Comprehensive competitive endogenous RNA network analysis reveals -related axes and prognostic biomarkers in hepatocellular carcinoma.

OBJECTIVES

Hepatocellular carcinoma (HCC) is a common and lethal type of cancer worldwide. The importance of non-coding RNAs such as long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) have been recognized in the development of HCC. In this study, we constructed a four-component competing endogenous RNA (ceRNA) network in HCC and evaluated prognostic values of the ceRNAs.

MATERIALS AND METHODS

The expression profiles of lncRNAs, miRNAs, and mRNAs were retrieved from The Cancer Genome Atlas database. GSE94508 and GSE97332 studies from the Gene Expression Omnibus database were used to identify circRNAs expression profiles. A four-component ceRNA network was constructed based on differentially-expressed RNAs. Survival R package was utilized to identify potential prognostic biomarkers.

RESULTS

A four-component ceRNA network including 295 edges and 239 nodes was constructed and enrichment analysis revealed important Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. A Protein-Protein Interaction network with 118 nodes and 301 edges was also established. The enhancer of zeste homolog 2 (EZH2) was the highest degree hub gene in the PPI network. Because of the significance of EZH2 in HCC, we presented its axes in the ceRNA network, which play important roles in HCC progression. Furthermore, ceRNAs were identified as potential prognostic biomarkers utilizing survival analysis.

CONCLUSION

Our study elucidates the role of ceRNAs and their regulatory interactions in the pathogenesis of HCC and identifies EZH2-related RNAs which may be utilized as novel therapeutic targets and prognostic biomarkers in the future.