Development and validation of disulfidptosis-related genes signature for patients with glioma.

Autor: Wang, Jia, Luo, Junchi, Yang, Sha, Deng, Yongbing, Chen, Peng, Tan, Ying, Liu, Yang
Zdroj: Discover Oncology; 12/18/2024, Vol. 15 Issue 1, p1-20, 20p
Abstrakt: Background: Disulfidptosis has recently emerged as a novel form of regulated cell death (RCD). Evasion of cell death is a hallmark of cancer, and the resistance of many tumors to apoptosis-inducing therapies has heightened interest in exploring alternative RCD mechanisms. Methods: Transcriptomic and clinical data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA). Glioma samples were classified using non-negative matrix factorization (NMF). A predictive model was constructed using Lasso regression analysis, and its performance was evaluated through receiver operating characteristic (ROC) and Kaplan–Meier survival analyses. The relationship between the model and the tumor immune microenvironment (TIME) as well as treatment sensitivity was also assessed. Finally, we validated the expression of key signature genes in glioma. Results: Glioma samples were categorized into two distinct subtypes based on disulfidptosis-related genes, showing significant differences in overall survival (OS) and progression-free survival (PFS) between the subtypes. A genetic risk score model was then developed using these genes. A nomogram predicting OS was constructed using the risk score and clinical variables. Patients were stratified into low- and high-risk groups based on the median risk score from the TCGA cohort. Low-risk patients had significantly better outcomes compared to high-risk patients (TCGA cohort, OS: p < 0.001; PFS: p < 0.001; CGGA cohort, OS: p < 0.001). The risk score was associated with HLA expression, immune checkpoint genes, immune cell infiltration, immune function, tumor mutation burden, tumor stemness score, and drug sensitivity. Lastly, the expression of 11 signature genes was confirmed in glioma tissues. Conclusions: The disulfidptosis-related gene-based risk score model effectively predicted glioma outcomes and highlighted the role of disulfidptosis-related genes in tumor immunity. This study offers potential new avenues for glioma treatment by targeting disulfidptosis. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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