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SONG Shangjin, GU You, WANG Yichao, YUE Xiaoqiang. Bioinformatics Analysis of Gastric Intestinal Metaplasia-related Genes and Pathways Based on GEO Database[J]. Cancer Research on Prevention and Treatment, 2018, 45(10): 768-774. DOI: 10.3971/j.issn.1000-8578.2018.17.1651
Citation: SONG Shangjin, GU You, WANG Yichao, YUE Xiaoqiang. Bioinformatics Analysis of Gastric Intestinal Metaplasia-related Genes and Pathways Based on GEO Database[J]. Cancer Research on Prevention and Treatment, 2018, 45(10): 768-774. DOI: 10.3971/j.issn.1000-8578.2018.17.1651

Bioinformatics Analysis of Gastric Intestinal Metaplasia-related Genes and Pathways Based on GEO Database

  • Objective To investigate the related genes and potential mechanism in the course of gastric intestinal metaplasia and confirm whether these differential genes continusously function in the development of gastric cancer.
    Methods The microarray data of gene expression profile sets containing normal and intestinal gastric mucosa tissue were searched in Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) of each set of gene expression profile and key gene shared by all sets were identified by GEO2R analysis. Every differentially expressed gene were analyzed to identify the related pathways in gastric intestinal metaplasia by Gene Oncology (GO) and KEGG pathway based on the Database for Annotation Visualization and Integrated Discovery (DAVID) program. The expression distinction of all key genes in gastric cancer tissues and normal gastric tissues was assessed based on The Cancer Genome Altas (TCGA) dataset. And the correlation between key genes and prognosis of gastric cancer patients was calculated by KM plotter analysis.
    Results A total of three microarray datasets involved in intestinal metaplasia of normal gastric mucosa were identified in GEO database. The GEO2R analysis targeted 1188 DEGs and nine key genes (ALDOB, CLCA1, CLDN7, DMBT1, KRT20, MTTP, OLFM4, REG3A and TFF3). The GO and KEGG analysis implied that the functions of DEGs were closely related with digestion and absorption of nutrition, hydrolysis and synthesis of proteins, and xenobiotic metabolic process. The TCGA dataset analysis showed that all the nine key genes had significantly different expression in gastric cancer tissues when compared with normal gastric tissues, and the KM plotter analysis confirmed their correlation with the prognosis of gastric cancer patients.
    Conclusion This study identifies the potential differentially expressed genes and related pathways that play important roles in the course of gastric intestinal metaplasia from normal to gastric cancer, and confirms their correlation with clinical prognosis.
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