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A magneto-activated nanoscale cytometry platform for molecular profiling of small extracellular vesicles

Kangfu Chen, Bill T. V. Duong, Sharif U. Ahmed, Piriththiv Dhavarasa, Zongjie Wang, Mahmoud Labib, Connor Flynn, Jingya Xu, Yi Y. Zhang, Hansen Wang, Xiaolong Yang, Jagotamoy Das, Hossein Zargartalebi, Yuan Ma and Shana O. Kelley ()
Additional contact information
Kangfu Chen: University of Toronto
Bill T. V. Duong: University of Toronto
Sharif U. Ahmed: University of Toronto
Piriththiv Dhavarasa: University of Toronto
Zongjie Wang: Northwestern University
Mahmoud Labib: University of Toronto
Connor Flynn: University of Toronto
Jingya Xu: University of Toronto
Yi Y. Zhang: University of Toronto
Hansen Wang: University of Toronto
Xiaolong Yang: University of Toronto
Jagotamoy Das: Northwestern University
Hossein Zargartalebi: University of Toronto
Yuan Ma: University of Toronto
Shana O. Kelley: University of Toronto

Nature Communications, 2023, vol. 14, issue 1, 1-15

Abstract: Abstract Exosomal PD-L1 (exoPD-L1) has recently received significant attention as a biomarker predicting immunotherapeutic responses involving the PD1/PD-L1 pathway. However, current technologies for exosomal analysis rely primarily on bulk measurements that do not consider the heterogeneity found within exosomal subpopulations. Here, we present a nanoscale cytometry platform NanoEPIC, enabling phenotypic sorting and exoPD-L1 profiling from blood plasma. We highlight the efficacy of NanoEPIC in monitoring anti-PD-1 immunotherapy through the interrogation of exoPD-L1. NanoEPIC generates signature exoPD-L1 patterns in responders and non-responders. In mice treated with PD1-targeted immunotherapy, exoPD-L1 is correlated with tumor growth, PD-L1 burden in tumors, and the immune suppression of CD8+ tumor-infiltrating lymphocytes. Small extracellular vesicles (sEVs) with different PD-L1 expression levels display distinctive inhibitory effects on CD8 + T cells. NanoEPIC offers robust, high-throughput profiling of exosomal markers, enabling sEV subpopulation analysis. This platform holds the potential for enhanced cancer screening, personalized treatment, and therapeutic response monitoring.

Date: 2023
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DOI: 10.1038/s41467-023-41285-8

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