PROJECT SUMMARY Prostate cancer risk assessment governs decisions across a spectrum of local-regional disease from whether to biopsy to whether to intensify treatment using multimodality therapy. RNA transcript-based signatures have rapidly been incorporated into such determinations, along with Gleason Score (now termed Grade Group or GG). The significance of the proposed work is that there is a pressing need for optimization and standardization of preanalytic conditions for determination of highest GG and expression of Prostate Transcripts of Aggressiveness (PTAs), especially when working with biopsy biospecimens. These preanalytic variables extend from tissue procurement to preservation of transcript marker integrity such that appropriate risk is assigned for each patient. Obtaining prostate biopsies with multiparametric (mp) MRI-guidance has rapidly gained acceptance but there is little information about how prostate mpMRI contributes to the preanalytic variables that must be recognized and managed in clinical trials and clinical practice. There are considerable variances in the location and number of prostate biopsies collected and in the handling of the tissue from fixation to embedding to processing for testing of PTAs. As transcriptomic tests become more incorporated into clinical trials and practice, the tolerance of an assay for routinely encountered preanalytic variables must be considered in the formalization of standard operating procedures (SOPs). We will evaluate mpMRI targeted prostate biopsy specimens obtained from patients enrolled in five existing clinical trials in which the MR images are interpreted using both the standard-of- care reporting system for prostate (PIRADSv2.1) and a more advanced, automated, and portable quantitative mpMRI pixel by pixel-based scoring system termed the “Habitat Risk Score” (HRS). While PIRADS provides a critically important framework for prostate mpMRI image acquisition and interpretation, it is limited by reader subjectivity and variability in defining biopsy regions. In this project the impact of refined prostate biopsy procurement is paired with delineation of tissue processing variables for the classification of the most aggressive prostate cancer attributes defined by GG and PTAs. The Decipher Genomic Classifier (GC) score is representative of PTAs incorporated into signatures and is routinely used in clinical practice, is included in current NCCN recommendations, and is part of a combined GG/GC risk model (Spratt model). Our proof-of-principal studies on the impact of preanalytic variables examine highest GG and GC score, as well as effects on >400 PTAs. We hypothesize that mpMRI HRS directed tissue procurement will result in tissue more representative of prostate cancer risk, as determined by combined GG/GC score, as compared to tissue procurement directed by mpMRI PIRADS suspicion scores (Aim 1), that GG/Decipher GC risk will be adequately defined by 2 cores, as compared to 4 (Aim 2) and ...