Objective: To investigate the predictive indicators and therapeutic targets of gastric cancer using bioinformatics approach and analyze the relations of them with prognosis.
Methods: Three microarray datasets (GSE13911, GSE33651, GSE79973) were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes between gastric cancer samples and normal tissue samples were screened using GEO2R tools. The functional and pathway annotations of the differentially expressed genes were performed by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Meanwhile, the protein-protein interaction network (PPI) was constructed using STRING and Cytoscape to pick up the hub genes, and the relations of the hub genes with prognosis were analyzed using the Kaplan-Meier plotter database. 
Results: A total of 135 differentially expressed genes were screened, of which 68 were up-regulated and 67 were down-regulated. GO analysis showed that the differentially expressed genes were mainly enriched in biological processes such as signal transduction, calcium ion binding and extracellular exosomes. KEGG analysis revealed that the major enriched pathways of the differentially expressed genes included PI3K/Akt signaling pathways, ECM receptor interactions and focal adhesions. PPI analysis showed that COL1A1, COL1A2, COL4A1, FN1, THBS1, CD44, COL2A1, COL4A2, CXCL8, COL5A1 were the hub genes. Survival analysis showed that except the up-regulation of THBS1, the abnormal expressions of other hub genes were significantly associated with the overall survival of the gastric cancer patients. 
Conclusion: The abnormal expressions of the screened hub genes may be involved in the development and progression of gastric cancer, and could be closely related to the prognosis of gastric cancer patients. These genes may serve as potential predictors and therapeutic targets for further research of gastric cancer.