1. Prognostic model based on disulfidptosis-related lncRNAs for predicting survival and therapeutic response in bladder cancer
- Author
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Lirui Han, Hankai Yang, Xuan Jiang, Ziyu Zhou, Chang Ge, Kairan Yu, Guofang Li, Wei Wang, and Yubo Liu
- Subjects
disulfidptosis ,bladder cancer ,long non-coding RNA ,machine learning ,prognosis ,Immunologic diseases. Allergy ,RC581-607 - Abstract
BackgroundWith poor treatment outcomes and prognosis, bladder cancer remains a focus for clinical research in the precision oncology era. However, the potential of disulfidptosis, a novel cell death mechanism, and its related long non-coding RNAs to support selective cancer cell killing in this disease is still unclear.MethodsWe identified key disulfidptosis-related lncRNAs in bladder cancer, constructed a prognostic risk model with potential therapeutic targets, and confirmed the findings through quantitative PCR analysis.ResultsWe identified five crucial lncRNAs (AC005840.4, AC010331.1, AL021707.6, MIR4435-2HG and ARHGAP5-AS1) and integrated them into a predictive model centered on disulfidptosis-associated lncRNAs. Reliability and validity tests demonstrated that the lncRNA prediction index associated with disulfidptosis effectively discerns patients’ prognosis outcomes. Additionally, high-risk patients exhibited elevated expression levels of genes involved in the PI3K-Akt signaling pathway, extracellular matrix organization, and immune escape mechanisms, which are associated with poor prognosis. Notably, high-risk patients demonstrated higher sensitivity to Sorafenib, Oxaliplatin and MK-2206, underscoring the promise of these lncRNAs as precise therapeutic targets in bladder cancer.ConclusionBy revealing the predictive importance of disulfidptosis-associated lncRNAs in bladder cancer, our research offers new perspectives and pinpoints potential therapeutic targets in clinical environments.
- Published
- 2024
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