Uncovering exRNA and protein determinants of secreted vesicle heterogeneity by flow cytometric purification of vesicle subsets from cells and plasma

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PROJECT SUMMARY All cells secrete small portions of their protein and RNA contents as lipid vesicles called extracellular vesicles (EVs). In various diseases, normal EV cargos change as disease initiate and progress, altering what proteins and RNAs are packaged into them. Small EVs, called exosomes, and larger EVs called microvesicles carry many of these disease-associated cargos and we have shown that both protein and RNA exosomal and microvesicle constituents change with cancer progression; such EVs can end up in the biofluids of the body including blood, cerebral spinal fluid, urine and saliva providing a non invasive and readily available source of biomarkers. Recently it has been shown that EVs released from cells are highly heterogeneous in nature and that only small fractions are disease associated. Furthermore many extracellular constituents that were thought to be associated with vesicles are not, either arising from non-vesicular or other lipoprotein complexes of exRNAs and proteins. To advance the field beyond incremental science, we require a superior understanding of the relationship between molecular heterogeneity (cargo composition) and physical heterogeneity for the various types of vesicles secreted by cells and tissues. To this we developed, Fluorescence-Activated Vesicle Sorting (FAVS), as a means to analyze and purify small and large EVs, on a per vesicle basis, from various biofluids. FAVS is generally accessible since it uses a flow sorter available at many research institutions, so it is an ideal method to be applied by this consortium. In this proposal we will demonstrate the capability of FAVS to purify small EVs derived from colorectal cancer (CRC) and Glioblastoma Multiforme (GBM) models, including cell line, PDX, mouse plasma and patient plasma sources of EVs. Both cancers are significant health risks. GBMs are a common, yet incurable, malignant brain tumor (over 12,000 new cases predicted in 2018) and CRC is the third leading cause of cancer deaths in the US. In the first Aim of this proposal we will optimize the FAVS pipeline by: validating preprocessing steps that separate EVs based on their physical heterogeneity (size and density), before performing FAVS; testing new candidate reagents for use with FAVS that more clearly delineates EV subgroups; and uncovering new RNA and protein markers of EV heterogeneity. Because such cancers are often associated with increased expression and activation of Epidermal Growth Factor Receptor (EGFR) we will use EGFR-targeted antibodies, along with other EV cargo binding antibodies, to purify EV subsets from these cancers. We will use EGFR antibodies to analyze CRC and GBM associated EVs as we have done previously, using antibodies that bind total and active EGFR. The second Aim of the grant is to uncover tissue specific markers of EV production by using a cell specific EV-tagging methodology in mouse genetic models. We will also use orthotopically implanted GBM and CRC PDX xenografts to purify circulating EV subsets to compare to EVs purified from patient plasmas. In the third Aim we will use our FAVS pipeline to purify patient derived EVs from plasma to credentialize EV RNA/protein constituents discovered by this work.