Identification of hub genes in gastric cancer by integrated bioinformatics analysis

Background: Gastric cancer (GC) is one of the most common cancer worldwide. With the high rates of metastasis and recurrence, its overall survival remains poor at the present time. Hence, seeking new potential therapeutic targets of GC is important and urgent. Methods: We retrieved the gene expression profiles and clinical data from The Cancer Genome Atlas (TCGA) datasets. After screening differentially expressed genes (DEGs), we carried out the survival analysis for overall survival to pick out robust DEGs. To explore the role of these robust DEGs, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Subsequently, protein interactions network was constructed utilizing the Search Tool for the Retrieval of Interacting Genes (STRING) database. We then presented the module analysis and filtered out hub genes by the Cytoscape software. Finally, Kaplan-Meier analysis was utilized to demonstrate the prognostic role of these hub genes. Results: According to the gene expression profiles of TCGA and the survival analysis, 238 robust DEGs were filtered out, consisting of 140 up-regulated and 98 down-regulated genes. The up-regulated DEGs were mainly enriched in systemic lupus erythematosus, cytokine activity, and alcoholism, while downregulated DEGs were mainly enriched in steroid hormone receptor activity, immune response, and metabolism. Through the construction of the protein-protein interaction (PPI) network, eight hub genes were finally screened out, including CCR8, HIST1H3B, HIST1H2AH, HIST1H2AJ, NPY, HIST2H2BF, GNG7, and CCL25. Conclusions: Our study picked out eight hub genes, which might be potential prognostic biomarkers for GC and even be treatment targets for clinical implication in the future.