Gastric Cancer Open Access
Copyright ©2005 Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Apr 28, 2005; 11(16): 2390-2397
Published online Apr 28, 2005. doi: 10.3748/wjg.v11.i16.2390
Gene expression profile differences in gastric cancer, pericancerous epithelium and normal gastric mucosa by gene chip
Chuan-Ding Yu, Shen-Hua Xu, Hang-Zhou Mou, Zhi-Ming Jiang, Chi-Hong Zhu, Xiang-Lin Liu, Zhejiang Cancer Research Institute, Hangzhou 310022, Zhejiang Province, China
Author contributions: All authors contributed equally to the work.
Correspondence to: Dr. Chuan-Ding Yu, Zhejiang Cancer Research Institute, No. 38 Guangji Road, Hangzhou 310022, Zhejiang Province, China. yuchuanding@hotmail.com
Telephone: +86-571-88122588 Fax: +86-571-88122508
Received: April 28, 2004
Revised: April 29, 2004
Accepted: June 28, 2004
Published online: April 28, 2005

Abstract

AIM: To study the difference of gene expression in gastric cancer (T), pericancerous epithelium (P) and normal tissue of gastric mucosa (C), and to screen an associated novel gene in early gastric carcinogenesis by oligonucleotide microarray.

METHODS: U133A (Affymetrix, Santa Clara, CA) gene chip was used to detect the gene expression profile difference in T, P and C, respectively. Bioinformatics was used to analyze the detected results.

RESULTS: When gastric cancer was compared with normal gastric mucosa, 766 genes were found, with a difference of more than four times in expression levels. Of the 766 genes, 530 were up-regulated (Signal Log Ratio [SLR]>2), and 236 were down-regulated (SLR<-2). When pericancerous epithelium was compared with normal gastric mucosa, 64 genes were found, with a difference of more than four times in expression levels. Of the 64 genes, 50 were up-regulated (SLR>2), and 14 were down-regulated (SLR<-2). Compared with normal gastric mucosa, a total of 143 genes with a difference in expression levels (more than four times, either in cancer or in pericancerous epithelium) were found in gastric cancer (T) and pericancerous epithelium (P). Of the 143 genes, 108 were up-regulated (SLR>2), and 35 were down-regulated (SLR<-2).

CONCLUSION: To apply a gene chip could find 143 genes associated with the genes of gastric cancer in pericancerous epithelium, although there were no pathological changes in the tissue slices. More interesting, six genes of pericancerous epithelium were up-regulated in comparison with genes of gastric cancer and three genes were down-regulated in comparison with genes of gastric cancer. It is suggested that these genes may be related to the carcinogenesis and development of early gastric cancer.

Key Words: Gastric cancer; Pericancerous epithelium; Gene expression profile; Gene chip



INTRODUCTION

Differentially expressed genes from different specimens may be detected with parallel analysis by gene chips. This technique possesses many advantages, of which the greatest is to improve traditional experiments by allowing a single or several gene expression differences to be observed in a single test. More and more cDNA microarray methods are applied in the study of gene expression. In the paper, a gene chip technique was used to analyze the different gene expression patterns in gastric cancer, its pericancerous epithelium tissue and normal tissue of gastric mucosa. Exploring tumor-associated gene-clusters and their role in the process of carcinogenesis and development of gastric cancer is helpful in gaining a comprehensive understanding of the molecular mechanisms in cell transformation. This may also provide molecular markers and target genes for clinical diagnosis and prevention, and treatment of gastric cancer.

MATERIALS AND METHODS
Materials

Gastric cancer tissues and pericancerous epithelial tissues as well as normal gastric mucosa tissues were obtained from five patients who underwent gastrectomy at our hospital. For each specimen one part was immediately snap-frozen in liquid nitrogen and the other was used for histopathological examination to ensure all the pericancerous and control gastric mucosa without cancer cells but with their corresponding histological appearance. The clinical and pathological data of these patients are shown in Table 1.

Table 1 Clinical and pathological data of five patients with gastric cancer.
Number of In-PNameSexAge (yr)Pathological diagnosisLymph metastasisClinical stage
113702JiangF45Lesser curvature of stomach invasion ulcer type moderate differentiation adenocarcinoma invasion serosa1/35III
123730XuM48Anterior wall in body of stomach moderate differentiation adenocarcinoma invasion muscular layers and nerve1/17III
123673TangF57Lesser curvature in cardia of stomach invasion ulcer type moderate differentiation adenocarcinoma invasion serosa1/14III
123808YuF49Anterior wall in cardia of stomach poor-moderate differentiation adenocarcinoma, a part of mucinous adenocarcinoma and esophagus of extremities inferior0/35II
123733HuangM60Cardia of stomach node type moderate differentiation adenocarcinoma invasion muscular layer esophagus5/22III
Oligonucleotide microarray gene chip

Human full-length genome U133A (Affymetrix, Santa Clara, CA) contained about 18000 full-length genes from the unigene GenBank.

