Urinary Metabolomics in Bladder Cancer: A Scoping Review of Current Evidence and Translation Implications

Bladder cancer (BC) diagnosis and surveillance currently rely largely on invasive cystoscopy, making urine an attractive non-invasive biofluid for discovering metabolic biomarkers, given its direct contact with the bladder urothelium. This review provides a comprehensive and critical synthesis of the literature on urinary metabolomic profiling in BC, summarising metabolites and metabolite panels associated with the disease, their relevant metabolic pathways, and diagnostic performance. A search was conducted in PubMed, complemented by records from reference lists of relevant reviews. After screening, 30 original studies comparing urinary metabolomic profiles between BC patients and cancer-free controls were included, encompassing diverse analytical platforms and statistical approaches. A wide range of urinary metabolites were reported to be altered between BC patients and controls, of which 52 were recurrently identified in at least two independent studies. Increased levels of taurine, valine, lactate, adenosine monophosphate and adipate were among the most consistent metabolic alterations, whereas the levels of citrate, glycerol, creatinine, and several dicarboxylic acids and acylcarnitines were consistently decreased. Other metabolites, such as hippurate, tyrosine, and histidine, showed variable trends in their levels. These alterations may reflect metabolic processes associated with tumour growth, energy reprogramming, lipid metabolism, and oxidative stress adaptation. Most studies also proposed multi-metabolite panels combining metabolites to discriminate BC patients from controls, achieving sensitivity and specificity up to 100% and AUC up to 0.983, while fewer studies explored panels for tumour stage and grade discrimination, with more modest performance. Overall, urinary metabolomics reveals a broad, biologically coherent set of metabolic alterations associated with BC, but methodological heterogeneity and limited independent validation still hinder clinical translation. Larger, harmonised, prospectively validated studies integrating multi-omics and machine learning are needed to establish robust urinary biomarkers for BC.