Objectives: Hepatocellular carcinoma (HCC) is the sixth leading cause of cancer-related mortality in the world. Accumulating evidence has highlighted the regulatory roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in HCC.
Methods: The lncRNA expression data and corresponding patient information were obtained from The Cancer Genome Atlas (TCGA) database. Competing lncRNA-mRNA interactions were identified using the hypergeometric test. Co-expression analysis was implemented using the Spearman correlation coefficient. Multivariate Cox regression survival analysis was utilized to extract prognostic lncRNAs in the network.
Results: Based on the "ceRNA hypothesis", a global lncRNA-associated ceRNA network (LCeNET) in HCC was constructed. Nine lncRNAs were identified as hubs and found to be enriched in various cancer-related biological processes. In addition, ceRNA pairs associated with survival were screened to construct a lncRNA-miRNA-mRNA sub network. Finally, we developed a sixteen-lncRNA model that could classify patients into high- and low-risk subgroups with different survival outcomes, and MCM3AP-AS1 functioned as a hub in both LCeNET and prognostic model.
Conclusions: Our work will improve the understanding of lncRNA-mediated ceRNA regulatory mechanisms in HCC pathogenesis and facilitate the identification of candidate prognostic biomarkers for HCC.
Keywords: Competitive endogenous RNA; Liver hepatocellular carcinoma; Long non-coding RNAs; Prognostic biomarker.
Copyright © 2018. Published by Elsevier GmbH.