ArticleDiscover oncology2025
Disulfidptosis, a novel regulated cell death to predict survival and therapeutic response in kidney renal clear cell carcinoma.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Disulfidptosis: molecular mechanisms and therapeutic targets.Signal transduction and targeted therapy · 2026Review
- Disulfidptosis: Mechanisms, evidence boundaries, and translational opportunities.Redox biology · 2026Review
- A multi-programmed cell death-related LncRNA signature for prognosis and immune microenvironment evaluation in kidney renal clear cell carcinoma.Scientific reports · 2026Article
- Identification of the disulfidptosis-related gene G6PD as a potential biomarker and therapeutic target in pancreatic ductal adenocarcinoma by integrative bioinformatics analysis and experimental validation.Discover oncology · 2026Article
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8 authors.
Funding
Abstract
backgroundMetabolic regulation of cell death has become a potential therapeutic target for kidney renal clear cell carcinoma (KIRC), which is distinguished by notable heterogeneity and significant immune infiltration. Disulfidptosis, a recently identified form of cell death, has gained prominence in antitumor immunity. This research aims to investigate the correlation between disulfidptosis and prognosis of KIRC, while also exploring the possibility of predicting therapeutic response by disulfidptosis-associated genes (DAGs).
methodsWe sourced clinical data and RNA sequence of KIRC from the Cancer Genome Atlas Database. Employing unsupervised clustering based on 23 DAGs, we further identified key differentially expressed genes (DEGs) between clusters to construct a DAG prognostic signature. A nomogram was developed and validated to predict clinical outcome of KIRC. Finally, we examined immune cell infiltration, tumor mutational burden, immunotherapy response, and sensitivity to drugs in high and low-risk groups.
resultsTwo distinct KIRC patient clusters were successfully stratified using the 23-DAG-related prognostic signature, comprising 11 key genes. This resulted in a robust risk model with strong predictive accuracy for overall survival. The nomogram, incorporating DAG-based risk scores, age, and pM stage, exhibited excellent predictive performance. The high-risk group displayed increased immune cell infiltration and tumor mutational burden, while the low-risk group showed heightened sensitivity to immunotherapies and targeted treatments.
conclusionThis study established a robust DAG-based risk model for KIRC, highlighting its significant correlation with the immune landscape and therapeutic responses. Novel disulfidptosis-related biomarkers revealed distinct immune profiles, drug sensitivities, and immunotherapy potentials among KIRC patients.
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