胃癌基因表达谱芯片差异基因的生物信息学分析

doi:10.3969/j.issn.1004-616x.2019.04.007

Abstract

Abstract: OBJECTIVE:To screen the key genes and signal pathways in the development of gastric cancer and to provide the basis for finding valuable molecular markers of gastric cancer. METHODS:Five gastric cancer gene chip datasets were downloaded from the GEO database:GSE35809,GSE54129,GSE79973,GSE66229,and GSE51105. The samples in the five data sets were combined,the batch effect between the data sets was removed,the combined gene expression data was normalized,and the data standardization was monitored by principal component analysis. The limma package in the R language was used to screen for differentially expressed genes in gastric cancer tissues and normal tissues. The DAVID database was used to analyze the differential genes in the development of gastric cancer,and the interaction network between the differentially encoded proteins was analyzed and visualized by STRING database and Cytoscape. RESULTS:A total of 1205 differential genes were screened,including 480 up-regulated genes and 725 down-regulated genes. The biological functions of differential genes are mainly enriched in cell-cell signaling,regulation of inflammatory responses,cell adhesion,apoptosis,and transmembrane transport of ions. Analysis of KEGG signaling pathway revealed that differential genes are mainly enriched in the p53,PI3K-Akt and NF-κB signaling pathways. The 29 Hub genes such as CENPE,KIF15,MELK,KIF2C,CENPF,KIF11,NUSAP1,UBE2C,TTK,AURKB,DLGAP5,TOP2A were screened by constructing a protein interaction network. CONCLUSION:By combining different data sets,key genes and signal pathways for the development of gastric cancer were screened by bioinformatics method,providing new research targets for the diagnosis and treatment of gastric cancer.

Key words: gastric cancer, bioinformatics analysis, differentially expressed genes, gene chip

CLC Number:

R730.2

ZENG Lei, XU Xuelian, LUO Manman, ZHANG Fan, HAN Zhijian, LI Yumin. Bioinformatics analyses of differential genes in gastric cancer gene expression profiles[J]. Carcinogenesis, Teratogenesis & Mutagenesis, 2019, 31(4): 300-307.

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Bioinformatics analyses of differential genes in gastric cancer gene expression profiles

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