| Abstract: Gene expression profiles of gastric cancer (GC) were analyzed with bioinformatics tools to identify signature genes associated with prognosis. Four gene expression data sets (accession number: GSE2685, GSE30727, GSE38932 and GSE26253) were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened out using significance analysis of microarrays (SAM) algorithm. P-value 1 were set as the threshold. A co-expression network was constructed for the GC-related genes with package WGCNA of R. Modules were disclosed with WGCNA algorithm. Survival-related signature genes were screened out via COX single-variable regression. A total of 3210 GC-related genes were identified from the 3 data sets. Significantly enriched GO biological process terms included cell death, cell proliferation, apoptosis, response to hormone and phosphorylation. Pathways like viral carcinogenesis, metabolism, EBV viral infection, and PI3K-AKT signaling pathway were significantly over-represented in the DEGs. A gene co-expression network including 2414 genes was constructed, from which 7 modules were revealed. A total of 17 genes were identified as signature genes, such as DAB2, ALDH2, CD58, CITED2, BNIP3L, SLC43A2, FAU and COL5A1.Many signature genes associated with prognosis of GC were identified in present study, some of which have been implicated in the pathogenesis of GC. These findings could not only improve the knowledge about GC, but also provide clues for clinical treatments.
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