Development of extracellular vesicles-based classifier for detection of early-stage bladder, ovarian, and pancreatic cancer.

person Juan Pablo Hinestrosa Biological Dynamics, San Diego, CA info_outline Juan Pablo Hinestrosa, Razelle Kurzrock, Jean Lewis, Nick Schork, Ashish M. Kamat, Andrew M. Lowy, Ramez Nassef Eskander, Orlando Perrera, David Searson, Iryna Clark, Heath Balcer, Mark J. Adler, Scott Michael Lippman, Rajaram Krishnan

Authors person Juan Pablo Hinestrosa Biological Dynamics, San Diego, CA info_outline Juan Pablo Hinestrosa, Razelle Kurzrock, Jean Lewis, Nick Schork, Ashish M. Kamat, Andrew M. Lowy, Ramez Nassef Eskander, Orlando Perrera, David Searson, Iryna Clark, Heath Balcer, Mark J. Adler, Scott Michael Lippman, Rajaram Krishnan Organizations Biological Dynamics, San Diego, CA, University of California San Diego, Moores Cancer Center, La Jolla, CA, Biological Dynamics, Inc., San Diego, CA, City of Hope, Duarte, CA, The University of Texas MD Anderson Cancer Center, Houston, TX, UCSD Moores Cancer Center, La Jolla, CA, UC San Diego Moores Cancer Center, San Diego, CA, Biological Dynamics, Inc, San Diego, CA, UC San Diego Moores Cancer Center, Vista, CA, University of California San Diego, La Jolla, CA Abstract Disclosures Research Funding Pharmaceutical/Biotech Company Biological Dynamics Background: Many cancers are lethal because they present with metastatic disease. Because localized/resectable tumors produce vague symptoms, diagnosis is delayed. In pancreatic cancer, only ̃10% of patients survive five years, and it will soon become the second leading cause of cancer-related deaths in the USA. For patients with metastatic disease, the 2- and 5-year survival is < 10% and ̃3%, respectively. For the few patients with local disease, 5-year survival is ̃40%. Many other cancers have comparable differences between early- and late-stage disease. It is apparent a diagnostic assay for early-stage cancers would transform the field by minimizing the need for aggressive surgeries and other harsh interventions, and by its potential to increase survival. Identifying cancer-specific aberrations in blood-based “liquid” biopsies offers a prospect for a non-invasive cancer detection tool. In the bloodstream, there are extracellular vesicles (EVs) with cargoes including membrane and cytosolic proteins, as well as RNA and lipids derived from their parent cells. Methods: We used an alternating current electrokinetics (ACE) microarray to isolate EVs from the plasma of stage I and II bladder (N = 48), ovarian (N = 42), and pancreatic cancer patients (N = 44), and healthy volunteers (N = 110). EVs were analyzed using multiplex protein immunoassays for 54 cancer-related proteins. EV protein expression patterns were analyzed using stepwise logistic regression followed by a split between training and test sets (67%/33% respectively). This process enabled biomarker selection and generation of a classifier to discriminate between cancer and healthy donors. Results: The EV protein-based classifier had an overall area under curve (AUC) of 0.95 with a sensitivity of 71.2% (69.4% – 73.0%, at 95% confidence interval) at > 99% specificity. The classifier’s performance for the pancreatic cancer cohort was very strong, with overall sensitivity of 95.7% (94.6% – 96.9%, at 95% confidence interval) at > 99% specificity. Conclusions: EV-associated proteins may enable early cancer detection where surgical resection is most likely to improve outcomes. The classifier’s performance for the initial three cancers studied showed encouraging results. Future efforts will include examining additional cancer types and evaluating the classifier performance using samples from donors with related benign conditions with the aim of a pan-cancer early detection assay.