Network and functional analyses of differentially expressed genes in gastric cancer provide new biomarkers associated with disease pathogenesis

Abstract

Abstract Background Gastric cancer is a dominant source of cancer-related death around the globe and a serious threat to human health. However, there are very few practical diagnostic approaches and biomarkers for the treatment of this complex disease. Methods This study aimed to evaluate the association between differentially expressed genes (DEGs), which may function as potential biomarkers, and the diagnosis and treatment of gastric cancer (GC). We constructed a protein-protein interaction network from DEGs followed by network clustering. Members of the two most extensive modules went under the enrichment analysis. We introduced a number of hub genes and gene families playing essential roles in oncogenic pathways and the pathogenesis of gastric cancer. Enriched terms for Biological Process were obtained from the “GO” repository. Results A total of 307 DEGs were identified between GC and their corresponding normal adjacent tissue samples in GSE63089 datasets, including 261 upregulated and 261 downregulated genes. The top five hub genes in the PPI network were CDK1, CCNB1, CCNA2, CDC20, and PBK. They are involved in focal adhesion formation, extracellular matrix remodeling, cell migration, survival signals, and cell proliferation. No significant survival result was found for these hub genes. Conclusions Using comprehensive analysis and bioinformatics methods, important key pathways and pivotal genes related to GC progression were identified, potentially informing further studies and new therapeutic targets for GC treatment.

Keywords

• Gastric cancer
• Gene expression
• Signaling networks
• Biomarkers