Creation of a resource for deconvolution of circulating extracellular vesicle (EV) small RNA profiles based on tissue-specific signatures for prediction of response to immunotherapy 2233

Abstract Description Factors that influence response to cancer immunotherapy (IT) are still poorly understood but will be critical in improving patient outcomes. A priori molecular states of immune cells can be important in determining response to IT (Moshe Sade-Feldman et al. 2018), therefore we hypothesized that since immune cells likely disproportionately contribute to the circulating pool of extracellular vesicles (EVs) in blood, these transcriptional states may be detected in EVs. Small RNA from EVs is packaged from the cell-of-origin through a non-stochastic process that is also poorly understood, thus complicating interpretation of results without high-quality reference data for deconvolution. Our goal was to sequence small RNA in EVs from monocultures of cell lines representing different lineages and activation states to build this resource. THP-1, PLB895, Platelets, NALM-6, RAJI, JURKAT and SupT1 cells were cultured and EVs isolated for sequencing. B-lineage cells were activated with anti-IgM and T cells with anti-CD3/ CD28. Stimulation of B-lineage was confirmed by CD80/CD86 expression, while T-lineage cells were analyzed at 48h with IL-2 ELISA (2-fold increase) and proliferation assay (30-39% increase). Small (<200 nm) and large (<1 µm) EVs were collected by filtration and sequenced. Transcriptome profiles established by this work will be key in reusing public liquid biopsy sequencing data and in determining if predictive IT signals are reflected in EV content from host immune cells. Funding Sources Supported by Research New Brunswick, and funds from the Atlantic Cancer Research Institute. Topic Categories Computational and Systems Immunology (COMP)