Non-invasive fecal metabonomic detection of colorectal cancer

Colorectal cancer: the potential of metabolic fingerprinting

Metabolomics is a relatively new omics science that can provide a strong individual small-molecule fingerprint. Disease onset can be monitored as a deviation from the normal healthy fingerprint at the systemic level or in tissues from the diseased organ(s). By applying mass spectrometry and nuclear magnetic resonance as analytical platforms, metabolomics has been used for colorectal cancer phenotyping at different levels. The metabolic profile as a whole is a complex biomarker of diagnostic and prognostic value. Results are promising for the implementation of the method at the clinical level, but larger scale studies and extensive standardization of the pre-analytical phase are needed for a validated definition of the colorectal cancer signature.

Novel methodologies in analysis of small molecule biomarkers and living cells

Enzyme-linked immuno-sorbent assay (ELISA) is widely used for biomarker detection. A good biomarker can distinguish patients from healthy or benign diseases. However, the ELISA method is not suitable for small molecule or trace substance detection. Along with the development of new technologies, an increasing level of biomaterials, especially small molecules, will be identified as novel biomarkers. Quantitative immuno-PCR, chromatography-mass spectrometry, and nucleic acid aptamer are emerging methodologies for detection of small molecule biomarkers, even in living cells. In this review, we focus on these novel technologies and their potential for small molecule biomarkers and living cell analysis.

Fecal metabolomics: assay performance and association with colorectal cancer

Metabolomic analysis of feces may provide insights on colorectal cancer (CRC) if assay performance is satisfactory. In lyophilized feces from 48 CRC cases, 102 matched controls, and 48 masked quality control specimens, 1043 small molecules were detected with a commercial platform. Assay reproducibility was good for 527 metabolites [technical intraclass correlation coefficient (ICC) >0.7 in quality control specimens], but reproducibility in 6-month paired specimens was lower for the majority of metabolites (within-subject ICC ≤0.5). In the CRC cases and controls, significant differences (false discovery rate ≤0.10) were found for 41 of 1043 fecal metabolites. Direct cancer association was found with three fecal heme-related molecules [covariate-adjusted 90th versus 10th percentile odds ratio (OR) = 17-345], 18 peptides/amino acids (OR = 3-14), palmitoyl-sphingomyelin (OR = 14), mandelate (OR = 3) and p-hydroxy-benzaldehyde (OR = 4). Conversely, cancer association was inverse with acetaminophen metabolites (OR <0.1), tocopherols (OR = 0.3), sitostanol (OR = 0.2), 3-dehydrocarnitine (OR = 0.4), pterin (OR = 0.3), conjugated-linoleate-18-2N7 (OR = 0.2), N-2-furoyl-glycine (OR = 0.3) and p-aminobenzoate (PABA, OR = 0.2). Correlations suggested an independent role for palmitoyl-sphingomyelin and a central role for PABA (which was stable over 6 months, within-subject ICC 0.67) modulated by p-hydroxy-benzaldehyde. Power calculations based on ICCs indicate that only 45% of metabolites with a true relative risk 5.0 would be found in prospectively collected, prediagnostic specimens from 500 cases and 500 controls. Thus, because fecal metabolites vary over time, very large studies will be needed to reliably detect associations of many metabolites that potentially contribute to CRC.