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Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer
Disease breathomics is gaining importance nowadays due to its usefulness as non-invasive early cancer detection. Mass spectrometry (MS) technique is often used for analysis of volatile organic compounds (VOCs) associated with cancer in the exhaled breath but a long-standing challenge is the uncertai...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865157/ https://www.ncbi.nlm.nih.gov/pubmed/29572531 http://dx.doi.org/10.1038/s41598-018-22890-w |
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author | Chin, Sung-Tong Romano, Andrea Doran, Sophie L. F. Hanna, George B. |
author_facet | Chin, Sung-Tong Romano, Andrea Doran, Sophie L. F. Hanna, George B. |
author_sort | Chin, Sung-Tong |
collection | PubMed |
description | Disease breathomics is gaining importance nowadays due to its usefulness as non-invasive early cancer detection. Mass spectrometry (MS) technique is often used for analysis of volatile organic compounds (VOCs) associated with cancer in the exhaled breath but a long-standing challenge is the uncertainty in mass peak annotation for potential volatile biomarkers. This work describes a cross-platform MS strategy employing selected-ion flow tube mass spectrometry (SIFT-MS), high resolution gas chromatography-mass spectrometry (GC-MS) retrofitted with electron ionisation (EI) and GC-MS retrofitted with positive chemical ionisation (PCI) as orthogonal analytical approaches in order to provide facile identification of the oxygenated VOCs from breath of cancer patients. In addition, water infusion was applied as novel efficient PCI reagent in breathomics analysis, depicting unique diagnostic ions M(+) or [M-17](+) for VOC identification. Identity confirmation of breath VOCs was deduced using the proposed multi-platform workflow, which reveals variation in breath oxygenated VOC composition of oesophageal-gastric (OG) cancer patients with dominantly ketones, followed by aldehydes, alcohols, acids and phenols in decreasing order of relative abundance. Accurate VOC identification provided by cross-platform approach would be valuable for the refinement of diagnostic VOC models and the understanding of molecular drivers of VOC production. |
format | Online Article Text |
id | pubmed-5865157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-58651572018-03-27 Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer Chin, Sung-Tong Romano, Andrea Doran, Sophie L. F. Hanna, George B. Sci Rep Article Disease breathomics is gaining importance nowadays due to its usefulness as non-invasive early cancer detection. Mass spectrometry (MS) technique is often used for analysis of volatile organic compounds (VOCs) associated with cancer in the exhaled breath but a long-standing challenge is the uncertainty in mass peak annotation for potential volatile biomarkers. This work describes a cross-platform MS strategy employing selected-ion flow tube mass spectrometry (SIFT-MS), high resolution gas chromatography-mass spectrometry (GC-MS) retrofitted with electron ionisation (EI) and GC-MS retrofitted with positive chemical ionisation (PCI) as orthogonal analytical approaches in order to provide facile identification of the oxygenated VOCs from breath of cancer patients. In addition, water infusion was applied as novel efficient PCI reagent in breathomics analysis, depicting unique diagnostic ions M(+) or [M-17](+) for VOC identification. Identity confirmation of breath VOCs was deduced using the proposed multi-platform workflow, which reveals variation in breath oxygenated VOC composition of oesophageal-gastric (OG) cancer patients with dominantly ketones, followed by aldehydes, alcohols, acids and phenols in decreasing order of relative abundance. Accurate VOC identification provided by cross-platform approach would be valuable for the refinement of diagnostic VOC models and the understanding of molecular drivers of VOC production. Nature Publishing Group UK 2018-03-23 /pmc/articles/PMC5865157/ /pubmed/29572531 http://dx.doi.org/10.1038/s41598-018-22890-w Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chin, Sung-Tong Romano, Andrea Doran, Sophie L. F. Hanna, George B. Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
title | Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
title_full | Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
title_fullStr | Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
title_full_unstemmed | Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
title_short | Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
title_sort | cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865157/ https://www.ncbi.nlm.nih.gov/pubmed/29572531 http://dx.doi.org/10.1038/s41598-018-22890-w |
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