School of Mathematics and Physics, University of Portsmouth, Hampshire, United Kingdom.
Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
Cancer Res. 2020 Apr 1;80(7):1564-1577. doi: 10.1158/0008-5472.CAN-18-3637. Epub 2020 Feb 6.
Enzalutamide (MDV3100) is a potent second-generation androgen receptor antagonist approved for the treatment of castration-resistant prostate cancer (CRPC) in chemotherapy-naïve as well as in patients previously exposed to chemotherapy. However, resistance to enzalutamide and enzalutamide withdrawal syndrome have been reported. Thus, reliable and integrated preclinical models are required to elucidate the mechanisms of resistance and to assess therapeutic settings that may delay or prevent the onset of resistance. In this study, the prostate cancer multistage murine model TRAMP and TRAMP-derived cells have been used to extensively characterize and the response and resistance to enzalutamide. The therapeutic profile as well as the resistance onset were characterized and a multiscale stochastic mathematical model was proposed to link the and evolution of prostate cancer. The model showed that all therapeutic strategies that use enzalutamide result in the onset of resistance. The model also showed that combination therapies can delay the onset of resistance to enzalutamide, and in the best scenario, can eliminate the disease. These results set the basis for the exploitation of this "TRAMP-based platform" to test novel therapeutic approaches and build further mathematical models of combination therapies to treat prostate cancer and CRPC. Merging mathematical modeling with experimental data, this study presents the "TRAMP-based platform" as a novel experimental tool to study the and evolution of prostate cancer resistance to enzalutamide.
恩扎卢胺（MDV3100）是一种强效的第二代雄激素受体拮抗剂，被批准用于治疗化疗初治和化疗预处理的去势抵抗性前列腺癌（CRPC）。然而，已经报道了对恩扎卢胺的耐药性和恩扎卢胺撤药综合征。因此，需要可靠和综合的临床前模型来阐明耐药机制，并评估可能延迟或预防耐药发生的治疗方案。在这项研究中，使用前列腺癌多阶段小鼠模型 TRAMP 和源自 TRAMP 的细胞来广泛研究和评估对恩扎卢胺的反应和耐药性。对治疗谱和耐药性的发生进行了特征描述，并提出了一个多尺度随机数学模型来连接前列腺癌的和进化。该模型表明，所有使用恩扎卢胺的治疗策略都会导致耐药性的发生。该模型还表明，联合治疗可以延迟恩扎卢胺耐药性的发生，在最佳情况下，可以消除疾病。这些结果为利用这种“基于 TRAMP 的平台”来测试新的治疗方法并建立进一步的联合治疗数学模型来治疗前列腺癌和 CRPC 奠定了基础。通过将数学建模与实验数据相结合，本研究提出了“基于 TRAMP 的平台”作为一种新的实验工具，用于研究前列腺癌对恩扎卢胺耐药性的和进化。
