Identification of hub genes correlated with the pathogenesis and prognosis of gastric cancer via bioinformatics methods

Abstract

BACKGROUND: Gastric cancer (GC) is the fourth most common cause of cancer-related deaths in the world and 5-year overall survival (OS) rate is less than 10%. So, it is urgent to identified novel diagnostic and prognostic biomarkers. METHODS: Twelve GEO (gene expression omnibus) datasets were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between GC and normal tissues were screened and integrated using limma and RobustRankAggreg (RRA) packages in R software. Protein-protein interaction (PPI) network, GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses for DEGs were conducted via STRING and DAVID, respectively. Moreover, Cox regression model was used to construct a gene prognosis signature. RESULTS: Ten genes (COL1A1, CXCL8, COL3A1, SPP1, COL1A2, TIMP1, CXCL1, BGN, MMP3 and SERPINE1) were identified and might be highly related to GC. Further analysis showed high expression of CXCL8, COL3A1, CXCL1, MMP3 and SERPINE1, were significantly associated with late stage of GC. Lastly, we build a seven-gene prognosis signature (CYP19A1, SERPINE1, CGB5, CALCR, ASGR2, CYTL1 and ABCB5), which can give a good prediction of OS. CONCLUSIONS: Our article screened out key genes highly associating with GC's developments and prognosis, and it is useful for researcher to further understand GC's molecular basis and direct the synthesis medicine of GC.