Purpose: Liver transplantation (LT) currently yields the best outcomes for hepatocellular carcinoma (HCC). However, tumor recurrence still occurs in some patients. Identifying markers that predict HCC recurrence after LT is an unmet medical need.
Methods: In this study, differential expression analysis was used to identify differentially expressed microRNAs (DEmiRs) between HCC and liver tissues in the The Cancer Genome Atlas database and in data from patients with recurrent or non-recurrent HCC in the GSE64989 dataset. The expression profiles of the overlap DEmiRs were used to construct an miRNA-based risk score to predict prognosis using Cox regression analysis. The target genes of the miRNAs of interest were predicted, and they were analyzed for functional enrichment. Furthermore, we used the miRNAs of interest to construct a competitive endogenous RNA (ceRNA) network of long non-coding RNAs (lncRNAs), miRs and mRNAs.
Results: Four up-regulated and three down-regulated miRNAs in HCC and recurrent HCC after LT were considered as candidate miRs. MiR-3200-3p and miR-3690 were selected to construct the miR-based risk score, which was found to be associated with poor overall survival and progression-free survival. Furthermore, it proved to be an independent prognostic factor after adjusting for other clinicopathological factors. The corresponding ceRNA networks of these two miRs that we constructed may help to understand their regulatory mechanisms in HCC.
Conclusion: We propose a risk score based on miR-3200-3p and miR-3690 that may be useful as a prognostic marker to predict HCC recurrence after LT. We generated a ceRNA network involving these miRNAs, which may help reveal their regulatory roles in HCC.
Keywords: hepatocellular carcinoma, liver transplantation, microRNA, recurrence, ceRNA network