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Abstract
Disulfidptosis is a novel programmed cell death mode that has been reported to play a role in oncogenesis. Increasing evidences suggest that the long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of bladder cancer (BLCA). However, the role and prognostic value of disulfidptosis-related lncRNAs in BLCA remain unknown.The aim of this study was to construct and validate a disulfidptosis-related lncRNA risk model for predicting the prognosis of BLCA patients. A risk model consisting of 5 disulfidptosis-related lncRNAs was developed to predict the prognosis of BLCA patients. The overall survival (OS) of BLCA patients in the high-risk group was significantly shorter than that in the low-risk group (P < 0.05). The effectiveness of this model was validated using the receiver operating characteristic (ROC) curve analysis, and this model proved superior in prognostic accuracy compared with other clinical features. Furthermore, the tumor immune dysfunction and exclusion (TIDE) score in the high-risk group was significantly higher than that in the low-risk group, suggesting that the high-risk group had a less favorable response to immunotherapy. Simultaneously, patients in the low-risk group exhibited significantly higher sensitivity to CTLA-4 monoclonal antibody therapy compared to those in the high-risk group, suggesting potential benefits of immunotherapy for patients in the low-risk group. The combination of high risk and low tumor mutational burden (TMB) could further shortened the OS of BLCA patients. Lastly, the drug sensitivity analysis revealed that the BLCA cells in the high-risk group showed an increased sensitivity to cisplatin, sunitinib, cetuximab, axitinib, docetaxel, saracatinib, vinblastine and pazopanib compared with those in the low-risk group. According to the Quantitative real time PCR results, we found that five lncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line. The disulfidptosis-related lncRNA risk model has a valuable effect in assessing the prognosis of BLCA patients.
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Details
1 Medical School of Nantong University, Nantong, China (GRID:grid.260483.b) (ISNI:0000 0000 9530 8833)
2 Nantong Tumor Hospital, Affiliated Tumor Hospital of Nantong University, Cancer Research Center, Nantong, China (GRID:grid.410730.1) (ISNI:0000 0004 1799 4363)
3 Nantong Third People’s Hospital, Affiliated Nantong Hospital 3 of Nantong University, Department of Pathology, Nantong, China (GRID:grid.260483.b) (ISNI:0000 0000 9530 8833)