Sample preparation

Total RNA was extracted by a single step method[1]. Briefly, after T, P and C tissues were taken out from liquid nitrogen, specimens were ground completely into tiny powders while liquid nitrogen was added into a ceramic mortar. TRIzol was used to extract total RNA. A QIAGEN reagent kit was used to purify the total RNA. A spectrophotometer was used to calculate the total RNA concentration on the basis of optical density of A260. Total RNA was taken out from the T, P and C tissues and mixed, respectively. T7-(dT)24 was made for a primer, the first strand of cDNA was synthesized through retro-transcription on the base of the first strand as a template to synthesize the second strand. After the double stranded DNA was purified, a high yield RNA transcript labeling kit was used to transcribe synthetic cRNA directly. Then the transcribed cRNA was purified and treated at high temperature to produce fragments of 35-200 bp cRNA.

Hybridization and washing

The fragments of cRNA were mixed with other control agents to prepare a hybridization solution, the hybridization solution was injected into the chip. The three chips (T, P, C) were put into the hybridization oven (640 type) for 16 h to finish the hybridization procedure. The chips were taken out from the hybridization oven to recover the hybridization solution, then each composition elution and staining were automatically completed in the Fluidics Station 400.

Fluorescence scanning and result analysis

The chip was scanned with a GeneChip scanner. The intensity value of a fluorescent signal was obtained by expressing those genes. An internal reference gene (housekeeping gene) was chosen in advance. With regard to the primary signals, data were normalized and corrected. The acquired image was analyzed by Microarray suit software using a digital computer, and the intensity of fluorescence signals and its ratio were calculated.

RESULTS
Quantity judgment of the test chip

Each scanning profile was shown after hybridization with the test chip (Figure 1). A clearly printed character “GeneChip test” was on the upper of the profile. A lot of spots and well-distributed lines were around the profile. Some spots were on the four corners and the character “+” was clear. There was a good quantity between the gene chip and the samples of RNA. So this was a complete and reliable result of the detecting gene chip. Then, the samples from three groups were hybridized with U133A gene chip and scanned, respectively.

Figure 1
Figure 1 Control cRNA vs test chip post-hybridization.
Hybridization result of the sample chip

A scanning profile was obtained from the samples of three groups after being hybridized with U133A gene chip (Figure 2). The scatter plots are shown in Figure 3.

Figure 2
Figure 2 Hybridization results of the sample chip of scanning results. A: Post-hybridization of scanning results in control cRNA vs U133A chip; B: Post-hybridization of scanning results in gastric cancer group cRNA vs U133A chip; C: Post-hybridization of scanning results in pericancerous group cRNA vs U133A chip.
Figure 3
Figure 3 Scatter plots in gastric cancer and pericancerous tissues A: Scatter plots in gastric cancer tissue vs control B: Scatter plots in pericancerous tissue vs control.

Bioinformatics was used to detect and analyze the number of differentially expressed genes in gastric cancer (T) or pericancerous tissues (P). The results were compared to the normal gastric mucosa as shown in Table 2.

Table 2 Differentially expressed gene number in T, P and C.
Numbers of genesUp-regulated
Down-regulated
SLR>2SLR>3SLR <-2SLR <-3
T vs C530157236113
P vs C5017147
T and P vs C108213517

Although there were no pathological changes in the tissue slices, 143 genes were found. More interesting, six genes of pericancerous epithelium were up-regulated compared to gastric cancer and three genes were down-regulated compared to gastric cancer. Their functions were related to the activity of a number of factors such as lipid transporter factor, electron transporter, receptor of signal protein, growth factor, ATP dependent RNA helicase (Table 3).

Table 3 Up-regulated and down-regulated genes.
Probe Set IDT vs C SLRP vs C SLRNameGO molecular function
202580-x-at22.4Forkhead box M1GO:3702; RNA polymerase II transcription factor activity; traceable author statement
GO:3700; transcription factor activity; traceable author statement
203098-at2.32.4Chromodomain protein, Y chromosome-likeGO:3682; chromatin binding; inferred from electronic annotation
GO:3824; enzyme activity; inferred from electronic annotation
203334-at3.13.8DEAD/H (Asp-Glu-Ala-Asp/His)GO:3723; RNA binding; inferred from electronic annotation box polypeptide 8 (RNA helicase)
GO:8248; pre-mRNA splicing factor activity; traceable author statement
GO:5524; ATP binding; inferred from electronic annotation
GO:4004; ATP dependent RNA helicase activity; traceable author statement
208152-s-at1.92.1DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 21GO:3723; RNA binding; inferred from electronic annotation
GO:5524; ATP binding; inferred from electronic annotation
GO:4004; ATP dependent RNA helicase activity; traceable authorstatemen
209820-s-at2.22.3Transducin (beta)-like 3GO:5057; receptor signaling protein activity; predicted/computed
217173-s-at3.43.6Low density lipoprotein receptor (familial hypercholesterolemia)GO:5041; low-density lipoprotein receptor activity; traceable author statement
GO:5509; calcium ion binding; inferred from electronic annotation
GO:8034; lipoprotein binding; traceable author statement
GO:5319; lipid transporter activity; inferred from electronic
207102-at-2.4-3.6Aldo-keto reductase family 1, member D1 (delta 4-3-ketosteroid-5-beta-reductase)GO:5489; electron transporter activity; experimental evidence
208580-x-at-2.7-3H4 histone family, member E (H4FE)Unknown
218730-s-at-2.5-3.3Osteoglycin (osteoinductive factor, mimecan)GO:8083; growth factor activity; inferred from electronic annotation

