Cargando…
Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors
Distinguishing breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS) is a key step in breast surgery, especially to determine whether DCIS is associated with tumor cell micro-invasion. However, there is currently no reliable method to obtain molecular information for brea...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751527/ https://www.ncbi.nlm.nih.gov/pubmed/26868906 http://dx.doi.org/10.1038/srep21043 |
_version_ | 1782415599460155392 |
---|---|
author | Mao, Xinxin He, Jiuming Li, Tiegang Lu, Zhaohui Sun, Jian Meng, Yunxiao Abliz, Zeper Chen, Jie |
author_facet | Mao, Xinxin He, Jiuming Li, Tiegang Lu, Zhaohui Sun, Jian Meng, Yunxiao Abliz, Zeper Chen, Jie |
author_sort | Mao, Xinxin |
collection | PubMed |
description | Distinguishing breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS) is a key step in breast surgery, especially to determine whether DCIS is associated with tumor cell micro-invasion. However, there is currently no reliable method to obtain molecular information for breast tumor analysis during surgery. Here, we present a novel air flow-assisted ionization (AFAI) mass spectrometry imaging method that can be used in ambient environments to differentiate breast cancer by analyzing lipids. In this study, we demonstrate that various subtypes and histological grades of IDC and DCIS can be discriminated using AFAI-MSI: phospholipids were more abundant in IDC than in DCIS, whereas fatty acids were more abundant in DCIS than in IDC. The classification of specimens in the subtype and grade validation sets showed 100% and 78.6% agreement with the histopathological diagnosis, respectively. Our work shows the rapid classification of breast cancer utilizing AFAI-MSI. This work suggests that this method could be developed to provide surgeons with nearly real-time information to guide surgical resections. |
format | Online Article Text |
id | pubmed-4751527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47515272016-02-22 Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors Mao, Xinxin He, Jiuming Li, Tiegang Lu, Zhaohui Sun, Jian Meng, Yunxiao Abliz, Zeper Chen, Jie Sci Rep Article Distinguishing breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS) is a key step in breast surgery, especially to determine whether DCIS is associated with tumor cell micro-invasion. However, there is currently no reliable method to obtain molecular information for breast tumor analysis during surgery. Here, we present a novel air flow-assisted ionization (AFAI) mass spectrometry imaging method that can be used in ambient environments to differentiate breast cancer by analyzing lipids. In this study, we demonstrate that various subtypes and histological grades of IDC and DCIS can be discriminated using AFAI-MSI: phospholipids were more abundant in IDC than in DCIS, whereas fatty acids were more abundant in DCIS than in IDC. The classification of specimens in the subtype and grade validation sets showed 100% and 78.6% agreement with the histopathological diagnosis, respectively. Our work shows the rapid classification of breast cancer utilizing AFAI-MSI. This work suggests that this method could be developed to provide surgeons with nearly real-time information to guide surgical resections. Nature Publishing Group 2016-02-12 /pmc/articles/PMC4751527/ /pubmed/26868906 http://dx.doi.org/10.1038/srep21043 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Mao, Xinxin He, Jiuming Li, Tiegang Lu, Zhaohui Sun, Jian Meng, Yunxiao Abliz, Zeper Chen, Jie Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
title | Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
title_full | Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
title_fullStr | Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
title_full_unstemmed | Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
title_short | Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
title_sort | application of imaging mass spectrometry for the molecular diagnosis of human breast tumors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751527/ https://www.ncbi.nlm.nih.gov/pubmed/26868906 http://dx.doi.org/10.1038/srep21043 |
work_keys_str_mv | AT maoxinxin applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT hejiuming applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT litiegang applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT luzhaohui applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT sunjian applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT mengyunxiao applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT ablizzeper applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors AT chenjie applicationofimagingmassspectrometryforthemoleculardiagnosisofhumanbreasttumors |