Nano-sized extracelullar vesicles (EVs) released by various cell types play important roles in a plethora of (patho)physiological processes and are increasingly recognized as biomarkers for disease. In addition, engineered EV and EV-inspired liposomes hold great potential as drug delivery systems. Major technologies developed for high-throughput analysis of individual EV include nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (tRPS) and high-resolution flow cytometry (hFC). Currently, there is a need for comparative studies on the available technologies to improve standardization of vesicle analysis in diagnostic or therapeutic settings.We investigated the possibilities, limitations and comparability of NTA, tRPS and hFC for analysis of tumor cell-derived EVs and synthetic mimics (i.e. differently sized liposomes). NTA and tRPS instrument settings were identified that significantly affected the quantification of these particles. Furthermore, we detailed the differences in absolute quantification of EVs and liposomes using the three technologies. This study increases our understanding of possibilities and pitfalls of NTA, tRPS and hFC, which will benefit standardized and large-scale clinical application of (engineered) EVs and EV-mimics in the future.

Glioblastoma multiforme (GBM) is the most common primary brain tumor and is without exception lethal. GBMs modify the immune system, which contributes to the aggressive nature of the disease. Particularly, cells of the monocytic lineage, including monocytes, macrophages and microglia, are affected. We investigated the influence of GBM‐derived extracellular vesicles (EVs) on the phenotype of monocytic cells. Proteomic profiling showed GBM EVs to be enriched with proteins functioning in extracellular matrix interaction and leukocyte migration. GBM EVs appeared to skew the differentiation of peripheral blood‐derived monocytes to alternatively activated/M2‐type macrophages. This was observed for EVs from an established cell line, as well as for EVs from primary cultures of GBM stem‐like cells (GSCs). Unlike EVs of non‐GBM origin, GBM EVs induced modified expression of cell surface proteins, modified cytokine secretion (e.g., an increase in vascular endothelial growth factor and IL‐6) and increased phagocytic capacity of the macrophages. Most pronounced effects were observed upon incubation with EVs from mesenchymal GSCs. GSC EVs also affected primary human microglia, resulting in increased expression of Membrane type 1‐matrix metalloproteinase, a marker for GBM microglia and functioning as tumor‐supportive factor. In conclusion, GBM‐derived EVs can modify cells of the monocytic lineage, which acquire characteristics that resemble the tumor‐supportive phenotypes observed in patients.

BackgroundUnderstanding the pathogenic role of extracellular vesicles (EVs) in disease and their potential diagnostic and therapeutic utility is extremely reliant on in-depth quantification, measurement and identification of EV sub-populations. Quantification of EVs has presented several challenges, predominantly due to the small size of vesicles such as exosomes and the availability of various technologies to measure nanosized particles, each technology having its own limitations.Materials and MethodsA standardized methodology to measure the concentration of extracellular vesicles (EVs) has been developed and tested. The method is based on measuring the EV concentration as a function of a defined size range. Blood plasma EVs are isolated and purified using size exclusion columns (qEV) and consecutively measured with tunable resistive pulse sensing (TRPS). Six independent research groups measured liposome and EV samples with the aim to evaluate the developed methodology. Each group measured identical samples using up to 5 nanopores with 3 repeat measurements per pore. Descriptive statistics and unsupervised multivariate data analysis with principal component analysis (PCA) were used to evaluate reproducibility across the groups and to explore and visualise possible patterns and outliers in EV and liposome data sets.ResultsPCA revealed good reproducibility within and between laboratories, with few minor outlying samples. Measured mean liposome (not filtered with qEV) and EV (filtered with qEV) concentrations had coefficients of variance of 23.9% and 52.5%, respectively. The increased variance of the EV concentration measurements could be attributed to the use of qEVs and the polydisperse nature of EVs.ConclusionThe results of this study demonstrate the feasibility of this standardized methodology to facilitate comparable and reproducible EV concentration measurements.

Scanning ion occlusion sensing technology enables the quantification of MVs in biological samples without the requirement of MV isolation and/or labeling. This offers a highly valuable addition to the currently used repertoire of MV quantification methods.