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Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma
BACKGROUND: Previous metabolomics studies have found differences in metabolic characteristics between the healthy and ESCC patients. However, few of these studies concerned the whole process of the progression of ESCC. This study aims to explore serum metabolites associated with the progression of E...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100812/ https://www.ncbi.nlm.nih.gov/pubmed/33976728 http://dx.doi.org/10.7150/jca.54429 |
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author | Li, Xia Zhao, Lihong Wei, Mengke Lv, Jiali Sun, Yawen Shen, Xiaotao Zhao, Deli Xue, Fuzhong Zhang, Tao Wang, Jialin |
author_facet | Li, Xia Zhao, Lihong Wei, Mengke Lv, Jiali Sun, Yawen Shen, Xiaotao Zhao, Deli Xue, Fuzhong Zhang, Tao Wang, Jialin |
author_sort | Li, Xia |
collection | PubMed |
description | BACKGROUND: Previous metabolomics studies have found differences in metabolic characteristics between the healthy and ESCC patients. However, few of these studies concerned the whole process of the progression of ESCC. This study aims to explore serum metabolites associated with the progression of ESCC. METHODS: Serum samples from 653 participants (305 normal, 77 esophagitis, 228 LGD, and 43 HGD/ESCC) were examined by ultra-high performance liquid chromatography quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS). Principal component analysis (PCA) was first applied to obtain an overview of the clustering trend for the multidimensional data. Fuzzy c-means (FCM) clustering was then used to screen metabolites with a changing tendency in the progression of ESCC. Univariate ordinal logistic regression analysis and multiple ordinal logistic regression analysis were applied to evaluate the association of metabolites with the risk of ESCC progression, and adjusted for age, gender, BMI, tobacco smoking, and alcohol drinking status. RESULTS: After FCM clustering analysis, a total of 38 metabolites exhibiting changing tendency among normal, esophagitis, LGD, and HGD/ESCC patients. Final results showed 15 metabolites associated with the progression of ESCC. Ten metabolites (dopamine, L-histidine, 5-hydroxyindoleacetate, L-tryptophan, 2'-O-methylcytidine, PC (14:0/0:0), PC (O-16:1/0:0), PE (18:0/0:0), PC (16:1/0:0), PC (18:2/0:0)) were associated with decreased risk of developing ESCC. Five metabolites (hypoxanthine, inosine, carnitine (14:1), glycochenodeoxycholate, PC (P-18:0/18:3)) were associated with increased risk of developing ESCC. CONCLUSIONS: These results demonstrated that serum metabolites are associated with the progression of ESCC. These metabolites are capable of potential biomarkers for the risk prediction and early detection of ESCC. |
format | Online Article Text |
id | pubmed-8100812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-81008122021-05-10 Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma Li, Xia Zhao, Lihong Wei, Mengke Lv, Jiali Sun, Yawen Shen, Xiaotao Zhao, Deli Xue, Fuzhong Zhang, Tao Wang, Jialin J Cancer Research Paper BACKGROUND: Previous metabolomics studies have found differences in metabolic characteristics between the healthy and ESCC patients. However, few of these studies concerned the whole process of the progression of ESCC. This study aims to explore serum metabolites associated with the progression of ESCC. METHODS: Serum samples from 653 participants (305 normal, 77 esophagitis, 228 LGD, and 43 HGD/ESCC) were examined by ultra-high performance liquid chromatography quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS). Principal component analysis (PCA) was first applied to obtain an overview of the clustering trend for the multidimensional data. Fuzzy c-means (FCM) clustering was then used to screen metabolites with a changing tendency in the progression of ESCC. Univariate ordinal logistic regression analysis and multiple ordinal logistic regression analysis were applied to evaluate the association of metabolites with the risk of ESCC progression, and adjusted for age, gender, BMI, tobacco smoking, and alcohol drinking status. RESULTS: After FCM clustering analysis, a total of 38 metabolites exhibiting changing tendency among normal, esophagitis, LGD, and HGD/ESCC patients. Final results showed 15 metabolites associated with the progression of ESCC. Ten metabolites (dopamine, L-histidine, 5-hydroxyindoleacetate, L-tryptophan, 2'-O-methylcytidine, PC (14:0/0:0), PC (O-16:1/0:0), PE (18:0/0:0), PC (16:1/0:0), PC (18:2/0:0)) were associated with decreased risk of developing ESCC. Five metabolites (hypoxanthine, inosine, carnitine (14:1), glycochenodeoxycholate, PC (P-18:0/18:3)) were associated with increased risk of developing ESCC. CONCLUSIONS: These results demonstrated that serum metabolites are associated with the progression of ESCC. These metabolites are capable of potential biomarkers for the risk prediction and early detection of ESCC. Ivyspring International Publisher 2021-04-02 /pmc/articles/PMC8100812/ /pubmed/33976728 http://dx.doi.org/10.7150/jca.54429 Text en © The author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Research Paper Li, Xia Zhao, Lihong Wei, Mengke Lv, Jiali Sun, Yawen Shen, Xiaotao Zhao, Deli Xue, Fuzhong Zhang, Tao Wang, Jialin Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
title | Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
title_full | Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
title_fullStr | Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
title_full_unstemmed | Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
title_short | Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
title_sort | serum metabolomics analysis for the progression of esophageal squamous cell carcinoma |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100812/ https://www.ncbi.nlm.nih.gov/pubmed/33976728 http://dx.doi.org/10.7150/jca.54429 |
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