Abstract LB-A06: Pipeline for High Throughput Analysis of Exosomes in Clinical Biofluids

Purpose/Objective(s): Because Extracellular Vesicles (EVs) carry surface receptors that are characteristic of their cells of origin, EVs have tremendous potential as non-invasive biomarkers for diagnosis, risk-stratification, treatment selection, and treatment monitoring. We developed a first-in-class pipeline to characterize EV heterogeneity and provide high-sensitivity quantification of informative EVs in biofluids before, during, and after treatment. By combining multiplex assays with high-resolution, single EV flow cytometric methods together into a Mutiplex-to-Single EV Analysis (Mt-SEA) pipeline, we are able to characterize a broad range of relevant EV subsets, while also accurately measuring the concentration of specific EV populations. Exploratory studies presented here validate the performance of Mt-SEA method by confirming strong correlations of liquid biopsy EV repertoires with tumor burden and responses to treatment. Furthermore, EV analysis with Mt-SEA may identify previously unrecognized prognostic epitopes or EVs subsets. Materials/Methods: To evaluate the use of this pipeline in an exploratory clinical cohort, we evaluated EVs from plasma samples of Adult T Cell Leukemia/Lymphoma patients receiving palliative radiation. Plasma was obtained before and after treatment (n = 5 treatment courses). A customized multiplex array was used with detection antibodies to identify more than 40 major EV subsets. General exosome and EV detection epitopes included CD63, CD9, and CD81. Tumor-specific epitopes for each patient included CD4, CD5, and CD25, based on available histo-/cyto-pathology results. Next, high-resolution single EV analyses were performed with nanoFACS sorting and a prototype nanoFCM analyzer. Results: The Mt-SEA pipeline provided a broad survey of EV populations, followed by individual EV analysis ATLL-derived EVs were detected in each pre-treatment sample, with reduced specific ATLL-derived EV subsets concentrations at the end of treatment. Furthermore, ATLL-specific EVs from patients with progressive systemic disease prior to treatment were found to carry CD44 and CD133 epitopes, consistent with increasing tumor aggressiveness. Responses to treatment that were clinically evident mirrored changes in the Mt-SEA EV profiles, and Mt-SEA identified new candidate prognostic EV profiles associated with clinical outcomes that would not have been predicted. Conclusions: Optimal leverage the information carried by tumor- and immune cell-derived EVs (to use EVs as clinical biomarkers) will require a combination of methods to 1) broadly characterize EVs and 2) rigorously enumerate specific selected EV subsets using single molecule detection. The Mt-SEA pipeline achieves both of these goals. Our exploratory study with these ATLL cases demonstrates that Mt-SEA provides unexpected insights into tumor biology, along with robust estimations of concentrations of EV subsets of interest. Detection of tumor-associated EVs and detection of EV repertoire changes during treatment paves the way to future evaluation of the Mt-SEA pipeline for personalized, adaptive therapies in a wider range of tumor types. Citation Format: Jennifer Jones, Joshua Welsh, Jason Savage, Jenn Marte, James Gulley, Kevin Conlon, Thomas Waldmann, Kevin Camphausen, Jay Berzofsky. Pipeline for High Throughput Analysis of Exosomes in Clinical Biofluids [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr LB-A06.