Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework - Zhao, Songyun; Wang, Lanyu; Ding, Wei; Ye, Bicheng; Cheng, Chao; Shao, Jianfeng; Liu, Jinhui; Zhou, Hongyi (Frontiers in Endocrinology, 2023)
Background: Bladder cancer (BLCA) is is the most common malignancy of the urinary tract. On the other hand, disulfidptosis, a mechanism of disulfide stress-induced cell death, is closely associated with tumorigenesis and progression. Here, we investigated the impact of genes associated with disulfidptosis (DRGs) on the prognosis of BLCA, identified various DRG clusters and developed a risk model to assess patient prognosis, immunological profile and treatment response. Methods: After analyzing the expression and mutational characteristics of four DRGs in bulk RNA-Seq and single-cell data, we identified two DRG clusters through consensus clustering. Using differentially expressed genes in the two clusters, we transformed ten machine learning algorithms into over 80 combinations, ultimately selecting the optimal algorithm to construct a prognostic signature called DRPS that is related to disulfidptosis. We based this selection on the mean C-index of three BLCA cohorts. Furthermore, we explored the differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between high and low-risk groups. To visually depict the clinical value of DRPS, we employed nomograms. Additionally, we verified whether DRPS predicts response to immunotherapy in BLCA patients by utilizing the Tumour Immune Dysfunction and Rejection (TIDE) and IMvigor 210 cohorts. Results:In the integrated cohort, we identified several DRG clusters and DRG gene clusters that differed significantly in overall survival (OS) and tumour microenvironment. After integration of clinicopathological features, DRPS showed robust predictive power. Based on the median risk score associated with disulfidptosis, BLCA patients were divided into low risk (LR) and high risk (HR) groups, with patients in the LR group having a better prognosis, a higher tumour mutational load and being more sensitive to immunotherapy and chemotherapy. Conclusion: Our study therefore provides a valuable tool to further guide clinical management and tailor treatment of BLCA patients, offering new insights into individualised treatment.