Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma.

2020-02

Wang, Jing

Wuethrich, Alain

Sina, Abu Ali Ibn

Lane, Rebecca E

Lin, Lynlee L

Wang, Yuling

Cebon, Jonathan S

Behren, Andreas

Trau, Matt

Journal Article

0000-0001-6080-7998

0000-0001-9569-0478

0000-0001-8099-3863

0000-0002-7650-389X

0000-0003-3100-9668

0000-0003-3627-7397

0000-0002-3898-950X

0000-0001-5329-280X

0000-0001-5516-1280

10.1126/sciadv.aax3223

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.

link

Science Advances 2020; 6(9): eaax3223

Science Advances