Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its etiopathogenesis and earlier diagnosis. Here, we investigated the fecal metabolic phenotype of patients with advanced colorectal neoplasia and controls using (1)H-nuclear magnetic resonance (NMR) spectroscopy and multivariate modeling. The fecal microbiota composition was assessed by quantitative real-time PCR as well as Wif-1 methylation levels in stools, serum, and urine and correlated to the metabolic profile of each patient. The predictivity of the model was 0.507 (Q(2)Y), and the explained variance was 0.755 (R(2)Y). Patients with advanced colorectal neoplasia demonstrated increased fecal concentrations of four short-chain fatty acids (valerate, acetate, propionate, and butyrate) and decreased signals relating to β-glucose, glutamine, and glutamate. The predictive accuracy of the multivariate (1)H NMR model was higher than that of the guaiac-fecal occult blood test and the Wif-1 methylation test for predicting advanced colorectal neoplasia. Correlation analysis between fecal metabolites and bacterial profiles revealed strong associations between Faecalibacterium prausnitzii and Clostridium leptum species with short-chain fatty acids concentration and inverse correlation between Faecalibacterium prausnitzii and glucose. These preliminary results suggest that fecal metabonomics may potentially have a future role in a noninvasive colorectal screening program and may contribute to our understanding of the role of these dysregulated molecules in the cross-talk between the host and its bacterial microbiota.
Keywords: 1H NMR; advanced colorectal neoplasia; colorectal cancer; metabonomics.