ABSTRACT Prostate cancer is the most commonly diagnosed cancer in men, with an estimated 268,490 new cases in the U.S. in 2022. At the time of a prostate cancer biopsy, pathologists use the tumor material to determine the grade and stage. Primary treatment decisions are based on the biopsy tissue information and the PSA (prostate specific antigen, blood test). About 80% of newly diagnosed cases are considered low-risk. Since in the majority of newly diagnosed, low-risk prostate cancer cases the disease is indolent (~70%) and surgery comes with significant adverse effects, a unique treatment option for many men with prostate cancer is Active Surveillance. There is an urgent need for biomarkers that could supplement standard clinical variables (i.e., Gleason score, PSA, tumor staging, number of positive biopsies, patient age) to predict tumors that will become aggressive cases that require treatment and those that can safely elect Active Surveillance. The DNA copy number signature of the tumor, called GEMCaP (Genomic Evaluators of Metastatic Cancer of the Prostate), was discovered by the Principal Investigator. GEMCaP was validated in the post-surgery setting to identify those cases poised for biochemical recurrence and metastasis. GEMCaP was recently evaluated in the Active Surveillance setting using archived surgical tissue, adjacent to where the biopsy was sampled, in men with low-risk prostate cancer as defined by clinical variables. GEMCaP independently predicted adverse pathology alongside a commercially available RNA risk predictor. When combined with clinical variables, GEMCaP resulted in improved predictive power of biochemical recurrence post-surgery compared to a commercial RNA assay. GEMCaP was also shown to identify cases that can safely be managed with Active Surveillance, which has not previously been achieved by commercially-available RNA competitor products. The goal of Biomarker Corporation’s NIH SBIR Phase I project is to work toward commercializing GEMCaP using biopsy tissue and a custom sequencing panel. Biopsy biospecimens for this study will be provided by the Canary Foundation’s well-annotated Active Surveillance biospecimen collection of biopsy tissue with associated clinical variables and outcome data. The study will use a commercial RNA biomarker assay as a comparator. The aims of this project are to 1) Determine if GEMCaP can identify aggressive CaP in a cohort of patients considered clinically low-risk based on biopsies and compare Biomarker Corp.’s proprietary algorithm in the Active Surveillance setting with the binary cut-off method, 2) Test GEMCaP in identifying low-risk cases who can safely stay on Active Surveillance, 3) Compare GEMCaP’s performance to a commercially available RNA predictor. In Phase II we will validate our findings in a larger cohort, using the calling method identified in Aim 1. Successful clinical validation as a Phase II and implementation of GEMCaP will improve prediction accuracy and thereby...