# Combating Highly Aggressive Prostate Cancer: Development of Novel Patient Derived Xenograft Models and Application in Preclinical Studies of Novel Selective Androgen Receptor Degraders

> **NIH NIH U54** · BAYLOR COLLEGE OF MEDICINE · 2021 · $120,000

## Abstract

Project Summary
Disparities in cancer incidence, prevalence, mortality and survivorship burden racial and ethnic minority
populations in the US. In addition, these minority populations remain underrepresented in therapeutic clinical
trials. Our Minority Patient-Derived Xenograft (PDX) Development and Trial Center (M-PDTC) provides a unique
opportunity to help address these racial/ethnic disparities. This Center is built on the scientific premise that,
in addition to important socioeconomic factors, health disparities that burden racial/ethnic minorities in
the US are linked to poorly understood genetic and other intrinsic factors. We propose to leverage the
high numbers of minority cancer patients at Baylor College of Medicine (BCM) in order to generate and
utilize innovative PDX models of diverse racial/ethnic minority origin, which will assist the entire scientific
community delineate the molecular underpinnings of cancer of racial/ethnic minority origin. Houston is the most
diverse large US city, with ~20% of its residents being African American (AA) and ~40% Hispanic. BCM faculty
are responsible for clinical care at two major teaching hospitals that serve large minority populations: Ben Taub
Hospital (BTH), a public hospital (91% of patients are minorities), and the Michael E. DeBakey VA Medical Center
(MEDVAMC), one of the largest VA Medical Centers in the US, which serves over 100,000 veterans in Southeast
Texas (~30% are AA). Thus, there is a very large population of minority cancer patients available for potential
tissue donations. BCM has a long track record of successfully enrolling minority patients in clinical trials.
In addition to our large AA patient population at BCM, 59% of patients at BTH are of Hispanic ethnicity. We have
assembled a multidisciplinary and multi-institutional collaborative team, bringing together experts in PDX model
generation, molecular biology and signaling pathways, animal drug treatment studies, pathology and clinical
management of prostate and breast cancer from BCM and MD Anderson Cancer Center (MDACC). We are
ideally positioned to leverage the technical resources of our institutions and our high numbers of racial and ethnic
minority cancer patients at BCM, in order to support the broader goals of the M-PDTC RFA, in particular to
facilitate biospecimen donations from these populations and increase the racial and ethnic diversity of the
PDXNet repository in a wide spectrum of cancers, as well as to support the Specific Aims of our two research
projects in prostate and breast cancer. Few, if any, cancer centers have this combination of an outstanding
research base, large numbers of African American, Hispanic and Asian cancer patients, and BCM’s robust track
record of successfully enrolling minority patients from our catchment area (Houston) into clinical trials. Moreover,
our two research projects will utilize whole exome sequencing (WES), global RNA-sequencing (RNA-seq),
quantitative proteomic (qKiP) and m...

## Key facts

- **NIH application ID:** 10435884
- **Project number:** 3U54CA233223-01S2
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Nicholas Mitsiades
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $120,000
- **Award type:** 3
- **Project period:** 2021-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10435884

## Citation

> US National Institutes of Health, RePORTER application 10435884, Combating Highly Aggressive Prostate Cancer: Development of Novel Patient Derived Xenograft Models and Application in Preclinical Studies of Novel Selective Androgen Receptor Degraders (3U54CA233223-01S2). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10435884. Licensed CC0.

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