# Prostate Needle Biopsies: Impact of Preanalytical Procurement and Processing Variables on the Detection of Gene Expression Signatures of Prostate Cancer Aggressiveness

> **NIH NIH U01** · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · 2023 · $344,109

## Abstract

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 ...

## Key facts

- **NIH application ID:** 10649631
- **Project number:** 5U01CA271400-02
- **Recipient organization:** UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
- **Principal Investigator:** SANDRA M GASTON
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $344,109
- **Award type:** 5
- **Project period:** 2022-06-17 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10649631

## Citation

> US National Institutes of Health, RePORTER application 10649631, Prostate Needle Biopsies: Impact of Preanalytical Procurement and Processing Variables on the Detection of Gene Expression Signatures of Prostate Cancer Aggressiveness (5U01CA271400-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10649631. Licensed CC0.

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