Abstract

Glioblastoma multiforme (GBM) is highly malignant and lethal brain tumor, which displays cellular hierarchies with a sub-population of self-renewing and highly tumorigenic GBM stem cells (GSCs). To shape the tumor stroma to their own advantage, GSCs interact with other cells in the tumor microenvironment, however key signaling molecules that mediate such interactions remain to be fully characterized. Extracellular vesicles (EVs) have recently emerged as important mediators of inter-cellular communication which act by facilitating the horizontal transfer of bioactive molecules (including microRNAs), highlighting them as potential novel targets for therapeutic intervention. Discovery of microRNAs significantly expanded the knowledge and availability of strategies for GBM therapy. Their molecular signatures are associated with GBM/GSC subtypes and, in contrast to other components of EV cargo, can predict survival of GBM patients. Using well characterized panel of patient-derived GSCs we confirmed that GSC heterogeneity is reflected by disparate microRNA expression. Unbiased analysis of GSC heterogeneity revealed coherent microRNA-dependent molecular modules when analyzed along with mRNA expression profiling. Analysis of GSC EV microRNAome revealed only partial overlap with cellular expression profiles. To test the hypothesis that EV secretion of microRNAs reflects both their cellular status (e.g. miR-31) and EV-specific loading (e.g. miR-4443), we validated the secretion of microRNAs by analyzing their precursor and mature form in cells and EVs. The transfer and uptake of EVs and EV-microRNAs were monitored using fluorescence-labeled EVs and microRNAs. The functional transfer of EV microRNAs was monitored by analysis of direct mRNA targets in the recipient cells from the brain microenvironment (GSC, endothelial cells and astrocytes). We demonstrated that the EV transfer of active microRNAs between the cells with different molecular background results in direct and indirect targeting of recipient cell-specific effectors (e.g. ID2, p21). Our results shed a light on an additional layer of the complexity in heterogeneity of GBM.

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