Purpose: 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.
Methods: 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.
Results: 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.
Conclusion: FOXD2-AS1/miR-139-5p/BLVRA or CYTH2 axis might be the underlying molecular mechanism that dissects HCC development caused by cirrhosis.
Keywords: Bioinformatics; Cirrhosis; Differentially expressed genes; Hepatocellular carcinoma; Long non-coding RNAs; miRNAs.