Establishment and evaluation cuproptosis-related gene signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma.

BACKGROUND

This study aims to develop a novel cuproptosis-related model through bioinformatics analysis, providing new insights into HCC classification. It also explores the correlation between the cuproptosis-related risk score and factors such as prognosis, tumor mutation burden (TMB), biological function, tumor microenvironment (TME), and immune efficacy.

METHODS

We performed unsupervised clustering of cuproptosis-related gene expression profiles from TCGA and GEO to identify molecular subtypes and differentially expressed genes. Prognostic models were constructed using univariate, Lasso, and multivariate Cox regression analyses. HCC patients were classified into high-risk and low-risk subgroups, and the model's prognostic value was assessed through survival analysis, ROC curves, and nomograms. Immune checkpoint, drug sensitivity, and IPS were used to evaluate immunotherapy response. The model's predictive ability was further validated with the ICGC database and IMvigor210 cohort. Finally, key gene expression and biological functions were validated in human tissues and HCC cell lines.

RESULTS

The cuproptosis-related gene risk score model (CRGRM), based on GMPS, DNAJC6, BAMBI, MPZL2, ASPHD1, IL7R, EPO, BBOX1, and CXCL9, independently predicted HCC prognosis and immune response. Clinical correlation and ROC curve analysis demonstrated its accuracy in predicting 0.5-, 1-, 3-, and 5-year survival. The risk score also strongly correlates with immunotherapy response and serves as a reliable treatment predictor. Drug sensitivity analysis revealed that the low-risk group was more sensitive to dasatinib, imatinib, and gefitinib. In vitro, BAMBI knockdown significantly inhibited HCC cell proliferation and metastasis.

CONCLUSIONS

This model demonstrates potential in predicting prognosis and immunotherapy response, providing insights into personalized treatment strategies for HCC. Additionally, our study suggests that BAMBI may serve as a novel biomarker and potential therapeutic target for HCC.