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Cancers 2018, 10(9), 300;

Targeted UPLC-MS Metabolic Analysis of Human Faeces Reveals Novel Low-Invasive Candidate Markers for Colorectal Cancer

Department of Gastroenterology, Complexo Hospitalario Universitario de Ourense, Instituto de Investigación Biomédica Ourense-Vigo-Pontevedra, 32005 Ourense, Spain
Exosomes Laboratory, CIC bioGUNE, CIBERehd, Bizkaia Technology Park, Derio, 48160 Bizkaia, Spain
Department of Gastroenterology, Hospital Donostia/Instituto Biodonostia, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Universidad del País Vasco (UPV/EHU), 20014 San Sebastián, Spain
OWL Metabolomics, Bizkaia Technology Park, Derio, 48160 Bizkaia, Spain
GAIKER-IK4 Technology Centre, Ed. 202, 48170 Zamudio, Spain
Gastrointestinal Genetics Unit, Biodonostia HRI, 20014 San Sebastián, Spain
IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain
Metabolomics Platform, CIC bioGUNE, CIBERehd, Bizkaia Technology Park, Derio, 48160 Bizkaia, Spain
Joaquin Cubiella and Marc Clos-Garcia shared first authorship.
Authors to whom correspondence should be addressed.
Received: 11 July 2018 / Revised: 2 August 2018 / Accepted: 28 August 2018 / Published: 1 September 2018
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Low invasive tests with high sensitivity for colorectal cancer and advanced precancerous lesions will increase adherence rates, and improve clinical outcomes. We have performed an ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-(TOF) MS)-based metabolomics study to identify faecal biomarkers for the detection of patients with advanced neoplasia. A cohort of 80 patients with advanced neoplasia (40 advanced adenomas and 40 colorectal cancers) and 49 healthy subjects were analysed in the study. We evaluated the faecal levels of 105 metabolites including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. We found 18 metabolites that were significantly altered in patients with advanced neoplasia compared to controls. The combinations of seven metabolites including ChoE(18:1), ChoE(18:2), ChoE(20:4), PE(16:0/18:1), SM(d18:1/23:0), SM(42:3) and TG(54:1), discriminated advanced neoplasia patients from healthy controls. These seven metabolites were employed to construct a predictive model that provides an area under the curve (AUC) median value of 0.821. The inclusion of faecal haemoglobin concentration in the metabolomics signature improved the predictive model to an AUC of 0.885. In silico gene expression analysis of tumour tissue supports our results and puts the differentially expressed metabolites into biological context, showing that glycerolipids and sphingolipids metabolism and GPI-anchor biosynthesis pathways may play a role in tumour progression. View Full-Text
Keywords: colorectal cancer; metabolomics; faecal samples; biomarkers colorectal cancer; metabolomics; faecal samples; biomarkers

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Cubiella, J.; Clos-Garcia, M.; Alonso, C.; Martinez-Arranz, I.; Perez-Cormenzana, M.; Barrenetxea, Z.; Berganza, J.; Rodríguez-Llopis, I.; D’Amato, M.; Bujanda, L.; Diaz-Ondina, M.; Falcón-Pérez, J.M. Targeted UPLC-MS Metabolic Analysis of Human Faeces Reveals Novel Low-Invasive Candidate Markers for Colorectal Cancer. Cancers 2018, 10, 300.

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