Cargando…

Differentiation between genetic mutations of breast cancer by breath volatolomics

Mapping molecular sub-types in breast cancer (BC) tumours is a rapidly evolving area due to growing interest in, for example, targeted therapy and screening high-risk populations for early diagnosis. We report a new concept for profiling BC molecular sub-types based on volatile organic compounds (VO...

Descripción completa

Detalles Bibliográficos
Autores principales: Barash, Orna, Zhang, Wei, Halpern, Jeffrey M., Hua, Qing-Ling, Pan, Yue-Yin, Kayal, Haneen, Khoury, Kayan, Liu, Hu, Davies, Michael P.A., Haick, Hossam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792597/
https://www.ncbi.nlm.nih.gov/pubmed/26540569
_version_ 1782421271919722496
author Barash, Orna
Zhang, Wei
Halpern, Jeffrey M.
Hua, Qing-Ling
Pan, Yue-Yin
Kayal, Haneen
Khoury, Kayan
Liu, Hu
Davies, Michael P.A.
Haick, Hossam
author_facet Barash, Orna
Zhang, Wei
Halpern, Jeffrey M.
Hua, Qing-Ling
Pan, Yue-Yin
Kayal, Haneen
Khoury, Kayan
Liu, Hu
Davies, Michael P.A.
Haick, Hossam
author_sort Barash, Orna
collection PubMed
description Mapping molecular sub-types in breast cancer (BC) tumours is a rapidly evolving area due to growing interest in, for example, targeted therapy and screening high-risk populations for early diagnosis. We report a new concept for profiling BC molecular sub-types based on volatile organic compounds (VOCs). For this purpose, breath samples were collected from 276 female volunteers, including healthy, benign conditions, ductal carcinoma in situ (DCIS) and malignant lesions. Breath samples were analysed by gas chromatography mass spectrometry (GC-MS) and artificially intelligent nanoarray technology. Applying the non-parametric Wilcoxon/Kruskal-Wallis test, GC-MS analysis found 23 compounds that were significantly different (p < 0.05) in breath samples of BC patients with different molecular sub-types. Discriminant function analysis (DFA) of the nanoarray identified unique volatolomic signatures between cancer and non-cancer cases (83% accuracy in blind testing), and for the different molecular sub-types with accuracies ranging from 82 to 87%, sensitivities of 81 to 88% and specificities of 76 to 96% in leave-one-out cross-validation. These results demonstrate the presence of detectable breath VOC patterns for accurately profiling molecular sub-types in BC, either through specific compound identification by GC-MS or by volatolomic signatures obtained through statistical analysis of the artificially intelligent nanoarray responses.
format Online
Article
Text
id pubmed-4792597
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Impact Journals LLC
record_format MEDLINE/PubMed
spelling pubmed-47925972016-03-29 Differentiation between genetic mutations of breast cancer by breath volatolomics Barash, Orna Zhang, Wei Halpern, Jeffrey M. Hua, Qing-Ling Pan, Yue-Yin Kayal, Haneen Khoury, Kayan Liu, Hu Davies, Michael P.A. Haick, Hossam Oncotarget Research Paper Mapping molecular sub-types in breast cancer (BC) tumours is a rapidly evolving area due to growing interest in, for example, targeted therapy and screening high-risk populations for early diagnosis. We report a new concept for profiling BC molecular sub-types based on volatile organic compounds (VOCs). For this purpose, breath samples were collected from 276 female volunteers, including healthy, benign conditions, ductal carcinoma in situ (DCIS) and malignant lesions. Breath samples were analysed by gas chromatography mass spectrometry (GC-MS) and artificially intelligent nanoarray technology. Applying the non-parametric Wilcoxon/Kruskal-Wallis test, GC-MS analysis found 23 compounds that were significantly different (p < 0.05) in breath samples of BC patients with different molecular sub-types. Discriminant function analysis (DFA) of the nanoarray identified unique volatolomic signatures between cancer and non-cancer cases (83% accuracy in blind testing), and for the different molecular sub-types with accuracies ranging from 82 to 87%, sensitivities of 81 to 88% and specificities of 76 to 96% in leave-one-out cross-validation. These results demonstrate the presence of detectable breath VOC patterns for accurately profiling molecular sub-types in BC, either through specific compound identification by GC-MS or by volatolomic signatures obtained through statistical analysis of the artificially intelligent nanoarray responses. Impact Journals LLC 2015-11-02 /pmc/articles/PMC4792597/ /pubmed/26540569 Text en Copyright: © 2015 Barash et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Barash, Orna
Zhang, Wei
Halpern, Jeffrey M.
Hua, Qing-Ling
Pan, Yue-Yin
Kayal, Haneen
Khoury, Kayan
Liu, Hu
Davies, Michael P.A.
Haick, Hossam
Differentiation between genetic mutations of breast cancer by breath volatolomics
title Differentiation between genetic mutations of breast cancer by breath volatolomics
title_full Differentiation between genetic mutations of breast cancer by breath volatolomics
title_fullStr Differentiation between genetic mutations of breast cancer by breath volatolomics
title_full_unstemmed Differentiation between genetic mutations of breast cancer by breath volatolomics
title_short Differentiation between genetic mutations of breast cancer by breath volatolomics
title_sort differentiation between genetic mutations of breast cancer by breath volatolomics
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792597/
https://www.ncbi.nlm.nih.gov/pubmed/26540569
work_keys_str_mv AT barashorna differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT zhangwei differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT halpernjeffreym differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT huaqingling differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT panyueyin differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT kayalhaneen differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT khourykayan differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT liuhu differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT daviesmichaelpa differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics
AT haickhossam differentiationbetweengeneticmutationsofbreastcancerbybreathvolatolomics