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Updated: Sep 25, 2026

In Vivo Immunogenicity Screening of Tumor-Derived Extracellular Vesicles by Flow Cytometry of Splenic T Cells
Published on: September 23, 2021
Extracellular vesicle-mediated drug resistance in cancer
Baiwei Zhao1, Yongming Chen1, Hiba Khan2
1State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Abstract:
Drug resistance remains a major challenge to successful cancer treatment. Although cell-autonomous genetic, molecular, and cellular modifications have historically been linked to resistance, there is growing evidence that extracellular vesicles (EVs) can promote the intercellular transfer of resistance-associated components. With a focus on the ways in which EV cargo modifies treatment response, this review critically investigates the role of EVs in therapeutic resistance in breast cancer, lung cancer, leukemia, glioblastoma, pancreatic cancer, and melanoma. The effects of major EV-associated factors on drug efflux, apoptosis, survival signaling, DNA repair, and metabolic adaptation are discussed. These factors include drug-efflux transporters, anti-apoptotic and oncogenic proteins, non-coding RNAs, DNA-repair molecules, metabolic components, and drug-sequestering molecules. As components of the tumor microenvironment that may strengthen treatment resistance, the review also considers EVs released by mesenchymal stromal cells, cancer-associated fibroblasts, and tumor-associated macrophages. By combining these results, we present a community-level view of EV-mediated resistance, where multidrug resistance and treatment failure may be caused by tumor-intrinsic resistance, horizontal transfer via tumor-derived EVs, and TME-derived EV signaling. Lastly, the potential of EVs as delivery systems, biomarkers, predictors, and therapeutic targets is examined, along with the present translational constraints and open issues. This synthesis emphasizes EV-mediated communication as a crucial addition to traditional cancer medication resistance models.
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