Development of a prognostic model based on different disulfidptosis related genes typing for kidney renal clear cell carcinoma

作者：Yuanyuan Feng, Wenkai Wang, Shasha Jiang, Yongming Liu, Yan Wang, Xiangyang Zhan, Huirong Zhu, Guoqing Du · 发表于：Frontiers in Pharmacology · 年份：2024 · DOI：10.3389/fphar.2024.1343819 · 被引用次数：4 · 研究领域：Renal cell carcinoma treatment、Ferroptosis and cancer prognosis、Renal and related cancers

Background: Kidney renal clear cell carcinoma (KIRC) is a common and clinically significant subtype of kidney cancer. A potential therapeutic target in KIRC is disulfidptosis, a novel mode of cell death induced by disulfide stress. The aim of this study was to develop a prognostic model to explore the clinical significance of different disulfidptosis gene typings from KIRC. Methods: A comprehensive analysis of the chromosomal localization, expression patterns, mutational landscape, copy number variations, and prognostic significance of 10 disulfide death genes was conducted. Patients were categorized into distinct subtypes using the Non-negative Matrix Factorization (NMF) typing method based on disulfidptosis gene expression patterns. Weighted Gene Co-expression Network Analysis (WGCNA) was used on the KIRC dataset to identify differentially expressed genes between subtype clusters. A risk signature was created using LASSO-Cox regression and validated by survival analysis. An interaction between risk score and immune cell infiltration, tumor microenvironment characteristics and pathway enrichment analysis were investigated. Results: Initial findings highlight the differential expression of specific DRGs in KIRC, with genomic instability and somatic mutation analysis revealing key insights into their role in cancer progression. NMF clustering differentiates KIRC patients into subgroups with distinct survival outcomes and immune profiles, and hierarchical clustering identifies ...