Purpose Triple-negative breast cancer (TNBC), an aggressive breast cancer subtype, is genetically heterogeneous which challenges the identification of clinically effective molecular makers. Extracellular vesicles (EVs) are key players in the intercellular signaling communication and have been shown to be involved in tumorigenesis. The main goal of this study was to evaluate the role and mechanisms of EVs derived from TNBC cells in modulating proliferation and cytotoxicity to chemotherapeutic agents in non-tumorigenic breast cells (MCF10A). Methods EVs were isolated from TNBC cell lines and characterized by nanoparticle tracking analysis, Western blot, and transmission electron microscopy. MCF10A cells were treated with the isolated EVs and evaluated for cell proliferation and cytotoxicity to Docetaxel and Doxorubicin by the MTT and MTS assays, respectively. Gene and miRNA expression profiling was performed in the treated cells to determine expression changes that may be caused by EVs treatment. Results MCF10A cells treated with HCC1806-EVs (MCF10A/HCC1806-EVs) showed a significant increase in cell proliferation and resistance to the therapeutic agents tested. No significant effects were observed in the MCF10A cells treated with EVs derived from MDA-MB-231 cells. Gene and miRNA expression profiling revealed 138 genes and 70 miRNAs significantly differentially expressed among the MCF10A/HCC1806-EVs and the untreated MCF10A cells, affecting mostly the PI3K/AKT, MAPK, and HIF1A pathways. Conclusion EVs isolated from the HCC1806 TNBC cells are capable of inducing proliferation and drug resistance on the non-tumorigenic MCF10A breast cells, potentially mediated by changes in genes and miRNAs expression associated with cell proliferation, apoptosis, invasion, and migration.

Mammalian cells release a heterogeneous array of extracellular vesicles (EVs) that contribute to intercellular communication by means of the cargo that they carry. To resolve EV heterogeneity and determine if cargo is partitioned into select EV populations, we developed a method named "EV Fingerprinting" that discerns distinct vesicle populations using dimensional reduction of multiparametric data collected by quantitative single-EV flow cytometry. EV populations were found to be discernible by a combination of membrane order and EV size, both of which were obtained through multiparametric analysis of fluorescent features from the lipophilic dye Di-8-ANEPPS incorporated into the lipid bilayer. Molecular perturbation of EV secretion and biogenesis through respective ablation of the small GTPase Rab27a and overexpression of the EV-associated tetraspanin CD63 revealed distinct and selective alterations in EV populations, as well as cargo distribution. While Rab27a disproportionately affects all small EV populations with high membrane order, the overexpression of CD63 selectively increased the production of one small EV population of intermediate membrane order. Multiplexing experiments subsequently revealed that EV cargos have a distinct, nonrandom distribution with CD63 and CD81 selectively partitioning into smaller vs larger EVs, respectively. These studies not only present a method to probe EV biogenesis but also reveal how the selective partitioning of cargo contributes to EV heterogeneity.

MicroRNAs derived from extracellular vesicles (EV-miRNAs) are circulating miRNAs considered as potential new diagnostic markers for cancer that can be easily detected in liquid biopsies. In this study, we performed RNA sequencing analysis as a screening strategy to identify EV-miRNAs derived from serum of clinically well-annotated breast cancer (BC) patients from the south of Brazil. EVs from three groups of samples (healthy controls (CT), luminal A (LA), and triple-negative (TNBC)) were isolated from serum using a precipitation method and analyzed by RNA-seq (screening phase). Subsequently, four EV-miRNAs (miR-142-5p, miR-150-5p, miR-320a, and miR-4433b-5p) were selected to be quantified by quantitative real-time PCR (RT-qPCR) in individual samples (test phase). A panel composed of miR-142-5p, miR-320a, and miR-4433b-5p distinguished BC patients from CT with an area under the curve (AUC) of 0.8387 (93.33% sensitivity, 68.75% specificity). The combination of miR-142-5p and miR-320a distinguished LA patients from CT with an AUC of 0.9410 (100% sensitivity, 93.80% specificity). Interestingly, decreased expression of miR-142-5p and miR-150-5p were significantly associated with more advanced tumor grades (grade III), while the decreased expression of miR-142-5p and miR-320a was associated with a larger tumor size. These results provide insights into the potential application of EVs-miRNAs from serum as novel specific markers for early diagnosis of BC.