Comprehensive analysis of the molecular mechanism for gastric cancer based on competitive endogenous RNA network

Abstract

Objective: To explore the regulatory mechanism of competitive endogenous RNAs (ceRNA) in gastric cancer (GC) and to predict the prognosis of GC. Materials and Methods: Expression profiles of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs were obtained from The Cancer Genome Atlas platform. Differentially expressed RNAs (DERNAs) were screened to construct a lncRNA-miRNA-mRNA ceRNA network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed on the ceRNA network-related differentially expressed mRNAs (DEmRNAs). Next, the DERNAs were subjected to Cox regression and survival analyses to identify crucial prognostic factors for patients with GC. Results: We detected 1029 differentially expressed lncRNAs, 104 differentially expressed miRNAs, and 1659 DEmRNAs in patients with GC. Next, we performed bioinformatic analysis to construct the lncRNA-miRNA-mRNA ceRNA network, which included 10 miRNAs, 65 lncRNAs, and 10 mRNAs. Subsequently, KaplanMeier (K-M) analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group, and the area under the curve value of the receiver operating characteristic curve revealed that the polygenic model had good predictive ability. The results indicated that ADAMTS9-AS1, ATAD2, and CADM2 might be potential therapeutic targets and prognostic biomarkers for GC. Conclusions: Our study has implications for predicting prognosis and monitoring surveillance of GC and provides a new theoretical and experimental basis for the clinical prognosis of GC.