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• W2892563213 abstract "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. 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. 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. 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." @default.
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• W2892563213 date "2018-12-01" @default.
• W2892563213 modified "2023-10-14" @default.
• W2892563213 title "Construction of a long non-coding RNA-associated ceRNA network reveals potential prognostic lncRNA biomarkers in hepatocellular carcinoma" @default.
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• W2892563213 doi "https://doi.org/10.1016/j.prp.2018.09.022" @default.
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