Prognostic significance of copper metabolism-related genes as risk markers in bladder urothelial carcinoma

Bladder urothelial carcinoma (BLCA), a prevalent malignant neoplasm affecting the human urinary system, is frequently linked with an unfavorable prognosis in a significant proportion of individuals. More effective and sensitive markers are needed to provide a reference for prognostic judgment. We obtained RNA sequencing data and clinical information of individuals from TCGA, and 133 copper metabolism-related genes from literature. Prognostic genes were evaluated by univariate/multivariate Cox regression analysis and LASSO analysis, and a risk-scoring model was established and validated in the GEO dataset. The CIBERSORT method was utilized to explore immune cell infiltration in BLCA individuals. In addition, tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) were utilized to verify whether the model can foretell the response of BLCA individuals to immunotherapy. We successfully constructed an 8-gene risk scoring model to foretell individuals' overall survival, and the model performed well in TCGA training and GEO validation cohorts. Lastly, a nomogram containing clinical parameters and risk scores was constructed to help individualized result prediction for individuals. Calibration curves demonstrated a high degree of concordance between the observed and projected survival durations, attesting to its exceptional predictive accuracy. Analysis utilizing CIBERSORT unveiled elevated levels of immune cell infiltration in individuals classified as low risk. TIDE and IPS analyses substantiated that low-risk individuals exhibited a more favorable response to immunotherapy. In summary, the model held immense potential for stratifying the risk of survival and guiding tailored treatment approaches for individuals with BLCA, thereby offering valuable insights for personalized therapeutic interventions.