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A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics

BACKGROUND: Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging. METHODS: Serum metabolomic profiles of ade...

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Autores principales: Farshidfar, Farshad, Weljie, Aalim M, Kopciuk, Karen A, Hilsden, Robert, McGregor, S Elizabeth, Buie, W Donald, MacLean, Anthony, Vogel, Hans J, Bathe, Oliver F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5046202/
https://www.ncbi.nlm.nih.gov/pubmed/27560555
http://dx.doi.org/10.1038/bjc.2016.243
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author Farshidfar, Farshad
Weljie, Aalim M
Kopciuk, Karen A
Hilsden, Robert
McGregor, S Elizabeth
Buie, W Donald
MacLean, Anthony
Vogel, Hans J
Bathe, Oliver F
author_facet Farshidfar, Farshad
Weljie, Aalim M
Kopciuk, Karen A
Hilsden, Robert
McGregor, S Elizabeth
Buie, W Donald
MacLean, Anthony
Vogel, Hans J
Bathe, Oliver F
author_sort Farshidfar, Farshad
collection PubMed
description BACKGROUND: Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging. METHODS: Serum metabolomic profiles of adenoma (N=31), various stages of CRC (N=320) and healthy matched controls (N=254) were analysed by gas chromatography-mass spectrometry (GC-MS). A diagnostic model for CRC was derived by orthogonal partial least squares-discriminant analysis (OPLS-DA) on a training set, and then validated on an independent data set. Metabolomic models suitable for identifying adenoma, poor prognosis stage II CRC and discriminating various stages were generated. RESULTS: A diagnostic signature for CRC with remarkable multivariate performance (R(2)Y=0.46, Q(2)Y=0.39) was constructed, and then validated (sensitivity 85% specificity 86%). Area under the receiver-operating characteristic curve was 0.91 (95% CI, 0.87–0.96). Adenomas were also detectable (R(2)Y=0.35, Q(2)Y=0.26, internal AUROC=0.81, 95% CI, 0.70–0.92). Also of particular interest, we identified models that stratified stage II by prognosis, and classified cases by stage. CONCLUSIONS: Using a single assay system, a suite of CRC biomarkers based on circulating metabolites enables early detection, prognostication and preliminary staging information. External population-based studies are required to evaluate the repeatability of our findings and to assess the clinical benefits of these biomarkers.
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spelling pubmed-50462022017-09-27 A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics Farshidfar, Farshad Weljie, Aalim M Kopciuk, Karen A Hilsden, Robert McGregor, S Elizabeth Buie, W Donald MacLean, Anthony Vogel, Hans J Bathe, Oliver F Br J Cancer Molecular Diagnostics BACKGROUND: Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging. METHODS: Serum metabolomic profiles of adenoma (N=31), various stages of CRC (N=320) and healthy matched controls (N=254) were analysed by gas chromatography-mass spectrometry (GC-MS). A diagnostic model for CRC was derived by orthogonal partial least squares-discriminant analysis (OPLS-DA) on a training set, and then validated on an independent data set. Metabolomic models suitable for identifying adenoma, poor prognosis stage II CRC and discriminating various stages were generated. RESULTS: A diagnostic signature for CRC with remarkable multivariate performance (R(2)Y=0.46, Q(2)Y=0.39) was constructed, and then validated (sensitivity 85% specificity 86%). Area under the receiver-operating characteristic curve was 0.91 (95% CI, 0.87–0.96). Adenomas were also detectable (R(2)Y=0.35, Q(2)Y=0.26, internal AUROC=0.81, 95% CI, 0.70–0.92). Also of particular interest, we identified models that stratified stage II by prognosis, and classified cases by stage. CONCLUSIONS: Using a single assay system, a suite of CRC biomarkers based on circulating metabolites enables early detection, prognostication and preliminary staging information. External population-based studies are required to evaluate the repeatability of our findings and to assess the clinical benefits of these biomarkers. Nature Publishing Group 2016-09-27 2016-08-25 /pmc/articles/PMC5046202/ /pubmed/27560555 http://dx.doi.org/10.1038/bjc.2016.243 Text en Copyright © 2016 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Molecular Diagnostics
Farshidfar, Farshad
Weljie, Aalim M
Kopciuk, Karen A
Hilsden, Robert
McGregor, S Elizabeth
Buie, W Donald
MacLean, Anthony
Vogel, Hans J
Bathe, Oliver F
A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
title A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
title_full A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
title_fullStr A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
title_full_unstemmed A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
title_short A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
title_sort validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
topic Molecular Diagnostics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5046202/
https://www.ncbi.nlm.nih.gov/pubmed/27560555
http://dx.doi.org/10.1038/bjc.2016.243
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