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LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer
BACKGROUND: Colorectal Cancer (CRC) is a prevalent digestive system tumour with significant mortality and recurrence rates. Serum metabolomics, with its high sensitivity and high throughput, has shown potential as a tool to discover biomarkers for clinical screening and monitoring of the CRC patient...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338013/ https://www.ncbi.nlm.nih.gov/pubmed/37448516 http://dx.doi.org/10.3389/fonc.2023.1173424 |
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author | Yi, Yanan Wang, Jianjian Liang, Chengtong Ren, Chuanli Lian, Xu Han, Chongxu Sun, Wei |
author_facet | Yi, Yanan Wang, Jianjian Liang, Chengtong Ren, Chuanli Lian, Xu Han, Chongxu Sun, Wei |
author_sort | Yi, Yanan |
collection | PubMed |
description | BACKGROUND: Colorectal Cancer (CRC) is a prevalent digestive system tumour with significant mortality and recurrence rates. Serum metabolomics, with its high sensitivity and high throughput, has shown potential as a tool to discover biomarkers for clinical screening and monitoring of the CRC patients. METHODS: Serum metabolites of 61 sex and age-matched healthy controls and 62 CRC patients (before and after surgical intervention) were analyzed using a ultra-performance liquid chromatography-high resolution mass spectrometer (UPLC-MS). Statistical methods and pathway enrichment analysis were used to identify potential biomarkers and altered metabolic pathways. RESULTS: Our analysis revealed a clear distinction in the serum metabolic profile between CRC patients and healthy controls (HCs). Pathway analysis indicated a significant association with arginine biosynthesis, pyrimidine metabolism, pantothenate, and CoA biosynthesis. Univariate and multivariate statistical analysis showed that 9 metabolites had significant diagnostic value for CRC, among them, Guanosine with Area Under the Curve (AUC) values of 0.951 for the training group and0.998 for the validation group. Furthermore, analysis of four specific metabolites (N-Phenylacetylasparticacid, Tyrosyl-Gamma-glutamate, Tyr-Ser and Sphingosine) in serum samples of CRC patients before and after surgery indicated a return to healthy levels after an intervention. CONCLUSION: Our results suggest that serum metabolomics may be a valuable tool for the screening and monitoring of CRC patients. |
format | Online Article Text |
id | pubmed-10338013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103380132023-07-13 LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer Yi, Yanan Wang, Jianjian Liang, Chengtong Ren, Chuanli Lian, Xu Han, Chongxu Sun, Wei Front Oncol Oncology BACKGROUND: Colorectal Cancer (CRC) is a prevalent digestive system tumour with significant mortality and recurrence rates. Serum metabolomics, with its high sensitivity and high throughput, has shown potential as a tool to discover biomarkers for clinical screening and monitoring of the CRC patients. METHODS: Serum metabolites of 61 sex and age-matched healthy controls and 62 CRC patients (before and after surgical intervention) were analyzed using a ultra-performance liquid chromatography-high resolution mass spectrometer (UPLC-MS). Statistical methods and pathway enrichment analysis were used to identify potential biomarkers and altered metabolic pathways. RESULTS: Our analysis revealed a clear distinction in the serum metabolic profile between CRC patients and healthy controls (HCs). Pathway analysis indicated a significant association with arginine biosynthesis, pyrimidine metabolism, pantothenate, and CoA biosynthesis. Univariate and multivariate statistical analysis showed that 9 metabolites had significant diagnostic value for CRC, among them, Guanosine with Area Under the Curve (AUC) values of 0.951 for the training group and0.998 for the validation group. Furthermore, analysis of four specific metabolites (N-Phenylacetylasparticacid, Tyrosyl-Gamma-glutamate, Tyr-Ser and Sphingosine) in serum samples of CRC patients before and after surgery indicated a return to healthy levels after an intervention. CONCLUSION: Our results suggest that serum metabolomics may be a valuable tool for the screening and monitoring of CRC patients. Frontiers Media S.A. 2023-06-28 /pmc/articles/PMC10338013/ /pubmed/37448516 http://dx.doi.org/10.3389/fonc.2023.1173424 Text en Copyright © 2023 Yi, Wang, Liang, Ren, Lian, Han and Sun https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yi, Yanan Wang, Jianjian Liang, Chengtong Ren, Chuanli Lian, Xu Han, Chongxu Sun, Wei LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
title | LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
title_full | LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
title_fullStr | LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
title_full_unstemmed | LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
title_short | LC–MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
title_sort | lc–ms-based serum metabolomics analysis for the screening and monitoring of colorectal cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338013/ https://www.ncbi.nlm.nih.gov/pubmed/37448516 http://dx.doi.org/10.3389/fonc.2023.1173424 |
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