Abstract PR12: Detection of EV-based signatures in prostate cancer using microflow cytometry and machine learning
Authors: John D. Lewis, Robert J. Paproski, Desmond B. Pink, Catalina Vasquez, Eric Hyndman, Adrian Fairey
Journal: Clinical Cancer Research (2020)

Abstract Microflow cytometry (µFCM) has recently emerged as a viable technology to enumerate and quantify individual EVs from complex biologic fluids. This method is a promising alternative to biopsy collection because it is highly sensitive and allows for longitudinal assessment of patients. EVs are highly abundant and analysis by µFCM allows for sophisticated multiparametric analysis of organ-specific, disease-specific, and outcome-specific proteins, genes, or metabolites. Detection of EVs with µFCM requires very little sample yet provides exceptional specificity and sensitivity for low abundance events. By combining µFCM analysis of EVs with advanced machine learning approaches, we have developed a platform technology called ClarityDX to generate EV fingerprints that significantly improve the diagnosis of diseases such as prostate cancer using a few drops of blood. Here I will discuss the development and clinical validation of new blood tests for prostate cancer that utilize the ClarityDX platform. Prostate cancer is the most commonly diagnosed cancer and the third leading cause of cancer deaths in men. Screening has enabled the early detection of many latent prostate cancers, and it is estimated that up to 50% of new prostate cancer diagnoses detect a tumor that was unlikely to surface clinically in the absence of PSA screening. In the majority of cases, the treatment of indolent cancer causes a patient more harm than good. Consequently, there is an urgent need for a noninvasive test to detect clinically significant prostate cancer, or perhaps even more importantly, to detect metastatic disease. ClarityDX Prostate is a µFCM-based test to predict clinically significant prostate cancer prior to a prostate biopsy. A prospective clinical validation of ClarityDX Prostate was performed in a cohort of 377 Albertan men. The overall average AUC for ClarityDX Prostate in this population was 0.83, which was significantly higher than PSA alone. While PSA alone provided only 17% specificity for aggressive prostate cancer at a 95% sensitivity, ClarityDX Prostate was 56% specific for aggressive prostate cancer. We are now conducting a pivotal clinical validation study, in which up to 2,800 men will be enrolled to assess the performance of ClarityDX Prostate in a “real-world” clinical environment. Overall, we have established a robust µFCM EV platform for the development of novel and clinically viable diagnostic tests. Incorporating ClarityDX Prostate into routine prostate cancer screening could reduce the number of unnecessary biopsies by up to 40%. This abstract is also being presented as Poster B57. Citation Format: John D. Lewis, Robert J. Paproski, Desmond B. Pink, Catalina Vasquez, Eric Hyndman, Adrian Fairey, APCaRI. Detection of EV-based signatures in prostate cancer using microflow cytometry and machine learning [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR12.