# Biomarker Approaches to Individualizing Systemic Therapy for High Risk Prostate Cancer

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $651,833

## Abstract

Each year, over 1 million new patients are diagnosed with prostate cancer (PCa) worldwide, and over 300,000
men die of this disease. High risk PCa accounts for the vast majority of PCa deaths. The standard of care for
high risk PCa was set by RTOG 92-02, a phase III trial that demonstrated a reduction in disease recurrence
and an improvement in PCa-specific survival with radiation therapy (RT) plus long-term androgen deprivation
therapy (LTADT, 28 months), compared to RT with short-term ADT (STADT, 4 months). Despite this advance,
both overtreatment and undertreatment are acute clinical problems in this patient population. In this trial, 50%
of patients were ultimately not cured with RT + LTADT. If this subset of patients had been identified with
prognostic biomarkers, they could have received therapy more suited to their aggressive disease, including
chemotherapy and novel targeted agents. On the other hand, 30% of men were cured with RT + STADT alone,
and could have avoided 24 unnecessary months of exposure to ADT and its toxic side effects. Surprisingly,
PCa is one of the few common cancers in which molecular biomarkers are not routinely used to guide
therapeutic decisions. To address these unmet needs, we propose to develop and validate clinically useful and
cost-effective prognostic and predictive biomarkers for high-risk PCa patients treated with RT, by applying a
clinical-grade high-density oligonucleotide array on a unique set of tumor samples from three landmark phase
III trials (RTOG 92-02, 99-02, and 94-13). Our research team, combining expertise in PCa, prognostic and
predictive biomarker signature identification and validation, bioinformatics, and decision analysis, will: (1)
Optimize a prognostic classifier that integrates genomic and clinicopathologic data for PCa patients treated
with RT, allowing selection of men with high-risk PCa who would benefit from treatment intensification in future
trials, (2) Derive and validate an integrated genomic-clinicopathologic predictor of response to LTADT vs.
STADT, a therapeutic duration signature that would allow differentiation of patients who should require LTADT
vs. those who are likely to be cured with STADT alone, and (3) Determine the health benefits and cost-
effectiveness of using genomic-clinicopathologic classifiers to personalize therapy in men with high-risk PCa.
Successful completion of these aims would result in cost-effective prognostic and predictive clinical-grade
biomarkers developed on a CLIA-compliant platform that would have an immediate impact on the clinical
management of men with high-risk PCa, transforming current treatment paradigms for these patients.

## Key facts

- **NIH application ID:** 9972488
- **Project number:** 1R01CA240582-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Felix Yi-Chung Feng
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $651,833
- **Award type:** 1
- **Project period:** 2020-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9972488

## Citation

> US National Institutes of Health, RePORTER application 9972488, Biomarker Approaches to Individualizing Systemic Therapy for High Risk Prostate Cancer (1R01CA240582-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9972488. Licensed CC0.

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