Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma

Jing Wang, Alain Wuethrich, Abu Ali Ibn Sina, Rebecca E. Lane, Lynlee L. Lin, Yuling Wang, Jonathan Cebon, Andreas Behren, Matt Trau

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
14 Downloads (Pure)

Abstract

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.
Original languageEnglish
Article numbereaax3223
Pages (from-to)1-13
Number of pages13
JournalScience Advances
Volume6
Issue number9
DOIs
Publication statusPublished - 26 Feb 2020

Bibliographical note

Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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