Non–muscle-invasive bladder cancer (NMIBC) accounts for approximately 75% of bladder cancer cases and, despite a generally favorable prognosis, requires lifelong cystoscopic surveillance, resulting in substantial clinical burden. Non-invasive biomarkers with metabolic and translational relevance are needed to improve disease detection and patient stratification. Plasma represents a stable systemic matrix that captures tumor-associated metabolic alterations while minimizing pre-analytical variability. Targeted metabolomic profiling of 630 metabolites and 252 metabolic indicators was performed in plasma samples from 249 individuals, including 51 patients with NMIBC and 198 control individuals. Integrated univariate and multivariate analyses were used to identify discriminant metabolites, assess pathway-level perturbations, and develop diagnostic models. Model robustness was evaluated with respect to hematuria status. A total of 29 metabolites and 17 metabolic indicators were significantly altered in NMIBC. The dominant metabolic signature involved lipid and bile acid metabolism, characterized by reduced conjugated bile acids and increased lysophosphatidylcholines and polyunsaturated fatty acid species. Pathway enrichment analysis indicated perturbations in bile acid biosynthesis, PUFA turnover, glutathione metabolism, and glycolytic pathways. A diagnostic model based on 11 metabolites achieved high accuracy (AUC = 0.92 in the training set and 0.88 in the test set). Hematuria status did not affect clustering or model performance. Plasma metabolomic profiling identifies a systemic metabolic signature associated with lipid and bile acid dysregulation in NMIBC and supports the development of clinically applicable, non-invasive plasma-based approaches for bladder cancer detection and patient stratification. Further validation in independent and longitudinal cohorts is warranted.
Speziale et al. (2026) studied this question.