T and P were compared with C. The gene molecular function of a simultaneous expression difference belonged to nucleic acid binding activity (including RNA, DNA), protein binding activity (calcium, growth factor, cellular skeleton), enzyme activity. The functions of 34 genes were unknown (Table 4).

Table 4 Comparison between gene molecular functions of T, P and C.
Molecular functionUp-regulated (SLR> 2)Down-regulated (SLR <-2)
Enzyme activity154
Enzyme regular activity40
Structural molecule activity31
Transcription factor activity30
Nucleic acid binding (RNA, DNA)165
Protein binding activity (Ca , GF, cell skeleton)147
Carbohydrate binding activity30
Metal ion binding activity10
Signal transduction activity (receptor, GF)73
Sport activity21
Transporter activity (electron, ion, protein)76
Tumor antigen20
Tumor suppressor30
Apoptosis suppressor10
Fibrinogen01
Unknown277
Total10835

Genes with a difference of more than eight times are listed in Tables 5 and 6.

Table 5 Comparison between molecular functions of 21 genes in T, P and C.
Probe Set IDT vs C SLRP vs C SLRNameGO molecular function
201655-s-at3.12.6Heparan sulfateGO:5198; structural molecule activity; inferred from electronic annotation
proteoglycan 2 (perlecan)GO:5206; heparin sulfate proteoglycan; traceable author statement
201890-at3.11.6Ribonucleotide reductaseGO:4748; ribonucleoside-diphosphate reductase activity;non-traceable
M2 polypeptideauthor statement
GO:16491; oxidoreductase activity; inferred from electronic annotation
201926-s-at3.11Decay accelerating factor for complement (CD55, Cromer blood group system)Unknown
203334-at3.13.8DEAD/H (Asp-Glu-Ala—Asp/His) box polypeptide 8(RNA helicase)GO:3723; RNA binding; inferred from electronic annotation
GO:8248; pre-mRNA splicing factor activity; traceable author statement
GO:5524; ATP binding;inferred from electronic annotation
GO:4004; ATP dependent RNA helicase activity; traceable author statement
202870-s-at3.31.5CDC20 cell division cycle 20 homolog (S. cerevisiae)Unknown
209035-at3.31.6Midkine (neurite growth- promoting factor 2)GO:8201; heparin binding; not recorded
GO:8083; growth factor activity; not recorded
GO:5125; cytokine activity; not recorded
209803-s-at3.41.8Tumor suppressing subtransferable candidate 3Unknown
212444-at3.41.2Homo sapiens, clone IMAGE:4471726, mRNAUnknown
217173-s-at3.43.6Low density lipoprotein receptor (familial hypercholesterolemia)GO:5041; low-density lipoprotein receptor activity; traceable author statement
GO:5509; calcium ion binding; inferred from electronic annotation
GO:8034; lipoprotein binding; traceable author statement
GO:5319; lipid transporter activity; inferred from electronic
217221-x-at3.52.2RNA binding motif protein 10GO:3676; rrm; nucleic acid binding activity; 8.4e-05; extended: inferred from electronic annotation
GO:3676; rrm; nucleic acid binding activity; 0.76; extended: inferred from electronic annotation
202855-s-at3.61.2Solute carrier family 16 (monocarboxylic acid transporters), member 3GO:8028; monocarboxylic acid transporter activity; traceable author statement
GO:15355; monocarboxylate porter activity; inferred from electronic annotation
GO:15293; symporter activity; inferred from electronic annotation
203559-s-at3.61.2Amiloride binding protein 1(amine oxidase (copper-containing))GO:8144; drug binding;not recorded
GO:8201; heparin binding; inferred from electronic annotation
GO:8122; amine oxidase (copper-containing) activity; inferred from electronic annotation
GO:16491; oxidoreductase activity; inferred from electronic annotation
209373-at3.81.6BENE proteinUnknown
203108-at4.21.5Retinoic acid induced 3GO:8067; metabotropic glutamate, GABA-B-like receptor activity; inferred from electronic annotation
GO:4872; receptor activity; inferred from electronic annotation
202067-s-at4.53.8Low density lipoprotein receptor (familial hypercholesterolemia)GO:5041; low-density lipoprotein receptor activity; traceable author statement
GO:5509; calcium ion binding; inferred from electronic annotation
GO:8034; lipoprotein binding; traceable author statement
GO:5319; lipid transporter activity; inferred from electronic
218900-at4.53.7Cyclin M4Unknown
