Expression levels of lncRNAs are prognostic for hepatocellular carcinoma overall survival.

Studies have demonstrated that long non-coding RNAs (lncRNAs) play important roles in cancer development and progression. However, associations between the expression patterns and prognostic roles of lncRNAs in hepatocellular carcinoma (HCC) have not been comprehensively described. In this study, we established a prognostic model of lncRNA expression using public datasets of HCC from The Cancer Genome Atlas (TCGA) and adopted the International Cancer Genome Consortium (ICGC) as an independent cohort to validate the stability of our model. Cox regression analysis was used to explore the independent prognostic factor in both training and validation cohorts. Additionally, we explored the functional roles of lncRNAs using bioinformatic analyses. According to lncRNA consensus clusters, we resolved the distribution of molecular and clinical data and observed that individual lncRNA could function as prognostic biomarkers in HCC. Furthermore, the novel lncRNA molecular subtypes were statistically significant for predicting HCC status, which was validated by nested cross-validation. We found that lncRNA subtypes were partially related to gender, histological grade, and mutations within TP53. The lncRNA subtypes were also consistent with mRNA-based subtypes, and pathway enrichment analysis identified the involvement of multiple signaling pathways. In addition, we observed that upregulated DANCR was significantly associated with poor prognosis in HCC patients. In conclusion, our model based on lncRNA expression is statistically significant as a diagnostic and prognostic indicator for patients with HCC.