Oncotarget

Research Papers:

BAY 1024767 blocks androgen receptor mutants found in castration-resistant prostate cancer patients

Tatsuo Sugawara, Pascale Lejeune, Silke Köhr, Roland Neuhaus, Hortensia Faus, Kathy A. Gelato, Matthias Busemann, Arwed Cleve, Ulrich Lücking, Franz von Nussbaum, Michael Brands, Dominik Mumberg, Klaus Jung, Carsten Stephan and Bernard Haendler _

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Oncotarget. 2016; 7:6015-6028. https://doi.org/10.18632/oncotarget.6864

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Abstract

Tatsuo Sugawara1, Pascale Lejeune1, Silke Köhr1, Roland Neuhaus1, Hortensia Faus1, Kathy A. Gelato1, Matthias Busemann1, Arwed Cleve1, Ulrich Lücking1, Franz von Nussbaum1, Michael Brands1, Dominik Mumberg1, Klaus Jung2,3, Carsten Stephan2,3 and Bernard Haendler1

1 Global Drug Discovery, Bayer Pharma AG, Berlin, Germany

2 Berlin Institute of Urologic Research, Berlin, Germany

3 Department of Urology, Charité University Hospital, Berlin, Germany

Correspondence to:

Bernard Haendler, email:

Keywords: prostate cancer, androgen receptor, anti-androgen resistance, mutant

Received: October 22, 2015 Accepted: December 24, 2015 Published: January 09, 2016

Abstract

Androgen receptor (AR) mutations arise in patients developing resistance to hormone deprivation therapies. Here we describe BAY 1024767, a thiohydantoin derivative with strong antagonistic activity against nine AR variants with mutations located in the AR ligand-binding domain (LBD), and against wild-type AR. Antagonism was maintained, though reduced, at increased androgen levels. Anti-tumor efficacy was evidenced in vivo in the KuCaP-1 prostate cancer model which bears the W741C bicalutamide resistance mutation and in the syngeneic prostate cancer rat model Dunning R3327-G. The prevalence of six selected AR mutations was determined in plasma DNA originating from 100 resistant patients and found to be at least 12%. Altogether the results show BAY 1024767 to be a strong antagonist for several AR mutants linked to therapy resistance, which opens the door for next-generation compounds that can benefit patients based on their mutation profile.


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