Semi-mechanistic efficacy model for PARP + ATR inhibitors—application to rucaparib and talazoparib in combination with gartisertib in breast cancer PDXs

IF 6.8 1区 医学 Q1 ONCOLOGY British Journal of Cancer Pub Date : 2025-01-28 DOI:10.1038/s41416-024-02935-w
Claire C. Villette, Nathalie Dupuy, Frances A. Brightman, Astrid Zimmermann, Floriane Lignet, Frank T. Zenke, Nadia Terranova, Jayaprakasam Bolleddula, Samer El Bawab, Christophe Chassagnole
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Abstract

Promising cancer treatments, such as DDR inhibitors, are often challenged by the heterogeneity of responses in clinical trials. The present work aimed to build a computational framework to address those challenges. A semi-mechanistic pharmacokinetic-pharmacodynamic model of tumour growth inhibition was developed to investigate the efficacy of PARP and ATR inhibitors as monotherapies, and in combination. Key features of the DNA damage response were incorporated into the model to allow the emergence of synthetic lethality, including redundant DNA repair pathways that may be impaired due to genetic mutations, and due to PARP and ATR inhibition. Model parameters were calibrated using preclinical in vivo data for PARP inhibitors rucaparib and talazoparib and the ATR inhibitor gartisertib. The model successfully captured the monotherapy efficacies of rucaparib and talazoparib, as well as the combination efficacy with gartisertib. The model was evaluated against multiple tumour xenografts with diverse genetic backgrounds and was able to capture the observed heterogeneity of response profiles. By enabling simulation of in vivo tumour growth inhibition with PARP and ATR inhibitors for specific tumour types, the model provides a rational approach to support the optimisation of dosing regimens to stratified populations.

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PARP + ATR抑制剂的半机制疗效模型——鲁卡帕尼和塔拉唑帕尼联合加替替治疗乳腺癌pdx的应用
背景:有前景的癌症治疗,如DDR抑制剂,在临床试验中经常受到反应异质性的挑战。目前的工作旨在建立一个计算框架来应对这些挑战。方法:建立肿瘤生长抑制的半机制药动学-药效学模型,观察PARP和ATR抑制剂单独治疗和联合治疗的疗效。DNA损伤反应的关键特征被纳入模型,以允许合成致死性的出现,包括可能由于基因突变和PARP和ATR抑制而受损的冗余DNA修复途径。使用PARP抑制剂rucaparib和talazoparib以及ATR抑制剂gartisertib的临床前体内数据校准模型参数。结果:模型成功捕获了鲁卡帕尼和塔拉唑帕尼单药治疗的疗效,以及与加替替联合治疗的疗效。该模型对具有不同遗传背景的多种肿瘤异种移植物进行了评估,并能够捕捉到观察到的反应概况的异质性。结论:通过模拟PARP和ATR抑制剂对特定肿瘤类型的体内肿瘤生长抑制,该模型提供了一种合理的方法来支持分层人群的给药方案优化。
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来源期刊
British Journal of Cancer
British Journal of Cancer 医学-肿瘤学
CiteScore
15.10
自引率
1.10%
发文量
383
审稿时长
6 months
期刊介绍: The British Journal of Cancer is one of the most-cited general cancer journals, publishing significant advances in translational and clinical cancer research.It also publishes high-quality reviews and thought-provoking comment on all aspects of cancer prevention,diagnosis and treatment.
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