Analysis of a four-component competing endogenous RNA network reveals potential biomarkers in gastric cancer: An integrated systems biology and experimental investigation

Abstract

Background: Gastric cancer (GC) is a common and deadly cancer worldwide. Molecular changes underlying the development of GC are not thoroughly understood. Therefore, we constructed and analyzed a novel four-component competing endogenous RNA (ceRNA) network to introduce plausible diagnostic and prognostic biomarkers in GC. Materials and Methods: Transcriptomics and circular RNA (circRNA) data were retrieved from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, respectively. After batch effect correction, differential expression analysis, and interaction prediction, a ceRNA network including long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) was established. Enrichment analyses were performed, and a protein–protein interaction (PPI) network was constructed. Furthermore, a subnetwork was extracted, and using the quantitative real-time polymerase chain reaction (qRT-PCR) method, the expression changes of two hub ceRNAs were examined. Finally, survival analysis was performed to identify potential prognostic RNAs. Results: A four-component ceRNA network containing 822 nodes and 1365 edges was constructed. Enrichment analyses unveiled important signaling pathways and gene ontologies such as neuroactive ligand–receptor interaction and axonogenesis. The PPI network showed the interactions among mRNAs of the ceRNA network. qRT-PCR indicated downregulation of EPHA5 and SNAP91 mRNAs in GC compared to control tissues. Survival analyses revealed eight mRNAs and one lncRNA as potential prognostic biomarkers in GC. Conclusion: The established four-component network of ceRNAs in GC reveals a comprehensive view of the molecular and cellular characteristics of GC progression, which can be considered as a basis to examine and validate potential diagnostic and prognostic biomarkers as well as therapeutic targets.