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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
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.
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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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