Most prostate cancer deaths are due to failed treatment response or to metastasis, particularly to bone. We have been studying the mechanisms responsible for treatment failure using genetically-engineered mouse models (GEMMs) that recapitulate key features of advanced prostate cancer, including castration-resistant prostate cancer (CRPC) and aggressive-variant CRPC with neuroendocrine differentiation (CRPC-NE), and that develop highly penetrant metastatic prostate cancer including to bone, which is the primary site of metastasis in humans. Using novel cross-species computational approaches, we have shown that the mechanisms underlying disease progression in these GEMMs are conserved with human prostate cancer, while drug response in GEMMs can be predictive of drug response in humans. Among our major findings, we have shown that GEMMs based on combined loss-of-function of Pten and p53 (NPp53), which are frequently co-mutated in human CRPC, model key phenotypic and molecular features of treatment-induced aggressive variant CRPC. Not only do these NPp53 mice fail to respond to treatment with anti-androgens, treatment actually accelerates disease progression, which we have called exceptional non-responders. Furthermore, we have shown that the treatment-induced neuroendocrine phenotype (CRPC-NE) of these exceptional non-responders is related to lineage plasticity. Thus, our proposed studies will test the hypotheses that: (i) co-clinical analyses of GEMMs and human prostate cancer can elucidate biological and molecular mechanisms of drug response, and (ii) lineage plasticity is an important novel mechanism of drug resistance.
In Aim 1 we will perform co-clinical investigations capitalizing on our GEMMs that model key aspects of advanced prostate cancer, and complemented with analyses of human prostate cancer organoid models. We will evaluate the efficacy of clinically-relevant drugs and drug combinations, focusing on those that: (a) counteract cellular plasticity associated with treatment resistance in CRPC; and (b) target bone metastasis.
In Aim 2, we will investigate molecular mechanisms of drug response leveraging our genome-wide regulatory networks that enable cross-species integration between data from GEMMs and human prostate cancer. We will focus on identifying ?treatment response regulators? that inform on response to: (i) lineage plasticity and/or (ii) bone metastasis.
In Aim 3 we will identify novel drivers of advanced prostate cancer using a forward genetic screening approach. Toward this end, we have undertaken a genetic screen utilizing the Sleeping Beauty (SB) murine transposon-based system, and have shown that mice harboring the activated transposon display accelerated lethal prostate cancer phenotypes. Taken together, the successful implementation of these Aims will identify tumor contexts that are responsive to drug treatment and molecular mechanisms of drug response, and will identify new targets for intervention.

Public Health Relevance

Despite recent advances in new treatments, most men with advanced prostate cancer succumb to the disease. The major causes of prostate cancer deaths are due to failed response to treatment and metastasis, particularly to bone. Our proposal takes an innovative approach to address these clinical challenges by studying treatment response in the whole organism using genetically-engineered mouse models (GEMMs) with validation to human prostate cancer, in order to optimize drugs/drug combinations for: (1) treatment-induced aggressive castration-resistant prostate cancer; and (2) lethal bone metastasis.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA173481-09
Application #
10091974
Study Section
Basic Mechanisms of Cancer Therapeutics Study Section (BMCT)
Program Officer
Forry, Suzanne L
Project Start
2013-08-06
Project End
2023-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
9
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Pharmacology
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Arriaga, Juan M; Abate-Shen, Cory (2018) Genetically Engineered Mouse Models of Prostate Cancer in the Postgenomic Era. Cold Spring Harb Perspect Med :
Abate-Shen, Cory (2018) Prostate Cancer Metastasis - Fueled by Fat? N Engl J Med 378:1643-1645
Le Magnen, Clémentine; Shen, Michael M; Abate-Shen, Cory (2018) Lineage Plasticity in Cancer Progression and Treatment. Annu Rev Cancer Biol 2:271-289
Dutta, Aditya; Panja, Sukanya; Virk, Renu K et al. (2017) Co-clinical Analysis of a Genetically Engineered Mouse Model and Human Prostate Cancer Reveals Significance of NKX3.1 Expression for Response to 5?-reductase Inhibition. Eur Urol 72:499-506
Zou, Min; Toivanen, Roxanne; Mitrofanova, Antonina et al. (2017) Transdifferentiation as a Mechanism of Treatment Resistance in a Mouse Model of Castration-Resistant Prostate Cancer. Cancer Discov 7:736-749
Dutta, Aditya; Le Magnen, Clémentine; Mitrofanova, Antonina et al. (2016) Identification of an NKX3.1-G9a-UTY transcriptional regulatory network that controls prostate differentiation. Science 352:1576-80
Le Magnen, Clémentine; Dutta, Aditya; Abate-Shen, Cory (2016) Optimizing mouse models for precision cancer prevention. Nat Rev Cancer 16:187-96
Santanam, Urmila; Banach-Petrosky, Whitney; Abate-Shen, Cory et al. (2016) Atg7 cooperates with Pten loss to drive prostate cancer tumor growth. Genes Dev 30:399-407
Goodwin, Jonathan F; Kothari, Vishal; Drake, Justin M et al. (2015) DNA-PKcs-Mediated Transcriptional Regulation Drives Prostate Cancer Progression and Metastasis. Cancer Cell 28:97-113
Mitrofanova, Antonina; Aytes, Alvaro; Zou, Min et al. (2015) Predicting Drug Response in Human Prostate Cancer from Preclinical Analysis of In Vivo Mouse Models. Cell Rep 12:2060-71

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