Multi-centre cross-validation study in the search for volatile colorectal cancer biomarkers in breath and faeces
Multi-centre cross-validation study in the search for volatile colorectal cancer biomarkers in breath and faeces
Pham Y1,2, van Vorstenbosch R3, Mametov R4, Smolinska A3, Ligor T4, van Schooten FJ3, Buszewski B4, Heinrich K5, Stintzing S5, Beauchamp J1
1. Department of Sensory Analytics; Fraunhofer IVV, Freising, Germany
2. Chair of Aroma and Smell Research, Department of Chemistry and Pharmacy; Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
3. Department of Pharmacology and Toxicology; NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands
4. Chair of Environmental Chemistry and Bioanalytics, Faculty of Chemistry; Nicolaus Copernicus University, Torun, Poland
5. Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
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Abstract:
Non-invasive diagnostic tools based on the detection of volatile biomarkers in exhaled breath have largely failed to reach the necessary maturity for practical use. Cross-validation of large cohorts between clinical and analytical centres is imperative for developing biomarker-related screening tests with high sensitivity, specificity and low false-positive rates. Our multi-centre study will explore the presence of disease-specific volatile organic compounds (VOCs) in exhaled breath and faeces headspace of colorectal cancer (CRC) sufferers in comparison to other bowel disorders and healthy controls. In the first phase of the project, standard operating procedures (SOPs) will be established to ensure optimum sampling and analysis of the two gas matrix types. Samples will be collected onto Tenax/Carbograph sorbent tubes using a ReCIVA device for exhaled breath and a micro-chamber/thermal extractor for stool headspace. VOCs will be analysed by thermal desorption-gas chromatography-mass spectrometry. The study design is unique in that sample replicates for each patient of each cohort will be analysed at each of the centres. The project aims at recruiting approximately 300 participants for each cohort to search for CRC-specific biomarker, followed by a validation in independent patient cohorts. Datasets will be pooled for data-mining and biomarker discovery using machine learning techniques. This poster outlines the cross-validation concept, the methods being employed, and intends to spark debate and seek additional advice on searching for CRC-specific volatile biomarkers.
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