An N

Background: Hepatocellular carcinoma (HCC) is the leading cause of tumor-related mortality worldwide. N Methods: We used Pearson's correlation coefficient (r) to identify m6A-associated lncRNAs. We then performed univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses on the screened m6A-related lncRNAs to build a prognostic risk model for patients with HCC. The prognostic values and predictive performance of the model were then analyzed through Kaplan-Meier curve, receiver operating characteristic (ROC) curve, and nomogram. In addition, the potential value of this model for assessing sorafenib or immunotherapeutic responses was investigated based on the R package "pRRophetic" and immunophenoscore (IPS), respectively. Results: Fourteen m6A-related lncRNAs were identified to construct the predictive model (P<0.05). Patients with high risk showed poorer survival than those with low risk. The risk score may serve as an independent predictor for the prognosis of patients with HCC even in the subgroup analysis. Moreover, our predictive model outperformed Conclusions: This study identified that a novel 14-m6A-related lncRNA signature could be a promising predictor for patient survival, and it might provide a vista for treatment response assessment of chemotherapy and immunotherapy.