201884-at4.62.1Carcinoembryonic antigen-related cell adhesion molecule 5GO:8222; tumor antigen; traceable author statement
211657-at5.92.1Carcinoembryonic antigen- related cell adhesion molecule 6GO:8222; tumor antigen; traceable author statement
212768-s-at4.71.3Differentially expressed in hematopoietic lineagesUnknown
208250-s-at6.31.7Deleted in malignant brain tumors 1GO:8181; tumor suppressor; predicted/computed
GO:5044; SRCR; scavenger receptor activity; 3.7e-42;extended: unknown
204855-at7.74.2Serine (or cysteine) proteinase inhibitor, clade B (ovalbumin) member 5GO:4868; serpin; not recorded GO:4867; serine protease nhibitor activity; inferred from electronic annotation
GO:8181; tumor suppressor; traceable author statement serp
Table 6 Comparison between molecular functions of 17 genes in T, P and C.
Probe Set IDT vs C SLRP vs C SLRNameGO molecular function
207102-at-2.4-3.6Aldo-keto reductase family 1, member D1 (delta 4-3-ketosteroid-5- beta-reductase)GO:5489; electron transporter activity; experimental evidence
218730-s-at-2.5-3.3Osteoglycin (osteoinductive factor, mimecan)GO:8083; growth factor activity; inferred from electronic annotation
204940-at-3.3-1.3PhospholambanGO:42030; ATPase inhibitor activity; inferred from electronic annotation
GO:5246; calcium channel regulator activity; not recorded
208281-x-at-3.3-1.1Deleted in azoospermia 3GO:3676; nucleic acid binding; inferred from electronic annotation
216351-x-at-3.3-1.6Deleted in azoospermia 4Unknown
209894-at-3.7-1.5Leptin receptorGO:4896; hematopoietin/interferon-class (D200-domain) cytokine receptor activity; inferred from electronic annotation
214723-x-at-3.7-1.5KIAA1641 proteinUnknown
208282-x-at-4.3-1.2Deleted in azoospermia 2GO:3676; nucleic acid binding; inferred from electronic annotation
219564-at-4.3-1.2Potassium inwardly- rectifying channel, subfamily J, member 16GO:5242; inward rectifier potassium channel activity; inferred from electronic annotation
GO:5244; voltage-gated ion channel activity; inferred from electronic annotation
GO:5267; potassium channel activity; inferred from electronic annotation
203571-s-at-4.8-1.6Adipose specific 2Unknown
218087-s-at-5-1.3Sorbin and SH3 domain containing 1GO:8092; cytoskeletal protein binding; experimental evidence
GO:3779; actin binding; experimental evidence
207909-x-at-5.2-1.2Deleted in azoospermiaGO:3676; rrm; nucleic acid binding activity; 4.3e-10; extended: inferred from electronic annotation
GO:3723; RNA binding; predicted/computed
213071-at-5.3-1.3DermatopontinGO:5515; protein binding; traceable author statement
GO:5194; cell adhesion molecule activity; inferred from electronic annotation
201497-x-at-5.4-1Myosin, heavy polypeptide 11, smooth muscleGO:3779; actin binding; inferred from electronic annotation
GO:5516; calmodulin binding; inferred from electronic annotatio
GO:5524; ATP binding; inferred from electronic annotation
GO:3774; motor activity; inferred from electronic annotation
207912-s-at-5.9-1.3Deleted in azoospermiaGO:3676; rrm; nucleic acid binding activity; 4.3e-10;extended:inferred from electronic annotation
GO:3723; RNA binding;predicted/computed
220630-s-at-6.3-1.8Eosinophil chemotactic cytokineGO:16787; Glyco_hydro_18; hydrolase activity; 2.7e-81; extended:Unknown
GO:16798; hydrolase activity, acting on glycosyl bonds;inferred from electronic annotation
GO:8061; chitin binding;inferred from electronic annotation
GO:8843; endochitinase activity; inferred from electronic annotation
209612-s-at-6.9-1.4Alcohol dehydrogenase IB (class I), beta polypeptideGO:4024; alcohol dehydrogenase activity, zinc-dependent;traceable author statement
GO:4327; 1.2.1.1; formaldehyde dehydrogenase (glutathione) activity; 3.69e-120; extended: inferred from electronic annotation
GO:4023; alcohol dehydrogenase activity, metal ion- independent; inferred from electronic annotation
GO:4025; alcohol dehydrogenase activity, iron-dependent;inferred from electronic annotation
GO:8270; zinc ion binding; traceable author statement
GO:4552; 1.1.1.73; octanol dehydrogenase activity; 4.76e-120; extended: non-traceable author statement
GO:16491; oxidoreductase activity; inferred from electronic annotation
GO: 5489; electron transporter activity; traceable author statement
DISCUSSION

