Abstract: Objective To construct a prognostic prediction model for hepatocellular carcinoma based on necroptosis⁃related long non⁃coding RNAs (NRLs). Methods Transcript data and clinical information of hepatocellular carcinoma were downloaded from the TCGA database. The LASSO⁃Cox model was used to construct a prognostic prediction model, the predictive value of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve, and gene set enrichment analysis (GSEA) and immune infiltration analysis were performed. The differential expression of the four NRLs between hepatocellular carcinoma cells Huh7 and normal hepatocytes MIHA was confirmed by qRT⁃PCR. Results A prognostic prediction model was constructed for hepatocellular carcinoma based on four NRLs, including AL117336.2, MKLN1⁃AS, FOXD2⁃AS1, and LINC01224. The risk score constructed based on the training set was an independent factor on prognosis (HR=1.275, P<0.001). The AUCs of 1⁃, 3⁃ and 5⁃year OS predicted by the risk model were 0.816, 0.747 and 0.752, respectively, in the training set, and 0.713, 0.621 and 0.626, respectively, in the testing set. Patients were classified into high and low risk groups based on the median risk score, and the overall survival rate of the high risk group was lower than that of the low risk group in both the training set and the testing set (all P<0.05). In addition, there were significant differences in the degree of immune cell infiltration and the expression of immune checkpoint molecules between the two groups (all P<0.01). qRT⁃PCR results showed that the expression levels of the four NRLs were higher in hepatocellular carcinoma cells Huh7 than in normal hepatocytes MIHA (all P<0.05). Conclusions The NRLs model has been successfully constructed to predict the prognosis of patients with hepatocellular carcinoma, and the constructed model has potential value for guiding clinical treatment.

Key words: Hepatocellular carcinoma, Necroptosis, Long non?coding RNAs (lncRNAs), Prognosis