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Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer
Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investiga...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6635503/ https://www.ncbi.nlm.nih.gov/pubmed/31311965 http://dx.doi.org/10.1038/s41598-019-46643-5 |
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author | Berker, Yannick Vandergrift, Lindsey A. Wagner, Isabel Su, Li Kurth, Johannes Schuler, Andreas Dinges, Sarah S. Habbel, Piet Nowak, Johannes Mark, Eugene Aryee, Martin J. Christiani, David C. Cheng, Leo L. |
author_facet | Berker, Yannick Vandergrift, Lindsey A. Wagner, Isabel Su, Li Kurth, Johannes Schuler, Andreas Dinges, Sarah S. Habbel, Piet Nowak, Johannes Mark, Eugene Aryee, Martin J. Christiani, David C. Cheng, Leo L. |
author_sort | Berker, Yannick |
collection | PubMed |
description | Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum. |
format | Online Article Text |
id | pubmed-6635503 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66355032019-07-24 Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer Berker, Yannick Vandergrift, Lindsey A. Wagner, Isabel Su, Li Kurth, Johannes Schuler, Andreas Dinges, Sarah S. Habbel, Piet Nowak, Johannes Mark, Eugene Aryee, Martin J. Christiani, David C. Cheng, Leo L. Sci Rep Article Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum. Nature Publishing Group UK 2019-07-16 /pmc/articles/PMC6635503/ /pubmed/31311965 http://dx.doi.org/10.1038/s41598-019-46643-5 Text en © The Author(s) 2019 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 Berker, Yannick Vandergrift, Lindsey A. Wagner, Isabel Su, Li Kurth, Johannes Schuler, Andreas Dinges, Sarah S. Habbel, Piet Nowak, Johannes Mark, Eugene Aryee, Martin J. Christiani, David C. Cheng, Leo L. Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer |
title | Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer |
title_full | Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer |
title_fullStr | Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer |
title_full_unstemmed | Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer |
title_short | Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer |
title_sort | magnetic resonance spectroscopy-based metabolomic biomarkers for typing, staging, and survival estimation of early-stage human lung cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6635503/ https://www.ncbi.nlm.nih.gov/pubmed/31311965 http://dx.doi.org/10.1038/s41598-019-46643-5 |
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