Gastric cancer is one of the most common malignant tumors in China. At present, its treatment has been greatly improved, but it still is one of the principal diseases to seriously hurt people’s health. To explore its etiology and to seek the ideal and early molecular markers, and to develop a new method of gene therapy are a new direction against cancers. Carcinogenesis is a series of molecular changes caused by abnormal expression of tumor-associated genes or inactivation of tumor suppression genes. The gene chip has been widely used to detect gene expression differences in various specimens by parallel analysis. The largest advantage of this technique is that it changes the traditional experiment where only a single or several gene expression differences could be observed in one procedure. Therefore, more and more cDNA microarrays have been applied to the study of gene expression. For example, gene chip was used to study the relationship between Helicobacter pylori and gastric malignancy[2-6], to research the multidrug-resistance to chemotherapy[7-9], to establish carcinogensis models of gastric carcinoma[10], to find gastric cancer and its metastasis associated genes[11-14], to analyse gastric carcinoma and its prognosis and to compare gastric carcinoma with its normal gastric mucosa[15-29].

We used the oligonucleotide of gene chip technique to analyze the gene expression profile difference in gastric cancer, pericancerous epithelium and normal mucosa. When gastric cancer was compared with normal gastric mucosa, a total of 766 genes were found with a difference of more than four times in expression levels. Of the 766 genes, 530 were up-regulated (SLR>2), and 236 were down-regulated (SLR>-2), suggesting that these genes are associated with the occurrence and development of gastric cancer. When pericancerous epithelium was compared with normal gastric mucosa, a total of 64 genes were found, with a difference of more than four times in expression levels. Of the 64 genes, 50 were up-regulated (SLR>2) and 14 were down-regulated (SLR>-2). Compared with normal gastric mucosa, a total of 143 genes with a difference in expression levels (more than four times, either in cancer or in pericancerous epithelium) were found in gastric cancer (T) and pericancerous epithelium (P). Of the 143 genes, 108 were up-regulated (SLR>2) and 35 were down-regulated (SLR>-2). Although an abnormal appearance of pericancerous epithelium was not found in pathological examination, but the 143 genes were shown to have differences in gene expression levels. A more interesting finding was that six genes of pericancerous epithelium were up-regulated compared to gastric cancer and three genes were down-regulated compared to gastric cancer. All but one gene’s function was unknown, the function of other genes was related to the transporter activity of lipid and electrons, transcription factor activity, growth factor activity and ATP dependent RNA helicase activity, suggesting that these genes are probably related to the promotion and progression of carcinogensis at the early stage of gastric cancer. To seek for the expression products of these genes would be very useful in early diagnosis of gastric cancer.

CEA is a soluble glycoprotein with a complex structure. Its molecular weight is about 200000, CEA presents in gastrointestinal tract, pancreas and liver at embryonic development stage, and would increase in gastrointestinal malignant tumors. In other tumors such as breast and lung cancer, it was increased in the serum. Therefore, CEA is a broad-spectrum tumor marker, although it does not act as a specific marker for some malignant tumors, but it still has an important clinical value in differential diagnosis. In the present study, we found that CEA associated cell adhesion molecule 5 (CAM-5) (SLR cancer was 4.6, pericancerous epithelium was 2.1) and CAM-6 (SLR cancer was 5.6, pericancerous epithelium was 2.1) were up-regulated. Sakakura[12] reported that CEA gene expression was up-regulated in metastatic gastric cancer. Oue reported that CEA CAM-6 gene expression was up-regulated in 50% patients with gastric cancer, suggesting that carcino-embryonic antigen associated genes are up-regulated to produce a soluble glycoprotein which could secrete into the blood, increasing the amount of CEA in serum. It could be a molecular mechanism of CEA appearance in serum of patients with gastric cancer. It is a useful tumor marker for gastric cancer.

Na+/K+-ATPase widely distributed on cell membranes is a key enzyme for keeping Na+, K+ ion gradients of cells. Such an enzyme not only attends the ion and protein translocation and keeps the ion self-balance of stabilization, but also has an important role in embryogenesis of vertebrate, neuronal recognition, development of central nervous system, cell morphogenesis, cell adhesion, etc. Lee[24] reported that Na+/K+-ATPase expression levels were up-regulated in intestinal type of gastric cancer. In our study, ATPase, Na+/K+ transporting, alpha 1 polypeptide were found (SLR cancer was 2.4, pericancerous was 1.4).

Alcohol dehydrogenase and aldehyde dehydrogenase are two key enzymes in ethanol metabolism and its metabolic products. Aldehyde dehydrogenase and its gene polymorphism (aldehyde dehydrogenase) are related to liver cancer, gastric cancer and esophageal cancer. Abe[10] reported that aldehyde dehydrogenase expression level was obviously down-regulated in tissues of gastric cancer. In the present study, we also found that alcohol dehydrogenase IB expression levels were obviously down-regulated (SLR cancer was-6.9, pericancerous was-1.4).

