Identification of disulfidptosis-related subtypes and development of a prognosis model based on stacking framework in renal clear cell carcinoma

被引:5
作者
Peng, Kun [1 ]
Wang, Ning [1 ]
Liu, Qingyuan [1 ]
Wang, Lingdian [1 ]
Duan, Xiaoyu [1 ]
Xie, Guochong [1 ]
Li, Jixi [2 ]
Ding, Degang [1 ,2 ,3 ]
机构
[1] Zhengzhou Univ, Henan Prov Peoples Hosp, Peoples Hosp, Dept Urol, Zhengzhou 450003, Peoples R China
[2] Henan Univ, Henan Prov Peoples Hosp, Peoples Hosp, Dept Urol, Zhengzhou 450003, Peoples R China
[3] Henan Prov Peoples Hosp, Inst Urol, Zhengzhou, Peoples R China
关键词
Disulfidptosis; Ensemble learning; Machine learning; Immune infiltration; T cell exhaustion; Tumor microenvironment; ISG20;
D O I
10.1007/s00432-023-05201-3
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundClear cell renal cell carcinoma (ccRCC) is a common malignant tumor with an unsatisfactory prognosis. This study aims to identify the expression patterns of disulfidptosis-related genes (DRGs), develop a prognostic model, and predict immunological profiles.MethodsFirst, we identified differentially expressed DRGs in TCGA-KIRC cohort and analyzed their mutational profiles, methylation levels, and interaction networks. Subsequently, we identified disulfidptosis-associated molecular subtypes and investigated their prognostic and immunological characteristics. Simultaneously, a disulfidptosis-related prognostic signature (DRPS) was developed using a two-stage stacking framework consisting of 5 machine learning models. The effect of DRPS on immune cell infiltration levels was explored using seven different algorithms, and the status and function of T cells for distinct risk-score groups were evaluated based on T cell exhaustion and dysfunction scores. Additionally, the study also examined differences in clinical characteristics and therapy efficacy between high- and low-risk groups.ResultsWe found two disulfidptosis-associated clusters, one of which had a poor prognosis and was linked to high immune cell infiltration but impaired T cell function. DRPS showed excellent predictive performance in all four cohorts and could accurately identified disulfidptosis-related molecular subtypes. The DRPS-based risk score was positively associated with poor prognosis, malignant pathological features, high immune cell infiltration levels, and T cell exhaustion or dysfunction, and better respond to immunotherapy and targeted therapy. Additionally, we have identified a close association between ISG20 and disulfidptosis as well as tumor immunity.ConclusionOur study identified distinct disulfidptosis-related subtypes in ccRCC patients, and constructed the highly accurate and robust DRPS based on an ensemble learning framework, which has critical reference value in clinical decision-making and individualized treatment. And this work also revealed ISG20 exhibits promising potential as a therapeutic target for ccRCC.
引用
收藏
页码:13793 / 13810
页数:18
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