Objective:To construct a model of hepatocellular carcinoma recurrence risk and explore the po-tential value of CD1c as a biomarker in hepatocellular carcinoma recurrence.Methods:The clinical in-formation and lncRNA transcriptome data for hepatocellular carcinoma were downloaded from TCGA.Bioinformatics methods such as differential analysis and Lasso regression analysis were used to construct a risk model for predicting the recurrence of hepatocellular carcinoma.After scoring pa-tients by the model,immune genes associated with hepatocellular carcinoma recurrence were screened.Finally,immunofluorescence staining was used to validate the screened immune genes.Results:There were 4 539 differentially expressed lncRNAs between the tumor and the normal group,and 697 differentially expressed lncRNAs between the recurrence and the non-recurrence group.The 30 candidate lncRNAs obtained by the intersection of the above results were used to con-struct a risk model for predicting recurrence.According to the risk model scoring formula,patients with hepatocellular carcinoma were divided into high and low-recurrence risk groups.In the training and testing group,ROC curve analysis showed that the model(AUC=0.76 in the training group group and AUC=0.81 in the test group)had better predictive diagnostic ability than other clinical fac-tors.The gene set enrichment analysis(GSEA)and gene set variation analysis(GSVA)suggested that the recurrence of hepatocellular carcinoma was associated with immunosuppression.Correlation analysis between the risk score and immune genes indicated that CD1c was associated with the recur-rence of hepatocellular carcinoma.Immunofluorescence staining analysis further confirmed that CD1c could serve as a biomarker.Conclusion:The lncRNA-based risk model has excellent ability to predict the recurrence of hepatocellular carcinoma and the identified gene CD1c may serve as a potential bio-marker for hepatocellular carcinoma recurrence.
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