Routes and mechanisms of extracellular vesicle uptake

Extracellular vesicles (EVs) are small vesicles released by donor cells that can be taken up by recipient cells. Despite their discovery decades ago, it has only recently become apparent that EVs play an important role in cell-to-cell communication. EVs can carry a range of nucleic acids and proteins which can have a significant impact on the phenotype of the recipient. For this phenotypic effect to occur, EVs need to fuse with target cell membranes, either directly with the plasma membrane or with the endosomal membrane after endocytic uptake. EVs are of therapeutic interest because they are deregulated in diseases such as cancer and they could be harnessed to deliver drugs to target cells. It is therefore important to understand the molecular mechanisms by which EVs are taken up into cells. This comprehensive review summarizes current knowledge of EV uptake mechanisms. Cells appear to take up EVs by a variety of endocytic pathways, including clathrin-dependent endocytosis, and clathrin-independent pathways such as caveolin-mediated uptake, macropinocytosis, phagocytosis, and lipid raft–mediated internalization. Indeed, it seems likely that a heterogeneous population of EVs may gain entry into a cell via more than one route. The uptake mechanism used by a given EV may depend on proteins and glycoproteins found on the surface of both the vesicle and the target cell. Further research is needed to understand the precise rules that underpin EV entry into cells

Cisplatin induces the release of extracellular vesicles from ovarian cancer cells that can induce invasiveness and drug resistance in bystander cells

Ovarian cancer has a poor overall survival which is partly caused by resistance to drugs such as cisplatin. Resistance can be acquired as a result of changes to the tumour or due to altered interactions within the tumour microenvironment. Extracellular vesicles (EVs), small lipid-bound vesicles that are loaded with macromolecular cargo and released by cells, are emerging as mediators of communication in the tumour microenvironment. We previously showed that EVs mediate the bystander effect, a phenomenon in which stressed cells can communicate with neighbouring naïve cells leading to various effects including DNA damage; however, the role of EVs released following cisplatin treatment has not been tested. Here we show that treatment of cells with cisplatin led to the release of EVs that could induce invasion and increased resistance when taken up by bystander cells. This coincided with changes in p38 and JNK signalling, suggesting that these pathways may be involved in mediating the effects. We also show that EV uptake inhibitors could prevent this EV-mediated adaptive response and thus sensitise cells in vitro to the effects of cisplatin. Our results suggest that preventing pro-tumourigenic EV crosstalk during chemotherapy is a potential therapeutic target for improving outcome in ovarian cancer patients

Radiation-responsive miRNAs predicted by miRStress are biologically relevant.

<p>A: The miRNAs which are most frequently deregulated following radiation stress, as reported by miRStress, were used to ‘predict’ radiation-responsive pathways, as described in the methods. Control pathways were selected by using a list of control miRNAs. These were then compared to a list of KEGG pathways which are observed (as opposed to predicted) to actually change following radiation (in a total of 18 datasets). The average frequency with which the predicted control or radiation pathways appears in the observed pathways is shown. On average the radiation predicted-pathways are more frequently present in the observed pathways (t test, p 0.002). In other words, the radiation miRNAs are predicted to target pathways which actually change following radiation. Error bars show standard error of the mean for 20 (for radiation) and 21 (for control) pathways. B: Radiation and control miRNAs used in part A were used to test for correlations between SF5 (surviving fraction of cells following a 5 Gray radiation dose) and miRNA level across the NCI-60 panel. A Pearson correlation was obtained for each radiation and control miRNA (not all were available on the microarray platform). The average Pearson correlation value (see methods) for the control and radiation miRNAs is shown. The radiation miRNAs have a significantly higher correlation with radiosensitivity compared to the control miRNAs (t test, p = 0.02). </p