Identification of a potential competing endogenous RNA (ceRNA) network in gastric adenocarcinoma.

Abstract

Recently, a growing body of evidence has revealed the role of competing endogenous RNA (ceRNA) networks in various human cancers. However, there is still a lack of research on the systemic ceRNA network related to gastric adenocarcinoma. The intersection of differentially expressed genes (DEGs) was obtained by mining the GSE54129, GSE13861, and GSE118916 datasets from the Gene Expression Omnibus (GEO) website. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for the enrichment analysis. A protein-protein interaction (PPI) network was established with the STRING online database, and hub genes were identified by Cytoscape software. The prediction of key microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) was conducted by miRNet. The prognostic analysis, expression difference, and correlation analysis of messenger RNAs (mRNAs), lncRNAs, and miRNAs were carried out using the Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, and Encyclopedia of RNA Interactomes (ENCORI). We identified180 significant DEGs. Extracellular matrix (ECM) receptor interaction, focal adhesion, ECM tissue, and collagen catabolic processes were the most significant pathways in the functional enrichment analysis. Nineteen upregulated hub genes and one downregulated hub gene were found to be significantly associated with the prognosis of gastric adenocarcinoma. Of the 18 miRNAs targeting 12 key genes, only six were associated with a promising prognosis in gastric adenocarcinoma. By comprehensive differential expression and survival analysis, 40 key lncRNAs were identified. Finally, we constructed a network of 24 ceRNAs associated with gastric adenocarcinoma. Potential mRNA-miRNA-lncRNA subnets were constructed, each RNA of which can be used as a prognostic biomarker for gastric adenocarcinoma.