Identification of Potentially Functional CircRNA-miRNA-mRNA Regulatory Network in Hepatocellular Carcinoma by Integrated Microarray Analysis
Xiaoming Lin, Yuhan Chen
Department of Ultrasound, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China (mainland)
Med Sci Monit Basic Res 2018; 24:70-78
Hepatocellular carcinoma (HCC) is the most common malignancy of the liver and recent studies have revealed that circular RNA (circRNA) plays an important role in the pathogenesis of HCC. Some circRNAs may act as a microRNA (miRNA) sponge to affect miRNA activities in the regulation of messenger RNA (mRNA) expression. However, the circRNA-miRNA-mRNA network in HCC remains largely unknown.
MATERIAL AND METHODS: The circRNA expression profiles (GSE94508 and GSE97332), miRNA and mRNA expression profile (GSE22058) were downloaded from Gene Expression Omnibus microarray data and then a circRNA-miRNA-mRNA regulatory network in HCC was constructed. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed (DE) genes were performed. The functional circRNA-miRNA-mRNA regulatory modules were constructed using cytoHubba plugin based on Cytoscape and KEGG enrichment analysis.
RESULTS: The network contained 60 circRNA-miRNA pairs and 4982 miRNA-mRNA pairs, including 29 circRNAs, 16 miRNAs, and 1249 mRNAs. GO and KEGG pathway analysis revealed the network might be involved in the procession of carcinogenesis such as cell proliferation, cell cycle, and p53 signaling pathway. In addition, 3 top ranked circRNAs (hsa_circ_0078279, hsa_circ_0007456, and hsa_circ_0004913) related networks were identified to be highly correlated with the pathogenesis of HCC. Furthermore, the functional circRNA-miRNA-mRNA regulatory modules were constructed based on the 3 top-ranked circRNAs and those DE genes enriched in carcinogenesis related pathways.
CONCLUSIONS: This study suggests that a specific circRNA-miRNA-mRNA network is associated with the carcinogenesis of HCC, which might aid in the identification of molecular biomarkers and therapeutic targets for HCC.
Keywords: Biological Markers, Carcinoma, Hepatocellular, Computational Biology, RNA, Untranslated