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Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS

Serum prostate-specific antigen (PSA) is currently the most used biomarker in clinical practice for prostate cancer (PCa) detection. However, this biomarker has several drawbacks. In this work, an untargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling of PCa cells was pe...

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Autores principales: Lima, Ana Rita, Araújo, Ana Margarida, Pinto, Joana, Jerónimo, Carmen, Henrique, Rui, Bastos, Maria de Lourdes, Carvalho, Márcia, Guedes de Pinho, Paula
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882858/
https://www.ncbi.nlm.nih.gov/pubmed/29615722
http://dx.doi.org/10.1038/s41598-018-23847-9
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author Lima, Ana Rita
Araújo, Ana Margarida
Pinto, Joana
Jerónimo, Carmen
Henrique, Rui
Bastos, Maria de Lourdes
Carvalho, Márcia
Guedes de Pinho, Paula
author_facet Lima, Ana Rita
Araújo, Ana Margarida
Pinto, Joana
Jerónimo, Carmen
Henrique, Rui
Bastos, Maria de Lourdes
Carvalho, Márcia
Guedes de Pinho, Paula
author_sort Lima, Ana Rita
collection PubMed
description Serum prostate-specific antigen (PSA) is currently the most used biomarker in clinical practice for prostate cancer (PCa) detection. However, this biomarker has several drawbacks. In this work, an untargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling of PCa cells was performed to prove the concept that metabolic alterations might differentiate PCa cell lines from normal prostate cell line. For that, we assessed the differences in volatile organic compounds (VOCs) profile in the extracellular medium (exometabolome) of four PCa cell lines and one normal prostate cell line at two pH values (pH 2 and 7) by GC-MS. Multivariate analysis revealed a panel of volatile metabolites that discriminated cancerous from normal prostate cells. The most altered metabolites included ketones, aldehydes and organic acids. Among these, we highlight pentadecane-2-one and decanoic acid, which were significantly increased in PCa compared to normal cells, and cyclohexanone, 4-methylheptan-2-one, 2-methylpentane-1,3-diol, 4-methylbenzaldehyde, 1-(3,5-dimethylfuran-2-yl)ethanone, methyl benzoate and nonanoic acid, which were significantly decreased in PCa cells. The PCa volatilome was markedly influenced by the VOCs extraction pH, though the discriminant capability was similar. Overall, our data suggest that VOCs monitoring has the potential to be used as a PCa screening methodology.
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spelling pubmed-58828582018-04-09 Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS Lima, Ana Rita Araújo, Ana Margarida Pinto, Joana Jerónimo, Carmen Henrique, Rui Bastos, Maria de Lourdes Carvalho, Márcia Guedes de Pinho, Paula Sci Rep Article Serum prostate-specific antigen (PSA) is currently the most used biomarker in clinical practice for prostate cancer (PCa) detection. However, this biomarker has several drawbacks. In this work, an untargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling of PCa cells was performed to prove the concept that metabolic alterations might differentiate PCa cell lines from normal prostate cell line. For that, we assessed the differences in volatile organic compounds (VOCs) profile in the extracellular medium (exometabolome) of four PCa cell lines and one normal prostate cell line at two pH values (pH 2 and 7) by GC-MS. Multivariate analysis revealed a panel of volatile metabolites that discriminated cancerous from normal prostate cells. The most altered metabolites included ketones, aldehydes and organic acids. Among these, we highlight pentadecane-2-one and decanoic acid, which were significantly increased in PCa compared to normal cells, and cyclohexanone, 4-methylheptan-2-one, 2-methylpentane-1,3-diol, 4-methylbenzaldehyde, 1-(3,5-dimethylfuran-2-yl)ethanone, methyl benzoate and nonanoic acid, which were significantly decreased in PCa cells. The PCa volatilome was markedly influenced by the VOCs extraction pH, though the discriminant capability was similar. Overall, our data suggest that VOCs monitoring has the potential to be used as a PCa screening methodology. Nature Publishing Group UK 2018-04-03 /pmc/articles/PMC5882858/ /pubmed/29615722 http://dx.doi.org/10.1038/s41598-018-23847-9 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
Lima, Ana Rita
Araújo, Ana Margarida
Pinto, Joana
Jerónimo, Carmen
Henrique, Rui
Bastos, Maria de Lourdes
Carvalho, Márcia
Guedes de Pinho, Paula
Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS
title Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS
title_full Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS
title_fullStr Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS
title_full_unstemmed Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS
title_short Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS
title_sort discrimination between the human prostate normal and cancer cell exometabolome by gc-ms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882858/
https://www.ncbi.nlm.nih.gov/pubmed/29615722
http://dx.doi.org/10.1038/s41598-018-23847-9
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