Crosstalk of disulfidptosis-related subtypes identifying a prognostic signature to improve prognosis and immunotherapy responses of clear cell renal cell carcinoma patients

• Published in: BMC genomics Vol. 25; no. 1; p. 413
• Main Authors: Ren, Lei, Liu, Jinwen, Lin, Qingyuan, He, Tianyi, Huang, Guankai, Wang, Weifeng, Zhan, Xunhao, He, Yu, Huang, Bin, Mao, Xiaopeng
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 26.04.2024; BioMed Central; BMC
• Subjects: Algorithms; Apoptosis; Biomarkers, Tumor - genetics; Cancer; Cancer therapies; Carcinoma, Renal cell; Carcinoma, Renal Cell - genetics; Carcinoma, Renal Cell - immunology; Carcinoma, Renal Cell - therapy; Care and treatment; Cell death; Clear cell renal cell carcinoma; Clear cell-type renal cell carcinoma; Cluster analysis; Clustering; CTLA-4 protein; Disulfidptosis; Fatalities; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Genes; Genetic aspects; Glucose; Health aspects; Humans; Immune checkpoint; Immune evasion; Immunotherapy; Kidney cancer; Kidney Neoplasms - genetics; Kidney Neoplasms - immunology; Kidney Neoplasms - therapy; Kinases; Medical prognosis; Metabolism; Methods; Microenvironments; Mutation; Neoplasms; Nomograms; Patient outcomes; Patients; PD-1 protein; Prognosis; Proteins; Regression analysis; Risk factors; Risk groups; Tumor immune microenvironment; Tumor Microenvironment - genetics; Tumor Microenvironment - immunology; Tumor staging; Tumors; China; Tumor immune microenvironment; Clear cell renal cell carcinoma; Immune evasion; Disulfidptosis; Immunotherapy
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-024-10307-0

Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC. The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort. We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort. The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.