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Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality rate due to its poor diagnosis in the early stage. Here, we report a urinary metabolomic study on a cohort of CRC patients (n =67) and healthy controls (n =21) using ultraperformance liquid chromatography tripl...

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Autores principales: Zhu, Chang, Huang, Fengjie, Li, Yang, Zhu, Chaowei, Zhou, Kejun, Xie, Haihui, Xia, Ligang, Xie, Guoxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9064491/
https://www.ncbi.nlm.nih.gov/pubmed/35521635
http://dx.doi.org/10.1155/2022/1758113
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author Zhu, Chang
Huang, Fengjie
Li, Yang
Zhu, Chaowei
Zhou, Kejun
Xie, Haihui
Xia, Ligang
Xie, Guoxiang
author_facet Zhu, Chang
Huang, Fengjie
Li, Yang
Zhu, Chaowei
Zhou, Kejun
Xie, Haihui
Xia, Ligang
Xie, Guoxiang
author_sort Zhu, Chang
collection PubMed
description Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality rate due to its poor diagnosis in the early stage. Here, we report a urinary metabolomic study on a cohort of CRC patients (n =67) and healthy controls (n =21) using ultraperformance liquid chromatography triple quadrupole mass spectrometry. Pathway analysis showed that a series of pathways that belong to amino acid metabolism, carbohydrate metabolism, and lipid metabolism were dysregulated, for instance the glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, glycolysis, and TCA cycle. A total of 48 differential metabolites were identified in CRC compared to controls. A panel of 12 biomarkers composed of chenodeoxycholic acid, vanillic acid, adenosine monophosphate, glycolic acid, histidine, azelaic acid, hydroxypropionic acid, glycine, 3,4-dihydroxymandelic acid, 4-hydroxybenzoic acid, oxoglutaric acid, and homocitrulline were identified by Random Forest (RF), Support Vector Machine (SVM), and Boruta analysis classification model and validated by Gradient Boosting (GB), Logistic Regression (LR), and Random Forest diagnostic model, which were able to discriminate CRC subjects from healthy controls. These urinary metabolic biomarkers provided a novel and promising molecular approach for the early diagnosis of CRC.
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spelling pubmed-90644912022-05-04 Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer Zhu, Chang Huang, Fengjie Li, Yang Zhu, Chaowei Zhou, Kejun Xie, Haihui Xia, Ligang Xie, Guoxiang Dis Markers Research Article Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality rate due to its poor diagnosis in the early stage. Here, we report a urinary metabolomic study on a cohort of CRC patients (n =67) and healthy controls (n =21) using ultraperformance liquid chromatography triple quadrupole mass spectrometry. Pathway analysis showed that a series of pathways that belong to amino acid metabolism, carbohydrate metabolism, and lipid metabolism were dysregulated, for instance the glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, glycolysis, and TCA cycle. A total of 48 differential metabolites were identified in CRC compared to controls. A panel of 12 biomarkers composed of chenodeoxycholic acid, vanillic acid, adenosine monophosphate, glycolic acid, histidine, azelaic acid, hydroxypropionic acid, glycine, 3,4-dihydroxymandelic acid, 4-hydroxybenzoic acid, oxoglutaric acid, and homocitrulline were identified by Random Forest (RF), Support Vector Machine (SVM), and Boruta analysis classification model and validated by Gradient Boosting (GB), Logistic Regression (LR), and Random Forest diagnostic model, which were able to discriminate CRC subjects from healthy controls. These urinary metabolic biomarkers provided a novel and promising molecular approach for the early diagnosis of CRC. Hindawi 2022-04-26 /pmc/articles/PMC9064491/ /pubmed/35521635 http://dx.doi.org/10.1155/2022/1758113 Text en Copyright © 2022 Chang Zhu et al. https://creativecommons.org/licenses/by/4.0/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.
spellingShingle Research Article
Zhu, Chang
Huang, Fengjie
Li, Yang
Zhu, Chaowei
Zhou, Kejun
Xie, Haihui
Xia, Ligang
Xie, Guoxiang
Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer
title Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer
title_full Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer
title_fullStr Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer
title_full_unstemmed Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer
title_short Distinct Urinary Metabolic Biomarkers of Human Colorectal Cancer
title_sort distinct urinary metabolic biomarkers of human colorectal cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9064491/
https://www.ncbi.nlm.nih.gov/pubmed/35521635
http://dx.doi.org/10.1155/2022/1758113
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