# Improving Prostate Cancer Outcome Prediction Through Noninvasive exRNA Assessment

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $597,893

## Abstract

PROJECT SUMMARY / ABSTRACT:
Prostate cancer screening efforts and early detection of high-risk disease have driven a substantial drop in
mortality from the disease, but at the cost of much over-diagnosis and over-treatment of low-risk disease.
Indeed, some now believe that the morbidity associated with treatment cause more suffering than the disease
itself, leading to calls for the cessation of screening efforts. A better approach is to risk-stratify men with
prostate cancer patients with respect to likelihood of progression and, thereby, to personalize care
appropriately. This group has been a leader in developing improved clinicopathological stratification tools to
help physician and patients predict outcomes and, therefore, make better informed decisions regarding
treatment. Further we have been leaders in promoting active surveillance as a viable option to immediate
intervention. Through this experience, the need for additional biomarkers to improve risk stratification has
becoming increasingly clear. The long term goal is to identify the large number but relatively small proportion of
patients with localized disease who will benefit from intervention. Recently, we have validated a tissue RNA-
based molecular signature that can significantly add to current clinic-pathological parameters in predicting risk
of recurrence. While promising, a more essential need is to identify signatures that can stratify patients prior to
intervention as well as follow risk among patient who choose active surveillance. Furthermore, reducing the
use prostate biopsy, with its potential side effects, sampling error, and associated high costs would be a major
advance for the field. With these issues in mind, we hypothesize that plasma miRNAs could play a major role
in improving risk stratification among men with localized prostate cancer. Other recent work of ours has
identified a miRNA signature within pre-surgical plasma specimens that improved prediction of post-surgical
pathological upgrading over a combination of standard pre-surgical clinical parameters. Here we propose to
use recent advances in technologies to expand on these results by performing the following specific aims.
First, we aim to validate and expand the plasma miRNA signature associated with pathological upgrading by
using newer technology, evaluating a larger population across institutions, and measuring both upgraded and
upstaged tumors. Second, we aim to re-validate the signature and to compare tissue, serum, and urine
miRNA signatures that predict recurrence among patients who choose intervention. Both aims will be
leveraged by performing head-to-head comparisons with current commercially developed tissue/biopsy mRNA
signatures already being tested by our group. Third, we will evaluate sequential serum collections on a multi-
institutional cohort of men on active surveillance to evaluate whether the miRNA signature will precede other
evidence of progression. Successful completion of this prop...

## Key facts

- **NIH application ID:** 9995379
- **Project number:** 5R01CA198145-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Matthew R Cooperberg
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $597,893
- **Award type:** 5
- **Project period:** 2016-08-10 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9995379

## Citation

> US National Institutes of Health, RePORTER application 9995379, Improving Prostate Cancer Outcome Prediction Through Noninvasive exRNA Assessment (5R01CA198145-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9995379. Licensed CC0.

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