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Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma

Monitoring targeted therapy in real time for cancer patients could provide vital information about the development of drug resistance and improve therapeutic outcomes. Extracellular vesicles (EVs) have recently emerged as a promising cancer biomarker, and EV phenotyping shows high potential for moni...

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Autores principales: Wang, Jing, Wuethrich, Alain, Sina, Abu Ali Ibn, Lane, Rebecca E., Lin, Lynlee L., Wang, Yuling, Cebon, Jonathan, Behren, Andreas, Trau, Matt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043913/
https://www.ncbi.nlm.nih.gov/pubmed/32133394
http://dx.doi.org/10.1126/sciadv.aax3223
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author Wang, Jing
Wuethrich, Alain
Sina, Abu Ali Ibn
Lane, Rebecca E.
Lin, Lynlee L.
Wang, Yuling
Cebon, Jonathan
Behren, Andreas
Trau, Matt
author_facet Wang, Jing
Wuethrich, Alain
Sina, Abu Ali Ibn
Lane, Rebecca E.
Lin, Lynlee L.
Wang, Yuling
Cebon, Jonathan
Behren, Andreas
Trau, Matt
author_sort Wang, Jing
collection PubMed
description Monitoring targeted therapy in real time for cancer patients could provide vital information about the development of drug resistance and improve therapeutic outcomes. Extracellular vesicles (EVs) have recently emerged as a promising cancer biomarker, and EV phenotyping shows high potential for monitoring treatment responses. Here, we demonstrate the feasibility of monitoring patient treatment responses based on the plasma EV phenotypic evolution using a multiplex EV phenotype analyzer chip (EPAC). EPAC incorporates the nanomixing-enhanced microchip and the multiplex surface-enhanced Raman scattering (SERS) nanotag system for direct EV phenotyping without EV enrichment. In a preclinical model, we observe the EV phenotypic heterogeneity and different phenotypic responses to the treatment. Furthermore, we successfully detect cancer-specific EV phenotypes from melanoma patient plasma. We longitudinally monitor the EV phenotypic evolution of eight melanoma patients receiving targeted therapy and find specific EV profiles involved in the development of drug resistance, reflecting the potential of EV phenotyping for monitoring treatment responses.
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spelling pubmed-70439132020-03-04 Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma Wang, Jing Wuethrich, Alain Sina, Abu Ali Ibn Lane, Rebecca E. Lin, Lynlee L. Wang, Yuling Cebon, Jonathan Behren, Andreas Trau, Matt Sci Adv Research Articles Monitoring targeted therapy in real time for cancer patients could provide vital information about the development of drug resistance and improve therapeutic outcomes. Extracellular vesicles (EVs) have recently emerged as a promising cancer biomarker, and EV phenotyping shows high potential for monitoring treatment responses. Here, we demonstrate the feasibility of monitoring patient treatment responses based on the plasma EV phenotypic evolution using a multiplex EV phenotype analyzer chip (EPAC). EPAC incorporates the nanomixing-enhanced microchip and the multiplex surface-enhanced Raman scattering (SERS) nanotag system for direct EV phenotyping without EV enrichment. In a preclinical model, we observe the EV phenotypic heterogeneity and different phenotypic responses to the treatment. Furthermore, we successfully detect cancer-specific EV phenotypes from melanoma patient plasma. We longitudinally monitor the EV phenotypic evolution of eight melanoma patients receiving targeted therapy and find specific EV profiles involved in the development of drug resistance, reflecting the potential of EV phenotyping for monitoring treatment responses. American Association for the Advancement of Science 2020-02-26 /pmc/articles/PMC7043913/ /pubmed/32133394 http://dx.doi.org/10.1126/sciadv.aax3223 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Research Articles
Wang, Jing
Wuethrich, Alain
Sina, Abu Ali Ibn
Lane, Rebecca E.
Lin, Lynlee L.
Wang, Yuling
Cebon, Jonathan
Behren, Andreas
Trau, Matt
Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
title Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
title_full Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
title_fullStr Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
title_full_unstemmed Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
title_short Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
title_sort tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043913/
https://www.ncbi.nlm.nih.gov/pubmed/32133394
http://dx.doi.org/10.1126/sciadv.aax3223
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