This review discusses biomarkers in urothelial carcinoma, highlighting their role in diagnosis and treatment, while addressing AI's potential in biomarker discovery.
Urothelial carcinoma (UC) is marked by significant molecular heterogeneity and this complexity challenges precision medicine. Recent advances have improved biomarker development for UC diagnosis, prognosis and treatment. This review discusses established and emerging biomarkers in UC, including FGFR3 and HER2 alterations, PD-L1 expression and circulating tumor DNA (ctDNA). It also summarizes novel biomarkers such as Nectin-4, TROP-2, HER3, tumor mutational burden (TMB), and interferon-gamma signatures. The expanding role of artificial intelligence in biomarker discovery and interpretation is also addressed. Current literature was reviewed by a systematic search using PubMed, focusing on high-impact clinical trials, guidelines and recent reviews published up to May 2025. Despite advances, clinical implementation of biomarkers in UC is limited by methodological inconsistencies and lack of standardization. Robust clinical trials and multi-modal approaches, including liquid biopsy, tissue analysis, and AI-driven tools, will be essential to advance precision oncology in UC.
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Membribes et al. (2025) studied this question.
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