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Background: The present aimed to establish a prognostic signature based on autophagy-related long non-coding RNAs (lncRNAs) analysis to predict the clinical outcome of hepatocellular carcinoma (HCC) patients using a comprehensive analysis of micro array data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Methods: Based on co-expression network analysis, autophagy-related lncRNAs were obtained using edge R package. Univariate and multivariate analyses were used to develop an autophagy-related lncRNAs risk signature and a predictive nomogram by data from the TCGA database. Subgroup analysis and internal validation were performed to confirm the predictive power. Subsequently, the predictive autophagy-related lncRNA prognostic signature and nomogram were externally explored and validated by HCC patients from the ICGC database. Results: According to univariate and multivariate analyses, four autophagy-related lncRNAs (BACE1-AS, SNHG3, MIR210HG, and ZEB1-AS1) with prognostic value were identified in patients with HCC. Then, an autophagy-related lncRNAs prognostic signature was constructed. Based on the prognostic signature, all patients were subdivided into high- and low-risk groups. The autophagy-related lncRNA prognostic signature showed strong predictive power independent of all the clinicopathological features. A predictive nomogram based on the prognostic signature and multiple clinicopathological features was established through a survival analysis with the HCC data in TCGA. Internal validation demonstrated that the prognostic signature and nomogram have a strong power for predicting overall survival in patients with HCC. Whereas external validation further confirmed the robustly predictive power. Subsequently, functional enrichment analysis indicated the high-risk group mainly enriched in autophagy- and cancer-related pathways. Conclusions: The four autophagy-related lncRNAs prognostic signature and the predictive nomogram established in the study might support clinician in individual treatment optimization and clinical decision-making for patients with HCC. |
