Urinary Volatilomic Profiling Reveals Candidate Metabolomic Signatures Associated with Colorectal Cancer

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, largely due to delayed diagnosis. Current screening approaches are limited by invasiveness, cost, and low patient adherence, underscoring the urgent need for non-invasive biomarkers that could complement the existing strategies. Cancer-associated metabolic reprogramming, together with alterations in host–microbiota interactions, is reflected in the urinary volatilome, offering a potential source of candidate biomarkers. In this exploratory, case–control pilot study, urinary volatile organic metabolites (VOMs) were profiled in patients with colorectal cancer (CRC, n = 19) and healthy controls (HCs, n = 17) using headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS). Univariate and multivariate statistical modelling was applied to characterize disease-associated metabolic patterns. Sixty-seven urinary VOMs were identified, with terpenoids, ketones, phenolic compounds and norisoprenoids representing the predominant chemical classes. Following participant-level analysis and correction for multiple comparisons, 18 VOMs remained statistically significant between the two groups, consistent with metabolic perturbations previously associated with colorectal carcinogenesis, including gut microbial dysbiosis, oxidative stress, lipid peroxidation, chronic inflammation and altered energy metabolism. Orthogonal partial least squares-discriminant analysis (OPLS-DA), validated with participant-level cross-validation and 1000 permutations, revealed a separation between CRC and HC groups, supporting the existence of a disease-associated urinary volatilomic profile. Notably, one participant initially classified as an HC was subsequently diagnosed with metastatic CRC. This participant clustered with the CRC group in an unsupervised analysis performed using the original group label, without knowledge of the later diagnosis, raising the hypothesis, to be confirmed in a prospective cohort, that urinary volatilomic alterations may be detectable before clinical diagnosis. Our findings indicate that urinary volatilomic profiling captures metabolic changes associated with CRC and represents a promising, hypothesis-generating starting point for non-invasive biomarker discovery.