Abstract
Disulfidptosis is a novel form of metabolic-related regulated cell death (RCD) that is caused by disulfide stress caused by the accumulation of excess cystine in the cell. Targeting disulfide metabolism imbalance is an emerging strategy for the treatment of cancer. However, it is undetermined how disulfidptosis-related genes (DRGs) influence hepatocellular carcinoma (HCC). Unsupervised clustering analysis was performed on the TCGA-LIHC cohort to identify various phenotypes of disulfidptosis. GSVA was used to measure the activation of characteristic gene sets, while CIBERSORT was employed to estimate the infiltration of immune cells. Disulfidptosis-related signature was generated to quantify the phenotype of disulfidptosis in HCC patients. Next, we examined the disparities among the high and low disulfidptosis score categories by considering clinical characteristics, infiltration of immune cells, functions related to the immune system, sensitivity to chemotherapeutic drugs, and effectiveness of immunotherapy. Two different disulfidptosis phenotypes with different prognoses, clinical traits, biological pathways, and immune cell infiltration were identified. Based on differently expressed genes (DEGs) among 2 disulfidptosis phenotypes, a disulfidptosis-related signature was built. The prognostic value of this signature was then evaluated in the TCGA and GEO datasets. Low disulfidptosis score indicated favorable clinical outcomes, higher levels of immune cell infiltration, lower tumor purity, and enhanced immune responses. Furthermore, we noticed a clear disparity in tumor mutation load and drug responsiveness when comparing the high and low disulfidptosis score categories. Finally, a quantitative nomogram was built with disulfidptosis score and several clinical characteristics. The disulfidptosis-related signature provides new insights into the tumor immune microenvironment and complexity in HCC. The disulfidptosis score can serve as a promising tool for personalized prognostic prediction of HCC patients and for customizing more effective immunotherapeutic strategies.