Bioinformatics-Based Identification of Methylated-Differentially Expressed Genes and Related Pathways in Gastric Cancer.

Abstract

The aim of the study was to identify methylated-differentially expressed genes (MDEGs) in gastric cancer and investigate their potential pathways. Expression profiling (GSE13911 and GSE29272) and methylation profiling (GSE25869 and GSE30601) data were obtained from GEO DataSets. Differentially expressed genes and differentially methylated genes were identified using GEO2R. Gene ontology and pathway enrichment analyses were performed for the MDEGs. Protein-protein interaction (PPI) networks were established by STRING and Cytoscape. Analysis of modules in the PPI networks was performed using MCODE. Further, the hub genes derived from the PPI networks were verified by The Cancer Genome Atlas (TCGA) database and human tissues, with methylation-specific PCR for genes methylation and real-time qPCR for genes expression. A total of 445 genes were identified as hypermethylated, lowly expressed genes (Hyper-LGs), which were enriched in the regulation of system process and channel activity. A total of 129 genes were identified as hypomethylated, highly expressed genes (Hypo-HGs), which were involved in cell adhesion, cell proliferation, and protein binding. Pathway analysis showed that Hyper-LGs were associated with neuroactive ligand-receptor interaction and calcium signaling pathway, while Hypo-HGs were enriched in pathways in cancer. In the PPI networks, after verification by TCGA analysis and human tissue detection, CASR, CXCL12, and SST were identified as significantly different hub genes. MDEG analysis helps to understand the epigenetic regulation mechanisms involved in the development and progression of gastric cancer. The hub genes have predictive and prognostic value as methylation-based biomarkers for the precise diagnosis and treatment of gastric cancer.