Frontiers in Cell and Developmental Biology (Sep 2024)
Integrating oxidative-stress biomarkers into a precision oncology risk-stratification model for bladder cancer prognosis and therapy
Abstract
IntroductionBladder cancer is a common malignant tumor with significant heterogeneity, making personalized risk stratification crucial for optimizing treatment and prognosis. This study aimed to develop a prognostic model based on oxidative stress-related genes to guide risk assessment in bladder cancer.MethodsDifferentially expressed oxidative stress-related genes were identified using the GEO database. Functional enrichment and survival analyses were performed on these genes. A risk-scoring model was built and tested for prognostic value and therapeutic response prediction. Expression of key genes was validated by qRT-PCR in samples from two muscle-invasive and two non-muscle-invasive bladder cancer patients.ResultsSeveral oxidative stress-related genes were identified as significantly associated with survival. The risk-scoring model stratified patients into high- and low-risk groups, accurately predicting prognosis and therapeutic responses. qRT-PCR confirmed the differential expression of key genes in patient samples.DiscussionThe study provides a concise risk stratification model based on oxidative stress-related genes, offering a practical tool for improving personalized treatment in bladder cancer. Further validation is required for broader clinical application.
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