521 An Integrated Workflow for Identification, Enrichment, and Molecular Profiling of Tumor-Derived and Non-Tumor Derived Plasma Extracellular Vesicles in Glioblastoma Patients

Abstract

INTRODUCTION: Molecular analysis of bulk glioblastoma plasma EVs has demonstrated tumor-associated miRNA expression profiles. It remains unclear whether this molecular signature originates from tumor EVs or non-tumor EVs. Elucidating differences in molecular cargo in EVs originating from different cells could potentially identify highly specific EV biomarkers for glioblastoma diagnosis and disease progression monitoring. METHODS: EVs were isolated in vitro from human glioblastoma cells (dBT116)and CD14+ monocytes alone and as co-cultures +/- 5-amino levulinic acid (5-ALA) treatment. CD11b (myeloid marker) and protoporphyrin IX (tumor marker) expression were determined by flow cytometry. In addition, an EV characterization panel including 9 EV markers was further developed for GBM plasma samples. All assays and controls were performed per published guidelines. We utilized spectral flow cytometry to establish our gating strategy then used standard flow cytometry sorting to enrich plasma EVs into different subpopulations. LC-MS/MS proteomics was performed on sorted EVs. RESULTS: Protoporphyrin IX positivity was specific to tumor derived EVs. Rigorous assay controls confirmed that our EV characterization panel followed the current ISEV guideline for EV flow cytometry study. Our integrated workflow characterizes and can enrich plasma EVs with high efficiency, confirmed by the presence of multiple EV-associated proteins in proteomic analysis. Initial proteomic analysis suggests protoporphyrin IX-positive tumor EVs have unique protein expression profiles compared to CD11b-positive myeloid EVs. CONCLUSIONS: In this study, we were able developed an integrated workflow characterizing plasma EVs and enriching them into different subpopulations based on cell of origin. Application of this workflow in future larger cohorts will be conducted to identify additional specific plasma EV biomarkers for GBM.