Candidate lncRNA–miRNA–mRNA network in predicting hepatocarcinogenesis with cirrhosis: an integrated bioinformatics analysis

This study aimed to explore the potential competing endogenous RNA (ceRNA) network in forecasting HCC development in patients with cirrhosis through a comprehensive bioinformatic analysis. Data mining from GEO and TCGA databases was employed to dig a spectrum of differentially expressed mRNA, lncRNA and miRNA profiles. Their expression was confirmed by RT-PCR in matched HCC cohorts (n = 6/group). The ceRNA network was constructed by co-expression analysis. Their reciprocal regulations and their roles in epithelial-to-mesenchymal transition (EMT) process were validated by gain- and loss-of-function experiments at the cellular level. Kaplan–Meier method was applied to reveal prognostic values. By intersecting differentially expressed genes (DEGs) in GEO and TCGA data sets and Pearson correlation analysis, 20 mRNAs, 24 miRNAs and 41 lncRNAs were identified. Of these, FOXD2-AS1, BLVRA and CYTH2 were markedly upregulated in HCC tissues and HCC cells with high metastatic potential (MHCC97H) compared with their adjacent normal/cirrhotic tissues and L02 and MHCC97L cells. However, dysregulated miR-139-5p exhibited the opposite expression pattern. Using miRanda algorithms, FOXD2-AS1, BLVRA and CYTH2 showed potential binding sites for miR-139-5p. FOXD2-AS1 knockdown induced a marked increase in miR-139-5p and EMT inhibition. The loss of miR-139-5p led to an increase in BLVRA and CYTH2 expression and EMT process. Conversely, miR-139-5p overexpression suppressed BLVRA and CYTH expression and EMT process. FOXD2-AS1, miR-139-5p, BLVRA and CYTH2 highly correlated with prognosis in patients with HCC. FOXD2-AS1/miR-139-5p/BLVRA or CYTH2 axis might be the underlying molecular mechanism that dissects HCC development caused by cirrhosis.