Currently, metastatic castration-resistant prostate cancer (CRPC) is lethal, killing ~30,000 U.S. men each year. While CRPC typically remains dependent on active androgen receptor (AR) signaling, continued anti- androgen treatment can select for AR signaling negative (AR-) prostate cancer that has extremely poor prognosis. Unfortunately, little is known about genetic drivers and activated pathways in AR- prostate cancer, limiting precision medicine strategies. The rapid clinical uptake of novel agents targeting AR signaling suggests an imminent increase in AR- prostate cancer incidence, intensifying the need to identify genetic drivers and therapeutic strategies for this subset of prostate cancer. Jus as importantly, combined targeting of AR and drivers of AR- prostate cancer may improve treatment of AR dependent (AR+) CRPC, through inhibition of feedback pathways activated by AR inhibition and preventing AR- CRPC development. In preliminary studies, we prioritize novel drivers of AR- prostate cancer (including MET and NRAS) through basic molecular subtyping of a unique collection of prostate cancer xenografts, coupled with comprehensive transcriptomic and genomic characterization and comparison to our integrative profiling data of human CRPC tissues. Through this strategy, using in vitro and in vivo models, we show that an activating mutation in MET drives AR- prostate cancer, and more generally, MET is activated exclusively in AR- CRPC or AR+ CRPC upon androgen signaling inhibition. Importantly, we demonstrate that small molecule inhibitors of both AR and MET are more efficacious in AR+ CRPC models compared to either inhibitor alone, supporting the utility of targeting compensatory pathways activated upon AR inhibition. The underlying hypothesis of this proposal is that drivers of AR- CRPC identified through this integrative approach, such as MET and NRAS, can be exploited as therapeutic targets in both AR- and AR+ prostate cancer. To address this hypothesis, we propose the following specific aims: 1) Identify novel potential drivers of AR- prostate cancer through next generation sequencing of patient derived AR- CRPC xenografts and tissue samples. 2) Qualify novel drivers of AR- prostate cancer identified in our preliminary data and Aim 1 through comprehensive in vitro studies in both AR+ and AR- models. 3) Develop novel treatment strategies for AR- and AR+ prostate cancer through in vivo mouse xenograft studies using both CRPC cell lines and patient derived xenografts. Successful completion of this integrative proposal will result in the identification of novel drivers and development of potentia therapeutic targets in AR- CRPC. Importantly, our preliminary data also demonstrates that these drivers can be targeted in AR+ CRPC upon AR inhibition. In summary, this proposal has both short and long term potential to dramatically impact precision medicine for the ~30,000 U.S. men dying each year of both AR+ and AR- CRPC.

Public Health Relevance

Prostate cancer that progresses despite anti-androgen receptor (AR) based therapies, termed castration resistant prostate cancer (CRPC), often remains dependent on AR signaling (AR+). Continued treatment of AR+ CRPC can lead to highly lethal AR independent (AR-) CRPC through poorly understood mechanisms. This proposal will identify novel drivers of AR- CRPC and develop treatment strategies targeting these drivers in both AR+ and AR- CRPC, and is directly relevant to the ~30,000 U.S. men dying each year of CRPC.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA183857-04
Application #
9210061
Study Section
Tumor Cell Biology Study Section (TCB)
Program Officer
Sathyamoorthy, Neeraja
Project Start
2014-04-03
Project End
2019-02-28
Budget Start
2017-03-01
Budget End
2018-02-28
Support Year
4
Fiscal Year
2017
Total Cost
$289,462
Indirect Cost
$102,712
Name
University of Michigan Ann Arbor
Department
Pathology
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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