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Untargeted lipidomic features associated with colorectal cancer in a prospective cohort

BACKGROUND: Epidemiologists are beginning to employ metabolomics and lipidomics with archived blood from incident cases and controls to discover causes of cancer. Although several such studies have focused on colorectal cancer (CRC), they all followed targeted or semi-targeted designs that limited t...

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Autores principales: Perttula, Kelsi, Schiffman, Courtney, Edmands, William M B, Petrick, Lauren, Grigoryan, Hasmik, Cai, Xiaoming, Gunter, Marc J, Naccarati, Alessio, Polidoro, Silvia, Dudoit, Sandrine, Vineis, Paolo, Rappaport, Stephen M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194742/
https://www.ncbi.nlm.nih.gov/pubmed/30340609
http://dx.doi.org/10.1186/s12885-018-4894-4
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author Perttula, Kelsi
Schiffman, Courtney
Edmands, William M B
Petrick, Lauren
Grigoryan, Hasmik
Cai, Xiaoming
Gunter, Marc J
Naccarati, Alessio
Polidoro, Silvia
Dudoit, Sandrine
Vineis, Paolo
Rappaport, Stephen M
author_facet Perttula, Kelsi
Schiffman, Courtney
Edmands, William M B
Petrick, Lauren
Grigoryan, Hasmik
Cai, Xiaoming
Gunter, Marc J
Naccarati, Alessio
Polidoro, Silvia
Dudoit, Sandrine
Vineis, Paolo
Rappaport, Stephen M
author_sort Perttula, Kelsi
collection PubMed
description BACKGROUND: Epidemiologists are beginning to employ metabolomics and lipidomics with archived blood from incident cases and controls to discover causes of cancer. Although several such studies have focused on colorectal cancer (CRC), they all followed targeted or semi-targeted designs that limited their ability to find discriminating molecules and pathways related to the causes of CRC. METHODS: Using an untargeted design, we measured lipophilic metabolites in prediagnostic serum from 66 CRC patients and 66 matched controls from the European Prospective Investigation into Cancer and Nutrition (Turin, Italy). Samples were analyzed by liquid chromatography-high-resolution mass spectrometry (LC-MS), resulting in 8690 features for statistical analysis. RESULTS: Rather than the usual multiple-hypothesis-testing approach, we based variable selection on an ensemble of regression methods, which found nine features to be associated with case-control status. We then regressed each selected feature on time-to-diagnosis to determine whether the feature was likely to be either a potentially causal biomarker or a reactive product of disease progression (reverse causality). CONCLUSIONS: Of the nine selected LC-MS features, four appear to be involved in CRC etiology and merit further investigation in prospective studies of CRC. Four other features appear to be related to progression of the disease (reverse causality), and may represent biomarkers of value for early detection of CRC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4894-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-61947422018-10-30 Untargeted lipidomic features associated with colorectal cancer in a prospective cohort Perttula, Kelsi Schiffman, Courtney Edmands, William M B Petrick, Lauren Grigoryan, Hasmik Cai, Xiaoming Gunter, Marc J Naccarati, Alessio Polidoro, Silvia Dudoit, Sandrine Vineis, Paolo Rappaport, Stephen M BMC Cancer Research Article BACKGROUND: Epidemiologists are beginning to employ metabolomics and lipidomics with archived blood from incident cases and controls to discover causes of cancer. Although several such studies have focused on colorectal cancer (CRC), they all followed targeted or semi-targeted designs that limited their ability to find discriminating molecules and pathways related to the causes of CRC. METHODS: Using an untargeted design, we measured lipophilic metabolites in prediagnostic serum from 66 CRC patients and 66 matched controls from the European Prospective Investigation into Cancer and Nutrition (Turin, Italy). Samples were analyzed by liquid chromatography-high-resolution mass spectrometry (LC-MS), resulting in 8690 features for statistical analysis. RESULTS: Rather than the usual multiple-hypothesis-testing approach, we based variable selection on an ensemble of regression methods, which found nine features to be associated with case-control status. We then regressed each selected feature on time-to-diagnosis to determine whether the feature was likely to be either a potentially causal biomarker or a reactive product of disease progression (reverse causality). CONCLUSIONS: Of the nine selected LC-MS features, four appear to be involved in CRC etiology and merit further investigation in prospective studies of CRC. Four other features appear to be related to progression of the disease (reverse causality), and may represent biomarkers of value for early detection of CRC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4894-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-19 /pmc/articles/PMC6194742/ /pubmed/30340609 http://dx.doi.org/10.1186/s12885-018-4894-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Perttula, Kelsi
Schiffman, Courtney
Edmands, William M B
Petrick, Lauren
Grigoryan, Hasmik
Cai, Xiaoming
Gunter, Marc J
Naccarati, Alessio
Polidoro, Silvia
Dudoit, Sandrine
Vineis, Paolo
Rappaport, Stephen M
Untargeted lipidomic features associated with colorectal cancer in a prospective cohort
title Untargeted lipidomic features associated with colorectal cancer in a prospective cohort
title_full Untargeted lipidomic features associated with colorectal cancer in a prospective cohort
title_fullStr Untargeted lipidomic features associated with colorectal cancer in a prospective cohort
title_full_unstemmed Untargeted lipidomic features associated with colorectal cancer in a prospective cohort
title_short Untargeted lipidomic features associated with colorectal cancer in a prospective cohort
title_sort untargeted lipidomic features associated with colorectal cancer in a prospective cohort
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194742/
https://www.ncbi.nlm.nih.gov/pubmed/30340609
http://dx.doi.org/10.1186/s12885-018-4894-4
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