Identification of TRIM59 as a Key Biomarker for Ferroptosis Resistance and Immunotherapy Response in Bladder Cancer via Multi-Omics Integration and Machine Learning.

Background: Bladder cancer (BCa) is a highly heterogeneous malignancy, and precision treatment remains challenging. Identifying molecular biomarkers and risk factors is essential for improving prognosis and therapeutic strategies.

Methods: We integrated expression quantitative trait loci (eQTL) data with Mendelian randomization (MR) analysis to identify candidate risk genes associated with BCa. Subsequently, a prognostic risk model was developed using machine learning methods to explore its correlation with molecular features, immune cell infiltration, and ferroptosis-related pathways. Based on these findings, the Tripartite Motif Containing 59 (TRIM59) protein was selected for further experimental validation. The functional role of TRIM59 in BCa progression was further investigated using MTT assays in BCa cell lines. Additionally, western blotting (WB) was conducted to confirm the potential association between TRIM59 expression and ferroptosis regulation.

Results: The risk model identified distinct signaling pathways that differentiate the high-risk and low-risk BCa groups. The low-risk group demonstrated greater infiltration of CD8+ T cells. Conversely, the high-risk group exhibited enhanced immune evasion, as evidenced by increased infiltration of macrophages and fibroblasts. Furthermore, TRIM59 exerts a regulatory influence on ferroptosis progression in BCa by modulating key genes involved in this process, including Solute Carrier Family 7 Member 11 (SLC7A11), Glutathione Peroxidase 4 (GPX4), and Acyl-CoA Synthetase Long Chain Family Member 4 (ACSL4).

Conclusion: Our integrative approach highlights the potential of genomic and immune microenvironment data in developing personalized risk models for BCa, offering insights into individualized treatment strategies. Importantly, TRIM59 is involved in ferroptosis resistance in BCa. These findings have potential implications for identifying diagnostic biomarkers and therapeutic targets for BCa treatment.