Urinary metabolomics is a promising field in non-invasive oncology; however, pre-analytical variability and difficulty in achieving tumour specificity often hinder the transition from discovery to clinical application. This study presents a validated high-resolution liquid chromatography–mass spectrometry (LC-HRMS) workflow designed to overcome matrix-induced biases and distinguish bladder cancer (BCa) signatures.

To maximize metabolomic panels, including tryptophan–kynurenine metabolites and the carnitine shuttle system, our methodology employs a systematically optimized extraction protocol (methanol-based protein precipitation, 2:1 v/v). High analytical stability was shown in the first validation of a demographically matched cohort (n = 50), with tight quality control (QC) clustering in unsupervised multivariate analysis (PCA). Significant dysregulation in proteolytic activity and membrane lipid remodeling specific to the BCa microenvironment was found.

The study was extended to include a pilot pan-cancer sub-cohort that examined metabolic profiles in patients with gastrointestinal tumors, gynecological cancers, and prostate cancer in order to further evaluate the diagnostic specificity of these markers. According to preliminary comparative analysis, specific kynurenine-to-tryptophan ratios and acylated carnitine profiles offer a distinguishing fingerprint for urothelial-specific pathologies, while other metabolic changes reflect systemic oncogenic stress, with opportunities for metabolic overlap determining between synchronous tumors in patients with multiple primary malignancies.

The current analytical approach facilitates the shift to personalized diagnostic approaches in genitourinary oncology, offering a basis for the development of high-throughput, non-invasive screening.