Construction and validation of a cuproptosis-related genes prognostic model for hepatocellular carcinoma

Abstract

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a poor prognosis. Cuproptosis is a recently confirmed novel kind of programmed cell death and associated with a variety of cancer. However, the prognostic value of cuproptosis-related genes (CRGs) is still limited in HCC. Methods Gene expression data and clinical information of HCC patients were downloaded from the Cancer Genome Altas (TCGA) and Gene-Expression Omnibus (GEO) databases. Differential expression analysis was performed to identify the differentially expressed CRGs. Then univariate and multivariate Cox regression analyses were applied to screen out prognosis-related differentially expressed CRGs and construct a prognostic CRG models. The Kaplan-Meier survival analysis and Receiver operating characteristic (ROC) curves were employed to assess the prognostic values of the prognostic CRG model. The Cibersort analysis was used to evaluate the relationship between the CRG model and immune infiltration. In addition, the Gene Set Enrichment Analysis (GSEA) were used to explore the molecular mechanism of the prognostic CRG model. Results A total of 120 differentially expressed CRGs in HCC were screened. A prognostic CRG model containing three genes (ABCB6, AACS, CKAP2) was constructed for independently predicting the prognosis of HCC. The Kaplan-Meier survival analysis showed that patients in high-risk group had significantly shorter overall survival (OS). The ROC analysis indicated that the CRG model performed better than the single gene in predicting survival rates. Univariate and multivariate Cox regression analysis demonstrated that the CRG model was an independent predictor. Moreover, the CRG model was significantly correlated with the stromal score, the tumor purity score, T cells folicular helper, T cells regulator, and macrophages M0. In addition, the GSEA revealed cell cycle, oocyte meiosis, mitotic nuclear division, and DNA replication pathways were mainly enriched in the high-risk group. Conclusion This study constructed a prognostic CRG model in HCC, which has high predictive efficacy. These findings extend the knowledge of CRGs in HCC, provide theoretical support for the prognostic prediction, and may inform new therapeutic strategies for HCC.