Development and Validation of the novel Cuproptosis-and Immune-related Signature for Predicting Prognosis in Hepatocellular Carcinoma

Background : Hepatocellular carcinoma often results in late -stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. Method: We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. Results : Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk -scoring model was developed using gene expression, effectively categorizing patients into low- or high -risk groups. Validated in the ICGC dataset, high -risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low -risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. Conclusions : The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.