Obinata Daisuke, Lawrence Mitchell G, Takayama Kenichi, Choo Nicholas, Risbridger Gail P, Takahashi Satoru, Inoue Satoshi
Department of Urology, Nihon University School of Medicine, Tokyo, Japan.
Monash Biomedicine Discovery Institute Cancer Program, Prostate Cancer Research Group, Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, Australia.
Front Oncol. 2020 Oct 8;10:581515. doi: 10.3389/fonc.2020.581515. eCollection 2020.
The androgen receptor (AR) is the main therapeutic target in advanced prostate cancer, because it regulates the growth and progression of prostate cancer cells. Patients may undergo multiple lines of AR-directed treatments, including androgen-deprivation therapy, AR signaling inhibitors (abiraterone acetate, enzalutamide, apalutamide, or darolutamide), or combinations of these therapies. Yet, tumors inevitably develop resistance to the successive lines of treatment. The diverse mechanisms of resistance include reactivation of the AR and dysregulation of AR cofactors and collaborative transcription factors (TFs). Further elucidating the nexus between the AR and collaborative TFs may reveal new strategies targeting the AR directly or indirectly, such as targeting BET proteins or OCT1. However, appropriate preclinical models will be required to test the efficacy of these approaches. Fortunately, an increasing variety of patient-derived models, such as xenografts and organoids, are being developed for discovery-based research and preclinical drug screening. Here we review the mechanisms of drug resistance in the AR signaling pathway, the intersection with collaborative TFs, and the use of patient-derived models for novel drug discovery.
雄激素受体(AR)是晚期前列腺癌的主要治疗靶点,因为它调节前列腺癌细胞的生长和进展。患者可能会接受多线AR导向治疗,包括雄激素剥夺疗法、AR信号抑制剂(醋酸阿比特龙、恩杂鲁胺、阿帕鲁胺或达罗他胺),或这些疗法的联合使用。然而,肿瘤不可避免地会对后续的治疗产生耐药性。耐药的多种机制包括AR的重新激活以及AR辅因子和协同转录因子(TFs)的失调。进一步阐明AR与协同TFs之间的关系可能会揭示直接或间接靶向AR的新策略,例如靶向BET蛋白或OCT1。然而,需要合适的临床前模型来测试这些方法的疗效。幸运的是,越来越多的患者来源模型,如异种移植模型和类器官,正在被开发用于基于发现的研究和临床前药物筛选。在此,我们综述了AR信号通路中的耐药机制、与协同TFs的交叉点,以及患者来源模型在新型药物发现中的应用。