Integrative analysis of a four-component competing endogenous RNA network reveals potential diagnostic and prognostic biomarkers in gastric cancer

Gastric cancer (GC) is a common and deadly cancer in the world. 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. 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 non-coding RNAs (lncRNAs), circRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) was established. Enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. Furthermore, A sub-network was extracted and using qRT-PCR method, the expression changes of two hub ceRNAs were examined. Finally, survival analysis was performed to identify potential prognostic RNAs. 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 relating to the network. 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. The established ceRNA network 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.