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Profiling Single Cancer Cells with Volatolomics Approach

Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile orga...

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Detalles Bibliográficos
Autores principales: Serasanambati, Mamatha, Broza, Yoav Y., Marmur, Abraham, Haick, Hossam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319329/
https://www.ncbi.nlm.nih.gov/pubmed/30612036
http://dx.doi.org/10.1016/j.isci.2018.12.008
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author Serasanambati, Mamatha
Broza, Yoav Y.
Marmur, Abraham
Haick, Hossam
author_facet Serasanambati, Mamatha
Broza, Yoav Y.
Marmur, Abraham
Haick, Hossam
author_sort Serasanambati, Mamatha
collection PubMed
description Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis.
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spelling pubmed-63193292019-01-09 Profiling Single Cancer Cells with Volatolomics Approach Serasanambati, Mamatha Broza, Yoav Y. Marmur, Abraham Haick, Hossam iScience Article Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis. Elsevier 2018-12-14 /pmc/articles/PMC6319329/ /pubmed/30612036 http://dx.doi.org/10.1016/j.isci.2018.12.008 Text en © 2018 Technion - Israel Institute of Technology http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Serasanambati, Mamatha
Broza, Yoav Y.
Marmur, Abraham
Haick, Hossam
Profiling Single Cancer Cells with Volatolomics Approach
title Profiling Single Cancer Cells with Volatolomics Approach
title_full Profiling Single Cancer Cells with Volatolomics Approach
title_fullStr Profiling Single Cancer Cells with Volatolomics Approach
title_full_unstemmed Profiling Single Cancer Cells with Volatolomics Approach
title_short Profiling Single Cancer Cells with Volatolomics Approach
title_sort profiling single cancer cells with volatolomics approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319329/
https://www.ncbi.nlm.nih.gov/pubmed/30612036
http://dx.doi.org/10.1016/j.isci.2018.12.008
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