Objective: To construct a long non-coding RNA (lncRNA) risk model associated with pyrosis so as to predict the prognosis of primary hepatocellular carcinoma (HCC). Methods: TCGA-HCC transcript data and clinicopathological information were downloaded from The Cancer Genome Atlas (TCGA), and the expression matrix of pyroxis-related genes was extracted from the HCC expression data. Pearson correlation analysis was used to identify pyroxis-related lncRNAs.The differentially expressed pyrotic-related lncRNAs were screened by difference analysis and univariate COX regression, and the risk model of pyrotic-related lncRNAs was constructed by multivariate COX regression analysis. The scoring performance of the risk model was verified by AUC values for 1-year, 2-year, and 3-year survival, AUC values for risk factors, and DCA. Results: A risk model based on 14 pyroticosis-related lncRNAs (MKLN1-AS, NRAV, LINC00205, PTOV1-AS1, SNHG20, FAM111A-DT, SNHG4, AC074117.1, AC091057.1, PXN-AS1, AL031985.3, AC025178.2, AC016747.1, AC099850.4) was successfully constructed, and patients in the low-risk group had a better prognosis than those in the high-risk group (P＜0.001) and were superior to traditional clinicopathological features in predicting HCC outcomes.In addition, immune checkpoints PDCD-1 (PD-1), CD274(PD-L1), HAVCR2, and IDO2 were expressed differently between the two risk groups. Conclusion: The pyrotic-related lncRNA risk model developed in this study predicts the prognosis of HCC patients better than traditional clinicopathological features.
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