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NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as...

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Autores principales: Lin, Yan, Ma, Changchun, Liu, Chengkang, Wang, Zhening, Yang, Jurong, Liu, Xinmu, Shen, Zhiwei, Wu, Renhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045409/
https://www.ncbi.nlm.nih.gov/pubmed/27107423
http://dx.doi.org/10.18632/oncotarget.8762
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author Lin, Yan
Ma, Changchun
Liu, Chengkang
Wang, Zhening
Yang, Jurong
Liu, Xinmu
Shen, Zhiwei
Wu, Renhua
author_facet Lin, Yan
Ma, Changchun
Liu, Chengkang
Wang, Zhening
Yang, Jurong
Liu, Xinmu
Shen, Zhiwei
Wu, Renhua
author_sort Lin, Yan
collection PubMed
description Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy ((1)HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on (1)H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients.
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spelling pubmed-50454092016-10-13 NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer Lin, Yan Ma, Changchun Liu, Chengkang Wang, Zhening Yang, Jurong Liu, Xinmu Shen, Zhiwei Wu, Renhua Oncotarget Research Paper Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy ((1)HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on (1)H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients. Impact Journals LLC 2016-04-16 /pmc/articles/PMC5045409/ /pubmed/27107423 http://dx.doi.org/10.18632/oncotarget.8762 Text en Copyright: © 2016 Lin et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Lin, Yan
Ma, Changchun
Liu, Chengkang
Wang, Zhening
Yang, Jurong
Liu, Xinmu
Shen, Zhiwei
Wu, Renhua
NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
title NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
title_full NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
title_fullStr NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
title_full_unstemmed NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
title_short NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
title_sort nmr-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045409/
https://www.ncbi.nlm.nih.gov/pubmed/27107423
http://dx.doi.org/10.18632/oncotarget.8762
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