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A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis

Early diagnosis of gastric cancer is crucial to improve patient′ outcome. A good biomarker will function in early diagnosis for gastric cancer. In order to find practical and cost-effective biomarkers, we used gas chromatography combined mass spectrometer (GC-MS) to profile urinary metabolites on 29...

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Autores principales: Chen, Yinan, Zhang, Jun, Guo, Lei, Liu, Lei, Wen, Jingran, Xu, Lu, Yan, Min, Li, Zuofeng, Zhang, Xiaoyan, Nan, Peng, Jiang, Jinling, Ji, Jun, Zhang, Jianian, Cai, Wei, Zhuang, Huisheng, Wang, Yan, Zhu, Zhenggang, Yu, Yingyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5350005/
https://www.ncbi.nlm.nih.gov/pubmed/27589838
http://dx.doi.org/10.18632/oncotarget.11754
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author Chen, Yinan
Zhang, Jun
Guo, Lei
Liu, Lei
Wen, Jingran
Xu, Lu
Yan, Min
Li, Zuofeng
Zhang, Xiaoyan
Nan, Peng
Jiang, Jinling
Ji, Jun
Zhang, Jianian
Cai, Wei
Zhuang, Huisheng
Wang, Yan
Zhu, Zhenggang
Yu, Yingyan
author_facet Chen, Yinan
Zhang, Jun
Guo, Lei
Liu, Lei
Wen, Jingran
Xu, Lu
Yan, Min
Li, Zuofeng
Zhang, Xiaoyan
Nan, Peng
Jiang, Jinling
Ji, Jun
Zhang, Jianian
Cai, Wei
Zhuang, Huisheng
Wang, Yan
Zhu, Zhenggang
Yu, Yingyan
author_sort Chen, Yinan
collection PubMed
description Early diagnosis of gastric cancer is crucial to improve patient′ outcome. A good biomarker will function in early diagnosis for gastric cancer. In order to find practical and cost-effective biomarkers, we used gas chromatography combined mass spectrometer (GC-MS) to profile urinary metabolites on 293 urine samples. Ninety-four samples are taken as training set, others for validating study. Orthogonal partial least squares discriminant analysis (OPLS-DA), significance analysis of microarray (SAM) and Mann-Whitney U test are used for data analysis. The diagnostic value of urinary metabolites was evaluated by ROC curve. As results, Seventeen metabolites are significantly different between patients and healthy controls in training set. Among them, 14 metabolites show diagnostic value better than classic blood biomarkers by quantitative assay on validation set. Ten of them are amino acids and four are organic metabolites. Importantly, proline, p-cresol and 4-hydroxybenzoic acid disclose outcome-prediction value by means of survival analysis. Therefore, the examination of urinary metabolites is a promising noninvasive strategy for gastric cancer screening.
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spelling pubmed-53500052017-04-06 A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis Chen, Yinan Zhang, Jun Guo, Lei Liu, Lei Wen, Jingran Xu, Lu Yan, Min Li, Zuofeng Zhang, Xiaoyan Nan, Peng Jiang, Jinling Ji, Jun Zhang, Jianian Cai, Wei Zhuang, Huisheng Wang, Yan Zhu, Zhenggang Yu, Yingyan Oncotarget Clinical Research Paper Early diagnosis of gastric cancer is crucial to improve patient′ outcome. A good biomarker will function in early diagnosis for gastric cancer. In order to find practical and cost-effective biomarkers, we used gas chromatography combined mass spectrometer (GC-MS) to profile urinary metabolites on 293 urine samples. Ninety-four samples are taken as training set, others for validating study. Orthogonal partial least squares discriminant analysis (OPLS-DA), significance analysis of microarray (SAM) and Mann-Whitney U test are used for data analysis. The diagnostic value of urinary metabolites was evaluated by ROC curve. As results, Seventeen metabolites are significantly different between patients and healthy controls in training set. Among them, 14 metabolites show diagnostic value better than classic blood biomarkers by quantitative assay on validation set. Ten of them are amino acids and four are organic metabolites. Importantly, proline, p-cresol and 4-hydroxybenzoic acid disclose outcome-prediction value by means of survival analysis. Therefore, the examination of urinary metabolites is a promising noninvasive strategy for gastric cancer screening. Impact Journals LLC 2016-08-31 /pmc/articles/PMC5350005/ /pubmed/27589838 http://dx.doi.org/10.18632/oncotarget.11754 Text en Copyright: © 2016 Chen et al. http://creativecommons.org/licenses/by/3.0/ 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 Clinical Research Paper
Chen, Yinan
Zhang, Jun
Guo, Lei
Liu, Lei
Wen, Jingran
Xu, Lu
Yan, Min
Li, Zuofeng
Zhang, Xiaoyan
Nan, Peng
Jiang, Jinling
Ji, Jun
Zhang, Jianian
Cai, Wei
Zhuang, Huisheng
Wang, Yan
Zhu, Zhenggang
Yu, Yingyan
A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis
title A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis
title_full A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis
title_fullStr A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis
title_full_unstemmed A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis
title_short A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis
title_sort characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput gc-ms analysis
topic Clinical Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5350005/
https://www.ncbi.nlm.nih.gov/pubmed/27589838
http://dx.doi.org/10.18632/oncotarget.11754
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