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Stromal vapors for real-time molecular guidance of breast-conserving surgery
Achieving radical tumor resection while preserving disease-free tissue during breast-conserving surgery (BCS) remains a challenge. Here, mass spectrometry technologies were used to discriminate stromal tissues reported to be altered surrounding breast tumors, and build tissue classifiers ex vivo. Ad...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674429/ https://www.ncbi.nlm.nih.gov/pubmed/33208813 http://dx.doi.org/10.1038/s41598-020-77102-1 |
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author | Vaysse, Pierre-Maxence Kooreman, Loes F. S. Engelen, Sanne M. E. Kremer, Bernd Olde Damink, Steven W. M. Heeren, Ron M. A. Smidt, Marjolein L. Porta Siegel, Tiffany |
author_facet | Vaysse, Pierre-Maxence Kooreman, Loes F. S. Engelen, Sanne M. E. Kremer, Bernd Olde Damink, Steven W. M. Heeren, Ron M. A. Smidt, Marjolein L. Porta Siegel, Tiffany |
author_sort | Vaysse, Pierre-Maxence |
collection | PubMed |
description | Achieving radical tumor resection while preserving disease-free tissue during breast-conserving surgery (BCS) remains a challenge. Here, mass spectrometry technologies were used to discriminate stromal tissues reported to be altered surrounding breast tumors, and build tissue classifiers ex vivo. Additionally, we employed the approach for in vivo and real-time classification of breast pathology based on electrosurgical vapors. Breast-resected samples were obtained from patients undergoing surgery at MUMC+. The specimens were subsequently sampled ex vivo to generate electrosurgical vapors analyzed by rapid evaporative ionization mass spectrometry (REIMS). Tissues were processed for histopathology to assign tissue components to the mass spectral profiles. We collected a total of 689 ex vivo REIMS profiles from 72 patients which were analyzed using multivariate statistical analysis (principal component analysis-linear discriminant analysis). These profiles were classified as adipose, stromal and tumor tissues with 92.3% accuracy with a leave-one patient-out cross-validation. Tissue recognition using this ex vivo-built REIMS classification model was subsequently tested in vivo on electrosurgical vapors. Stromal and adipose tissues were classified during one BCS. Complementary ex vivo analyses were performed by REIMS and by desorption electrospray ionization mass spectrometry (DESI-MS) to study the potential of breast stroma to guide BCS. Tumor border stroma (TBS) and remote tumor stroma (RTS) were classified by REIMS and DESI-MS with 86.4% and 87.8% accuracy, respectively. We demonstrate the potential of stromal molecular alterations surrounding breast tumors to guide BCS in real-time using REIMS analysis of electrosurgical vapors. |
format | Online Article Text |
id | pubmed-7674429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76744292020-11-19 Stromal vapors for real-time molecular guidance of breast-conserving surgery Vaysse, Pierre-Maxence Kooreman, Loes F. S. Engelen, Sanne M. E. Kremer, Bernd Olde Damink, Steven W. M. Heeren, Ron M. A. Smidt, Marjolein L. Porta Siegel, Tiffany Sci Rep Article Achieving radical tumor resection while preserving disease-free tissue during breast-conserving surgery (BCS) remains a challenge. Here, mass spectrometry technologies were used to discriminate stromal tissues reported to be altered surrounding breast tumors, and build tissue classifiers ex vivo. Additionally, we employed the approach for in vivo and real-time classification of breast pathology based on electrosurgical vapors. Breast-resected samples were obtained from patients undergoing surgery at MUMC+. The specimens were subsequently sampled ex vivo to generate electrosurgical vapors analyzed by rapid evaporative ionization mass spectrometry (REIMS). Tissues were processed for histopathology to assign tissue components to the mass spectral profiles. We collected a total of 689 ex vivo REIMS profiles from 72 patients which were analyzed using multivariate statistical analysis (principal component analysis-linear discriminant analysis). These profiles were classified as adipose, stromal and tumor tissues with 92.3% accuracy with a leave-one patient-out cross-validation. Tissue recognition using this ex vivo-built REIMS classification model was subsequently tested in vivo on electrosurgical vapors. Stromal and adipose tissues were classified during one BCS. Complementary ex vivo analyses were performed by REIMS and by desorption electrospray ionization mass spectrometry (DESI-MS) to study the potential of breast stroma to guide BCS. Tumor border stroma (TBS) and remote tumor stroma (RTS) were classified by REIMS and DESI-MS with 86.4% and 87.8% accuracy, respectively. We demonstrate the potential of stromal molecular alterations surrounding breast tumors to guide BCS in real-time using REIMS analysis of electrosurgical vapors. Nature Publishing Group UK 2020-11-18 /pmc/articles/PMC7674429/ /pubmed/33208813 http://dx.doi.org/10.1038/s41598-020-77102-1 Text en © The Author(s) 2020 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Vaysse, Pierre-Maxence Kooreman, Loes F. S. Engelen, Sanne M. E. Kremer, Bernd Olde Damink, Steven W. M. Heeren, Ron M. A. Smidt, Marjolein L. Porta Siegel, Tiffany Stromal vapors for real-time molecular guidance of breast-conserving surgery |
title | Stromal vapors for real-time molecular guidance of breast-conserving surgery |
title_full | Stromal vapors for real-time molecular guidance of breast-conserving surgery |
title_fullStr | Stromal vapors for real-time molecular guidance of breast-conserving surgery |
title_full_unstemmed | Stromal vapors for real-time molecular guidance of breast-conserving surgery |
title_short | Stromal vapors for real-time molecular guidance of breast-conserving surgery |
title_sort | stromal vapors for real-time molecular guidance of breast-conserving surgery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674429/ https://www.ncbi.nlm.nih.gov/pubmed/33208813 http://dx.doi.org/10.1038/s41598-020-77102-1 |
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