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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-9064491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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