To develop and subsequently get cancer researchers to use organotypic three-dimensional (3D) models that can recapitulate the complexity of human in vivo tumors in an in vitro setting, it is important to establish what in vitro model(s) researchers are currently using and the reasons why. Thus, we developed a survey on this topic, obtained ethics approval, and circulated it throughout the world. The survey was completed by 101 researchers, across all career stages, in academia, clinical or industry settings. It included 40 questions, many with multiple options. Respondents reported on their field of cancer research; type of cancers studied; use of two-dimensional (2D)/monolayer, 2.5D and/or 3D cultures; if using co-cultures, the cell types(s) they co-culture; if using 3D cultures, whether these involve culturing the cells in a particular way to generate spheroids, or if they use additional supports/scaffolds; techniques used to analyze the 2D/2.5D/3D; and their downstream applications. Most researchers (>66%) only use 2D cultures, mainly due to lack of experience and costs. Despite most cancer researchers currently not using the 3D format, >80% recognize their importance and would like to progress to using 3D models. This suggests an urgent need to standardize reliable, robust, reproducible methods for establishing cost-effective 3D cell culture models and their subsequent characterization.

Blood–brain barrier (BBB) dysfunction is a key hallmark in the pathology of many neuroinflammatory disorders. Extracellular vesicles (EVs) are lipid membrane-enclosed carriers of molecular cargo that are involved in cell-to-cell communication. Circulating endothelial EVs are increased in the plasma of patients with neurological disorders, and immune cell-derived EVs are known to modulate cerebrovascular functions. However, little is known about whether brain endothelial cell (BEC)-derived EVs themselves contribute to BBB dysfunction. Human cerebral microvascular cells (hCMEC/D3) were treated with TNFα and IFNy, and the EVs were isolated and characterised. The effect of EVs on BBB transendothelial resistance (TEER) and leukocyte adhesion in hCMEC/D3 cells was measured by electric substrate cell-substrate impedance sensing and the flow-based T-cell adhesion assay. EV-induced molecular changes in recipient hCMEC/D3 cells were analysed by RT-qPCR and Western blotting. A stimulation of naïve hCMEC/D3 cells with small EVs (sEVs) reduced the TEER and increased the shear-resistant T-cell adhesion. The levels of microRNA-155, VCAM1 and ICAM1 were increased in sEV-treated hCMEC/D3 cells. Blocking the expression of VCAM1, but not of ICAM1, prevented sEV-mediated T-cell adhesion to brain endothelia. These results suggest that sEVs derived from inflamed BECs promote cerebrovascular dysfunction. These findings may provide new insights into the mechanisms involving neuroinflammatory disorders.

To study and exploit extracellular vesicles (EVs) for clinical benefit as biomarkers, therapeutics, or drug delivery vehicles in diseases such as cancer, typically we need to separate them from the biofluid into which they have been released by their cells of origin. For cultured cells, this fluid is conditioned medium (CM). Previous studies comparing EV separation approaches have typically focused on CM from one cell line or pooled samples of other biofluids. We hypothesize that this is inadequate and that extrapolating from a single source of EVs may not be informative. Thus, in our study of methods not previous compared (i.e., the original differential ultracentrifugation (dUC) method and a PEG followed by ultracentrifugation (PEG + UC) method), we analyzed CM from three different HER2-positive breast cancer cell lines (SKBR3, EFM192A, HCC1954) that grow in the same culture medium type. CM from each was collected and equally divided between both protocols. The resulting isolates were compared on seven characteristics/parameters including particle size, concentration, structure/morphology, protein content, purity, detection of five EV markers, and presence of HER2. Both dUC and PEG + UC generated reproducible data for any given breast cancer cell lines’ CM. However, the seven characteristics of the EV isolates were cell line- and method-dependent. This suggests the need to include more than one EV source, rather than a single or pooled sample, when selecting an EV separation method to be advanced for either research or clinical purposes.