Background and Aims Hepatocellular carcinoma (HCC) is a common malignancy with a high recurrence and mortality rate. Cuproptosis is a new type of programmed cell death involved in tumor cells' proliferation, growth, angiogenesis, and metastasis. Therefore, this study aims to investigate the relationship between the expression of cuproptosis-related genes (CRGs) and the prognosis in HCC, establish a prognosis-related nomogram model, and analyze the association of CRGs with the immune cell infiltration in HCC.Methods Differential expression analysis of CRGs in the TCGA database was performed using the R language "limma" package; the "clusterProfiler" package was used for GO and KEGG analysis; the prognostic CRGs were screened by univariate Cox regression analysis; the prognostic scoring model based on CRGs for HCC was constructed by Lasso-Cox regression analysis; the "ggsurvplot" package drew the Kaplan-Meier survival curve draws using overall survival (OS) as the outcome variable; the "survival ROC" package created the ROC curve for assessing the accuracy of the prognostic score; the nomogram and the calibration curves were drawn by the 'regplot' and 'rms' packages; the associations between the expression of CRGs and the abundance of six immune cells were analyzed using the TIMER database.Results Among the 19 CRGs, there were 16 differentially expressed ones in HCC tissue compared with normal tissue (up-regulation: PDHB, PDHA1, MTF1, LIPT1, LIPT2, LIAS, GLS, DLD, DLST, DLAT, CDKN2A, and ATP7A; down-regulation: SLC31A1, GCSH, DBT, and NLRP3), and NLRP 2 had the highest mutation frequency of 12%. GO, and KEGG analyses showed that CRGs were enriched in signaling pathways such as the tricarboxylic acid cycle, carbon metabolism, pyruvate metabolism, glycolysis/gluconeogenesis, and platinum drug resistance. Three CRGs (CDKN2A, GLS, and DLAT) that affected the OS were screened by univariate Cox regression analysis and LASSO Cox regression analysis for the construction of the prognostic model, and the prognostic score was constructed using regression coefficient: risk score=0.22×DLAT (expression level) + 0.11×CDKN2A (expression level) + 0.03×GLS (expression level). The Kaplan-Meier curve analysis showed that the HCC patients with high-risk scores had a poor prognosis (P<0.05), and the model prediction performance was evaluated by the time-dependent ROC curve of the risk model, and the AUC at 1, 3, and 5 years was 0.741,0.657 and 0.633, respectively. The nomogram was constructed by incorporating age, sex, T stage, N stage, M stage, pathological classification, CDKN2A, GLS, and DLAT. The calibration map showed good consistency between the nomogram prediction and the actual observation. There were positive correlations of GLS, DLAT, and CDKN2A with HCC immune cell infiltration and a significant correlation with immune checkpoints PDCD 1, CD274, and HAVCR2 (all P<0.05). Further analysis indicated that the higher CDKN2A, GLS, and DLAT expression in HCC tissue, the later the Barcelona pathological stage, the worse the histological grade in patients (all P<0.05).Conclusion Gene signatures associated with cuproptosis can be used as potential prognostic predictors for HCC patients and may provide new insights into the treatment of HCC.