Serine protein kinase takes part in translocation and localization, as well as signal transfer of cells. Oien[20] reported that serine protein kinase expression levels were obviously up-regulated in human gastric cancer tissues. In the present study, we also found that serine protein kinase inhibitor expression level was obviously up-regulated (SLR cancer was 7.7, pericancerous was 4.2).

It has been demonstrated that the activity of topoisomerase II (Topo II) was rapidly increased in proliferating cells from S phase to G2/M phase, suggesting that this enzyme activity might be related to the malignant transformation of tumor cells. So Topo II expression levels (high or low) might be a parameters for cell proliferation. It also could be used as a marker for judging the sensitivity and tolerance of antitumor drugs. Varis et al[30], reported that Topo II expression level was obviously up-regulated in human gastric cancer tissues. Skotheim[31] reported that Topo II expression level was obviously up-regulated in malignant peripheral nerve sheath tumors. In our study the Topo II expression was also up-regulated in gastric cancer and pericancerous epithelium (SLR cancer was 2.3, pericancerous was 1.4). It might be related to a degree of malignancy and resistance. In the present study, we found that the cell cycle protein M4 (SLR cancer was 4.5, pericancerous was 3.7) was highly expressed. It might indicate that tumor cells had a high proliferation ratio.

In our study, the expression of E-cadherin (SLR cancer was 2.3, pericancerous was 1.8) and integrin β 4 (SLR cancer was 2.7, pericancerous was 2.0) was significantly increased in gastric cancer as reported by Mori et al[16], Hippo et al[25] and Oue et al[34].

Cell skeleton tissues and formation of external matrix of cells play an important role in the invasion of tumors. In the present study we found a number of genes were involved in cell skeleton and matrix such as keratin protein 19 (SLR cancer was 2.5, pericancerous was 1.6), microtubule protein β 4 (SLR cancer was 2.4, pericancerous was 1.4), microtubule protein β 2 (SLR cancer was 2.1, pericancerous was 1.4), reticuloprotein 1, and interzonal fiber binding protein 500 ku (SLR cancer was 2.1, pericancerous was 1.8). Bae et al[32] reported that cell skeleton protein was up-regulated in gastric cancer. Inhibitor 3 of proteins belongs to external matrix of cells (SLR cancer was 2.3, pericancerous was 1.7). Wang et al[33] reported that external matrix of gastric cancer cells was up-regulated. We found that 4/5 patients had a lymph-node metastasis, and related metastatic genes had a higher expression, further suggesting that the overexpression of cell skeleton tissues and external matrix is associated with tumor invasion and metastasis.

The application of gene chip technique is a revolution in life science. This kind of study models will produce a great effect on researches in life science. Gene chip might provide a new direction for diagnosis, therapy and prevention of human gastric carcinoma.

