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Page 42                                             Extracell Vesicles Circ Nucleic Acids 2020;1:20-56  I  http://dx.doi.org/10.20517/evcna.2020.10

               Methods: This pilot study reports the longitudinal study of EGFR mutations carried in extracellular vesicle
               protein (evProtein) and RNA (evRNA) to monitor metastatic non-small cell lung cancer patients. We
               enrolled 10 NSCLC patients: 8 with exon 19 deletion mutations and 2 with co-harbored L858R sensitizing
               and T790M resistance mutations. We used ultracentrifugation to isolate EVs from dilute plasma before
               testing the EVs for mutations based on the patient’s original tumor biopsy. In our work, we used droplet
               digital PCR (ddPCR) to test for mutations in the EV-RNA and western blots to test for sensitizing
               mutations in EV-protein.
               Results: In our cohort of 10 NSCLC patients, mutant EV-RNA was detected in 9/10 patients. The overall
               detection rate for all EV-RNA mutations was 60%. Exon 19 del was detected in 7/8 patients, and in 78%
               of samples tested. While the detection rate of L858R remained moderate at 60%, the detection of the
               notoriously challenging T790M mutation was low, at 25% Sensitizing mutations were detected in 12/21
               (57%) EV-Protein samples. EV-RNA and EV-Protein were then compared to clinical data and showed
               that increasing EV-RNA mutation burden mirrored disease progression. For 6/7 patients who were
               longitudinally monitored, EV-RNA mutation burden mirrored clinical trajectory. Increasing exon 19 del
               exoRNA burden mirrored disease progression in two patients, while decreasing burden mirrored stable
               disease in three patients. The three patients who saw a decrease in exon 19 del burden have remained
               clinically stable for an average of 192 ± 9 days after the final blood draw, while those who had progressive
               disease are now deceased. Of the two patients with L858R/T790M mutations, one patient’s EV-RNA burden
               mirrored disease trajectory, while the other did not. Conversely, EV-Protein did not appear to mirror
               clinical progression and was largely patient dependent.
               Conclusions: In this novel proof of concept study, extracellular vesicles were screened for previously
               identified EGFR mutations carried by each patient. Changes in EV-RNA were found to correlate with
               disease trajectory; however, the clinical implications of EV-Protein remain unclear. This study demonstrates
               the potential utility of characterizing both extracellular vesicle RNA and protein cargo, allowing for multi-
               faceted analyses of a patient’s disease.



               29. The role of extracellular vesicles in cancer-related fatigue


               Authors: Dilorom Sass, Wendy Fitzgerald, Leorey Saligan, Leonid Margolis
               E-mail: delia.sass@nih.gov
               Affiliations: National Institute of Nursing Research, National Institute of Child Health and Human Development,
               USA.
               Abstracts:
               Purpose/Background: Cancer Related Fatigue (CRF) is the most prevalent and distressing symptom
               associated with cancer and its treatments. The etiology of CRF is shown to be multifactorial, yet the
               exact mechanisms of CRF are poorly understood. The purpose of this study was to investigate the role of
               extracellular vesicles (EVs) in the inflammation mechanism of CRF. EVs are ubiquitously present in the
               body, exchange material between cells and can serve as biomarkers for diagnosis and treatment. No prior
               studies have investigated EV markers as a measure of inflammation in CRF.
               Methods: Plasma was collected from men with non-metastatic prostate cancer receiving external
               beam radiation therapy (EBRT) (n = 40) at two time points: at the start of (T1) and 3 months after
               EBRT (T2). Fatigue was assessed using the Functional Assessment of Cancer Therapy - Fatigue (FACT-F).
               Characterization of the EVs included: size and concentrations using Nanoparticle Tracking Analysis
               (NTA), morphology using electron microscopy, and EV markers (CD9, CD81, TSG101) using western
               blot. Cytokines were measured in EV-associated and soluble (EV free) fractions using a multiplexed
               immunoassay system.
               Findings: Log fold change of EV-associated analytes showed increase in Eotaxin, hsp27, IP10, MIP3α from
               T1 to T2 in fatigued patients compared to non-fatigued. Whereas, in soluble fraction, only survivin had a
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