al. Variation in gene expressionpatterns in human gastric cancers. Mol Biol Cell 2003;14:3208–15.

60. Meireles SI, Carvalho AF, Hirata R, et al. Differentially expressedgenes in gastric tumors identified by cDNA array. Cancer Lett 2003;190:199–211.

61. Naughton DP. Hypoxia-induced upregulation of the glycolyticenzyme glucose-6-phosphate isomerase perpetuates rheumatoid arthritis.Med Hypotheses 2003;60:332–4.




Correction: Article on Identification of Gastric-Related Genes Using a cDNAMicroarray

In the article on Identification of Gastric-Related Genes in the January 15, 2005 issue ofClinical Cancer Research , the name of an author, Hyang-Sook Yoo, was misspelled.

Kim JM, Sohn HY, Yoon SY, et al. Identification of gastric cancer-related genes using acDNA microarray containing novel expressed sequence tags expressed in gastric cancer cells.Clin Cancer Res 2005:11:473–82.

www.aacrjournals.org Clin Cancer Res 2005;11(8) April 15, 20053149

Corrections

2005;11:473-482. Clin Cancer Res Jeong-Min Kim, Ho-Yong Sohn, Sun Young Yoon, et al. Tags Expressed in Gastric Cancer CellscDNA Microarray Containing Novel Expressed Sequence

Related Genes Using a−Identification of Gastric Cancer

Updated version

http://clincancerres.aacrjournals.org/content/11/2/473

Access the most recent version of this article at:

Cited articles

http://clincancerres.aacrjournals.org/content/11/2/473.full#ref-list-1

This article cites 61 articles, 21 of which you can access for free at:

Citing articles

http://clincancerres.aacrjournals.org/content/11/2/473.full#related-urls

This article has been cited by 13 HighWire-hosted articles. Access the articles at:

E-mail alerts related to this article or journal.Sign up to receive free email-alerts

Subscriptions

Reprints and

[email protected] at

To order reprints of this article or to subscribe to the journal, contact the AACR Publications

Permissions

Rightslink site. (CCC)Click on "Request Permissions" which will take you to the Copyright Clearance Center's

.http://clincancerres.aacrjournals.org/content/11/2/473To request permission to re-use all or part of this article, use this link



http://clincancerres.aacrjournals.org/content/11/2/473.full#ref-list-1

http://clincancerres.aacrjournals.org/content/11/2/473.full#related-urls

http://clincancerres.aacrjournals.org/cgi/alerts

mailto:[email protected]



identification of gastric cancer–related genes using a cdna … · identification of gastric...

Documents