Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort

BackgroundAccumulated evidences have demonstrated that long non-coding RNAs (lncRNAs) are correlated with prognosis of patients with hepatocellular carcinoma. The current study aimed to develop and validate a prognostic lncRNA signature to improve the prediction of overall survival in hepatocellular carcinoma patients.MethodsThe study cohort involved 348 hepatocellular carcinoma patients with lncRNA expression information and overall survival information. Through gene mining approach, the current study established a prognostic lncRNA signature (named LncRNA risk prediction score) for predicting the overall survival of hepatocellular carcinoma patients.ResultsThe current study built a predictive nomogram based on ten prognostic lncRNA predictors through Cox regression analysis. In model group, the Harrell's concordance indexes of LncRNA risk prediction score were 0.811 (95% CI 0.769-0.853) for 1-year overall survival, 0.814 (95% CI 0.772-0.856) for 3-year overall survival and 0.796 (95% CI 0.754-0.838) for 5-year overall survival respectively. In validation cohort, the Harrell's concordance indexes of LncRNA risk prediction score were 0.779 (95% CI 0.737-0.821), 0.828 (95% CI 0.786-0.870) and 0.796 (95%CI 0.754-0.838) for 1-year survival, 3-year survival and 5-year survival respectively. LncRNA risk prediction score could stratify hepatocellular carcinoma patients into low risk group and high risk group. Further survival curve analysis demonstrated that the overall survival rate of high risk patients was significantly poorer than that of low risk patients (P<0.001).ConclusionsIn conclusion, the current study developed and validated a prognostic signature to predict the individual mortality risk for hepatocellular carcinoma patients. LncRNA risk prediction score is helpful to identify the patients with high mortality risk and optimize the individualized treatment decision. The web calculator can be used by click the following URL: https://zhangzhiqiao2.shinyapps.io/Smart_cancer_predictive_system_HCC_3/.