Footnotes

Co-first-authors: Chuan-Ding Yu and Shen-Hua Xu

References
1.  Peng XL, Yuan HY, Xie Y, Wang HH. Experimental technique of gene engineering. Huna Science Technique Issue Agency Second. 1998;197-199.  [PubMed]  [DOI]  [Cited in This Article: ]
2.  Yoshida N, Ishikawa T, Ichiishi E, Yoshida Y, Hanashiro K, Kuchide M, Uchiyama K, Kokura S, Ichikawa H, Naito Y. The effect of rebamipide on Helicobacter pylori extract-mediated changes of gene expression in gastric epithelial cells. Aliment Pharmacol Ther. 2003;18 Suppl 1:63-75.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 10]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
3.  Nardone G, Morgner A. Helicobacter pylori and gastric malignancies. Helicobacter. 2003;8 Suppl 1:44-52.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 27]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
4.  Nilsson C, Sillén A, Eriksson L, Strand ML, Enroth H, Normark S, Falk P, Engstrand L. Correlation between cag pathogenicity island composition and Helicobacter pylori-associated gastroduodenal disease. Infect Immun. 2003;71:6573-6581.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 88]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
5.  Sepulveda AR, Tao H, Carloni E, Sepulveda J, Graham DY, Peterson LE. Screening of gene expression profiles in gastric epithelial cells induced by Helicobacter pylori using microarray analysis. Aliment Pharmacol Ther. 2002;16 Suppl 2:145-157.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 66]  [Cited by in F6Publishing: 73]  [Article Influence: 3.3]  [Reference Citation Analysis (0)]
6.  Maeda S, Otsuka M, Hirata Y, Mitsuno Y, Yoshida H, Shiratori Y, Masuho Y, Muramatsu M, Seki N, Omata M. cDNA microarray analysis of Helicobacter pylori-mediated alteration of gene expression in gastric cancer cells. Biochem Biophys Res Commun. 2001;284:443-449.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 70]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
7.  Kang HC, Kim IJ, Park JH, Shin Y, Ku JL, Jung MS, Yoo BC, Kim HK, Park JG. Identification of genes with differential expression in acquired drug-resistant gastric cancer cells using high-density oligonucleotide microarrays. Clin Cancer Res. 2004;10:272-284.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 140]  [Cited by in F6Publishing: 150]  [Article Influence: 7.5]  [Reference Citation Analysis (0)]
8.  Suganuma K, Kubota T, Saikawa Y, Abe S, Otani Y, Furukawa T, Kumai K, Hasegawa H, Watanabe M, Kitajima M. Possible chemoresistance-related genes for gastric cancer detected by cDNA microarray. Cancer Sci. 2003;94:355-359.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 49]  [Cited by in F6Publishing: 50]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
9.  Ludwig A, Dietel M, Lage H. Identification of differentially expressed genes in classical and atypical multidrug-resistant gastric carcinoma cells. Anticancer Res. 2002;22:3213-3221.  [PubMed]  [DOI]  [Cited in This Article: ]
10.  Abe M, Yamashita S, Kuramoto T, Hirayama Y, Tsukamoto T, Ohta T, Tatematsu M, Ohki M, Takato T, Sugimura T. Global expression analysis of N-methyl-N'-nitro-N-nitrosoguanidine-induced rat stomach carcinomas using oligonucleotide microarrays. Carcinogenesis. 2003;24:861-867.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 32]  [Cited by in F6Publishing: 34]  [Article Influence: 1.6]  [Reference Citation Analysis (0)]
11.  Weiss MM, Kuipers EJ, Postma C, Snijders AM, Siccama I, Pinkel D, Westerga J, Meuwissen SG, Albertson DG, Meijer GA. Genomic profiling of gastric cancer predicts lymph node status and survival. Oncogene. 2003;22:1872-1879.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 86]  [Cited by in F6Publishing: 92]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
12.  Sakakura C, Simomura K, Shuichi K, Nakase Y, Fukuda K, Takagi T, Hagiwara A, Ichikawa Y, Nishizuka I, Ishikawa T. Screening of novel biomarkers for the detection of intraperitoneally disseminated cancer cells using human cDNA microarray. Gan To Kagaku Ryoho. 2002;29:2271-2274.  [PubMed]  [DOI]  [Cited in This Article: ]
13.  Wang JH, Chen SS. Screening and identification of gastric adenocarcinoma metastasis-related genes by using cDNA microarray coupled to FDD-PCR. ShengWu HuaXue Yu ShengWu WuLi XueBao (Shanghai). 2002;34:475-481.  [PubMed]  [DOI]  [Cited in This Article: ]
14.  Hippo Y, Yashiro M, Ishii M, Taniguchi H, Tsutsumi S, Hirakawa K, Kodama T, Aburatani H. Differential gene expression profiles of scirrhous gastric cancer cells with high metastatic potential to peritoneum or lymph nodes. Cancer Res. 2001;61:889-895.  [PubMed]  [DOI]  [Cited in This Article: ]
15.  Meireles SI, Carvalho AF, Hirata R, Montagnini AL, Martins WK, Runza FB, Stolf BS, Termini L, Neto CE, Silva RL. Differentially expressed genes in gastric tumors identified by cDNA array. Cancer Lett. 2003;190:199-211.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 23]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
16.  Mori M, Mimori K, Yoshikawa Y, Shibuta K, Utsunomiya T, Sadanaga N, Tanaka F, Matsuyama A, Inoue H, Sugimachi K. Analysis of the gene-expression profile regarding the progression of human gastric carcinoma. Surgery. 2002;131:S39-S47.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 56]  [Cited by in F6Publishing: 62]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
