Creation of signatures and identification of molecular subtypes of glioblastoma based on disulfidptosis-related genes for predicting patient prognosis and immunological activity

• DOI: 10.1016/j.asjsur.2024.02.041
• Publication Date: 2024-03-11T02:36:58Z
• Authors: Dongjun Li; Xiaodong Li; Jianfeng Lv; Shaoyi Li
• Keywords: 0303 health sciences; 03 medical and health sciences; Risk score model; RD1-811; Surgery; Disulfidptosis; Unsupervised clustering; Glioblastoma; Programmed cell death

In recent times, disulfidptosis, an intricate form of cellular demise, has garnered attention due to its impact on prognosis, tumor progression and treatment response. Nevertheless, the exact significance disulfidptosis-related genes (DisRGs) in glioblastoma (GBM) remains enigmatic. The GEO TCGA databases provided transcriptional clinically relevant data samples, while GTEx database healthy tissues. Disulfidptosis-related were procured from previous scholarly investigations. expression profile DisRGs was initially scrutinized among patients diagnosed with GBM, subsequent which their prognostic value explored. Through consensus clustering, we constructed DisRGs-related clusters gene subtypes. Our results established that DisRG-related had differentially expressed genes, resulting a DisulfidptosisScore model, positive value. differential 24 between GBM samples acquired. cluster analysis, two distinct disulfidptosis subtypes, namely DisRGcluster A B, identified. Then, model including 4 characteristic constructed.Notably, assigned lower score demonstrated considerably longer overall survival (OS) compared those higher score. We have effectively devised associated presenting autonomous predictions for GBM. These findings serve as valuable addition current comprehension offer fresh theoretical substantiation development enhanced strategies.