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Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer

Molecular profiling of circulating extracellular vesicles (EVs) provides a promising noninvasive means to diagnose, monitor, and predict the course of metastatic breast cancer (MBC). However, the analysis of EV protein markers has been confounded by the presence of soluble protein counterparts in pe...

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Autores principales: Tian, Fei, Zhang, Shaohua, Liu, Chao, Han, Ziwei, Liu, Yuan, Deng, Jinqi, Li, Yike, Wu, Xia, Cai, Lili, Qin, Lili, Chen, Qinghua, Yuan, Yang, Liu, Yi, Cong, Yulong, Ding, Baoquan, Jiang, Zefei, Sun, Jiashu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100127/
https://www.ncbi.nlm.nih.gov/pubmed/33953198
http://dx.doi.org/10.1038/s41467-021-22913-7
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author Tian, Fei
Zhang, Shaohua
Liu, Chao
Han, Ziwei
Liu, Yuan
Deng, Jinqi
Li, Yike
Wu, Xia
Cai, Lili
Qin, Lili
Chen, Qinghua
Yuan, Yang
Liu, Yi
Cong, Yulong
Ding, Baoquan
Jiang, Zefei
Sun, Jiashu
author_facet Tian, Fei
Zhang, Shaohua
Liu, Chao
Han, Ziwei
Liu, Yuan
Deng, Jinqi
Li, Yike
Wu, Xia
Cai, Lili
Qin, Lili
Chen, Qinghua
Yuan, Yang
Liu, Yi
Cong, Yulong
Ding, Baoquan
Jiang, Zefei
Sun, Jiashu
author_sort Tian, Fei
collection PubMed
description Molecular profiling of circulating extracellular vesicles (EVs) provides a promising noninvasive means to diagnose, monitor, and predict the course of metastatic breast cancer (MBC). However, the analysis of EV protein markers has been confounded by the presence of soluble protein counterparts in peripheral blood. Here we use a rapid, sensitive, and low-cost thermophoretic aptasensor (TAS) to profile cancer-associated protein profiles of plasma EVs without the interference of soluble proteins. We show that the EV signature (a weighted sum of eight EV protein markers) has a high accuracy (91.1 %) for discrimination of MBC, non-metastatic breast cancer (NMBC), and healthy donors (HD). For MBC patients undergoing therapies, the EV signature can accurately monitor the treatment response across the training, validation, and prospective cohorts, and serve as an independent prognostic factor for progression free survival in MBC patients. Together, this work highlights the potential clinical utility of EVs in management of MBC.
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spelling pubmed-81001272021-05-11 Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer Tian, Fei Zhang, Shaohua Liu, Chao Han, Ziwei Liu, Yuan Deng, Jinqi Li, Yike Wu, Xia Cai, Lili Qin, Lili Chen, Qinghua Yuan, Yang Liu, Yi Cong, Yulong Ding, Baoquan Jiang, Zefei Sun, Jiashu Nat Commun Article Molecular profiling of circulating extracellular vesicles (EVs) provides a promising noninvasive means to diagnose, monitor, and predict the course of metastatic breast cancer (MBC). However, the analysis of EV protein markers has been confounded by the presence of soluble protein counterparts in peripheral blood. Here we use a rapid, sensitive, and low-cost thermophoretic aptasensor (TAS) to profile cancer-associated protein profiles of plasma EVs without the interference of soluble proteins. We show that the EV signature (a weighted sum of eight EV protein markers) has a high accuracy (91.1 %) for discrimination of MBC, non-metastatic breast cancer (NMBC), and healthy donors (HD). For MBC patients undergoing therapies, the EV signature can accurately monitor the treatment response across the training, validation, and prospective cohorts, and serve as an independent prognostic factor for progression free survival in MBC patients. Together, this work highlights the potential clinical utility of EVs in management of MBC. Nature Publishing Group UK 2021-05-05 /pmc/articles/PMC8100127/ /pubmed/33953198 http://dx.doi.org/10.1038/s41467-021-22913-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tian, Fei
Zhang, Shaohua
Liu, Chao
Han, Ziwei
Liu, Yuan
Deng, Jinqi
Li, Yike
Wu, Xia
Cai, Lili
Qin, Lili
Chen, Qinghua
Yuan, Yang
Liu, Yi
Cong, Yulong
Ding, Baoquan
Jiang, Zefei
Sun, Jiashu
Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
title Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
title_full Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
title_fullStr Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
title_full_unstemmed Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
title_short Protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
title_sort protein analysis of extracellular vesicles to monitor and predict therapeutic response in metastatic breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100127/
https://www.ncbi.nlm.nih.gov/pubmed/33953198
http://dx.doi.org/10.1038/s41467-021-22913-7
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