Identification of hub genes and biological characteristics of gastric cancer by multiple-microarray analysis

doi:10.3877/cma.j.issn.1674-0793.2022.01.004

Abstract

Abstract:

Objective

To investigate the potential target genes of gastric cancer and reveal their biological characteristics.

Methods

Gene expression profiles (GSE29272, GSE54129, GSE13911, GSE79973, GSE19826) were obtained from GEO database. Differentially expressed genes were screened out by GEO2R, and the Venn diagram plotted the intersection of five gene expression profiles to obtain common differentially expressed genes. DAVID database was used to analyze the KEGG pathway and GO enrichment analysis of the common differentially expressed genes. The protein-protein interaction (PPI) network diagram of the common differentially expressed genes were obtained through the STRING database and visualize it with Cytoscape software, and used the plug-in in Cytoscape software at the same time CytoHubba screened gastric cancer target genes. The target genes were further verified in the GEPIA database and UALCAN database for their expression and survival analysis. The CMap database predicted its potential targeted small molecule compounds.

Results

The Venn diagram screened 105 common differentially expressed genes, including 57 down-regulated genes and 48 up-regulated genes. The KEGG pathway analysis and GO enrichment analysis in the DAVID database showed that these up-regulated genes were mainly related to extracellular matrix tissues, cell adhesion, focal adhesion, PI3K-Akt signaling pathway, and "ECM-receptor interaction". Eight target genes were screened by Cytoscape software: BGN, SPARC, COL5A2, COL5A1, COL1A2, COL4A1, COL6A3 and COL11A1. After verification in the GEPIA database and UALCAN database, it was confirmed that these eight key genes were related to the occurrence and development of gastric cancer. Survival analysis showed that the high expression of COL4A1 (Log rank P=0.029, HR=1.4) and COL5A2 (Log rank P=0.009 5, HR=1.5) was related to the decrease of survival ability. Analysis of the CMap database showed that pyrrolamide and TTNPB were the most likely to reverse the state of gastric cancer.

Conclusions

BGN, SPARC, COL5A2, COL5A1, COL1A2, COL4A1, COL6A3 and COL11A1 genes may be used as potential targets for improving gastric cancer diagnosis and immunotherapy biomarkers. Pyrrolamide and TTNPB are most likely to be small molecule compounds for the treatment of gastric cancer. These analysis results provide a new direction for the study of the etiology of gastric cancer, and also provide a theoretical basis for in-depth exploration of its pathogenesis.

Key words: Bioinformatics, Gastric neoplasms, Biomarkers, Key genes

Xiangyuan Ding, Siqi Yan, Junjie Liu, Wei Yan. Identification of hub genes and biological characteristics of gastric cancer by multiple-microarray analysis[J]. Chinese Archives of General Surgery(Electronic Edition), 2022, 16(01): 20-26.

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Figures/Tables 6

References 24

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序号	种类	平台	Affymetrix基因芯片	正常	胃癌
1	GSE29272	GPL96	Affymetrix Human Genome U133A Array	134	134
2	GSE54129	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	21	111
3	GSE13911	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	31	38
4	GSE79973	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	10	10
5	GSE19826	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	15	12

序号	种类	平台	Affymetrix基因芯片	正常	胃癌
1	GSE29272	GPL96	Affymetrix Human Genome U133A Array	134	134
2	GSE54129	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	21	111
3	GSE13911	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	31	38
4	GSE79973	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	10	10
5	GSE19826	GPL570	Affymetrix Human Genome U133 Plus 2.0 Array	15	12

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