17.  Hasegawa S, Furukawa Y, Li M, Satoh S, Kato T, Watanabe T, Katagiri T, Tsunoda T, Yamaoka Y, Nakamura Y. Genome-wide analysis of gene expression in intestinal-type gastric cancers using a complementary DNA microarray representing 23,040 genes. Cancer Res. 2002;62:7012-7017.  [PubMed]  [DOI]  [Cited in This Article: ]
18.  Inoue H, Matsuyama A, Mimori K, Ueo H, Mori M. Prognostic score of gastric cancer determined by cDNA microarray. Clin Cancer Res. 2002;8:3475-3479.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  Ji J, Chen X, Leung SY, Chi JT, Chu KM, Yuen ST, Li R, Chan AS, Li J, Dunphy N. Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines. Oncogene. 2002;21:6549-6556.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 51]  [Cited by in F6Publishing: 52]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
20.  Oien KA, Vass JK, Downie I, Fullarton G, Keith WN. Profiling, comparison and validation of gene expression in gastric carcinoma and normal stomach. Oncogene. 2003;22:4287-4300.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 54]  [Cited by in F6Publishing: 57]  [Article Influence: 2.7]  [Reference Citation Analysis (0)]
21.  Stephen RL, Crabtree JE, Yoshimura T, Clayton CL, Dixon MF, Robinson PA. Increased zinc finger protein zFOC1 transcripts in gastric cancer compared with normal gastric tissue. Mol Pathol. 2003;56:167-171.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Cited by in F6Publishing: 3]  [Article Influence: 0.1]  [Reference Citation Analysis (0)]
22.  Boussioutas A, Li H, Liu J, Waring P, Lade S, Holloway AJ, Taupin D, Gorringe K, Haviv I, Desmond PV. Distinctive patterns of gene expression in premalignant gastric mucosa and gastric cancer. Cancer Res. 2003;63:2569-2577.  [PubMed]  [DOI]  [Cited in This Article: ]
23.  Askari MD, Miller GH, Vo-Dinh T. Simultaneous detection of the tumor suppressor FHIT gene and protein using the multi-functional biochip. Cancer Detect Prev. 2002;26:331-342.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 11]  [Cited by in F6Publishing: 11]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
24.  Lee S, Baek M, Yang H, Bang YJ, Kim WH, Ha JH, Kim DK, Jeoung DI. Identification of genes differentially expressed between gastric cancers and normal gastric mucosa with cDNA microarrays. Cancer Lett. 2002;184:197-206.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 49]  [Cited by in F6Publishing: 51]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
25.  Hippo Y, Taniguchi H, Tsutsumi S, Machida N, Chong JM, Fukayama M, Kodama T, Aburatani H. Global gene expression analysis of gastric cancer by oligonucleotide microarrays. Cancer Res. 2002;62:233-240.  [PubMed]  [DOI]  [Cited in This Article: ]
26.  El-Rifai W, Frierson HF, Harper JC, Powell SM, Knuutila S. Expression profiling of gastric adenocarcinoma using cDNA array. Int J Cancer. 2001;92:832-838.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 63]  [Cited by in F6Publishing: 66]  [Article Influence: 2.9]  [Reference Citation Analysis (0)]
27.  Kim B, Bang S, Lee S, Kim S, Jung Y, Lee C, Choi K, Lee SG, Lee K, Lee Y. Expression profiling and subtype-specific expression of stomach cancer. Cancer Res. 2003;63:8248-8255.  [PubMed]  [DOI]  [Cited in This Article: ]
28.  Chen X, Leung SY, Yuen ST, Chu KM, Ji J, Li R, Chan AS, Law S, Troyanskaya OG, Wong J. Variation in gene expression patterns in human gastric cancers. Mol Biol Cell. 2003;14:3208-3215.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 224]  [Cited by in F6Publishing: 241]  [Article Influence: 11.5]  [Reference Citation Analysis (0)]
29.  Tay ST, Leong SH, Yu K, Aggarwal A, Tan SY, Lee CH, Wong K, Visvanathan J, Lim D, Wong WK. A combined comparative genomic hybridization and expression microarray analysis of gastric cancer reveals novel molecular subtypes. Cancer Res. 2003;63:3309-3316.  [PubMed]  [DOI]  [Cited in This Article: ]
30.  Varis A, Wolf M, Monni O, Vakkari ML, Kokkola A, Moskaluk C, Frierson H, Powell SM, Knuutila S, Kallioniemi A. Targets of gene amplification and overexpression at 17q in gastric cancer. Cancer Res. 2002;62:2625-2629.  [PubMed]  [DOI]  [Cited in This Article: ]
31.  Skotheim RI, Kallioniemi A, Bjerkhagen B, Mertens F, Brekke HR, Monni O, Mousses S, Mandahl N, Soeter G, Nesland JM. Topoisomerase-II alpha is upregulated in malignant peripheral nerve sheath tumors and associated with clinical outcome. J Clin Oncol. 2003;21:4586-4591.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 51]  [Cited by in F6Publishing: 49]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
32.  Bae CD, Sung YS, Jeon SM, Suh Y, Yang HK, Kim YI, Park KH, Choi J, Ahn G, Park J. Up-regulation of cytoskeletal-associated protein 2 in primary human gastric adenocarcinomas. J Cancer Res Clin Oncol. 2003;129:621-630.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 29]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
33.  Wang YM, Xu SM, Huang QH. Analysis of human gastric cancer associated genes expression by gene chip. J Tongji Univ. 2003;24:932-934.  [PubMed]  [DOI]  [Cited in This Article: ]
34.  Oue N, Hamai Y, Mitani Y, Matsumura S, Oshimo Y, Aung PP, Kuraoka K, Nakayama H, Yasui W. Gene expression profile of gastric carcinoma: identification of genes and tags potentially involved in invasion, metastasis, and carcinogenesis by serial analysis of gene expression. Cancer Res. 2004;64:2397-2405.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 207]  [Cited by in F6Publishing: 224]  [Article Influence: 11.2]  [Reference Citation Analysis (0)]