Mechanistic data-informed multiscale quantitative systems pharmacology modeling framework enables the clinical translation and efficacy assessment of CAR-T therapy in solid tumors.

IF 10.6 1区 医学 Q1 IMMUNOLOGY
Siyuan Yang, Wenjie Wang, Qi Rao, Yiyang Xu, Sujie Zhang, Yuchen Qu, Qiuchuan Zhuang, Jie Mao, Laura Sun, Dong Geng, Da Xu, Chen Zhao
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引用次数: 0

Abstract

Background: Chimeric antigen receptor (CAR)-T cell therapy represents an innovative and potentially revolutionary modality in cancer treatment. Despite their great success in treating blood cancers, CAR-T therapies exhibit significantly lower effectiveness in treating solid tumors. Moreover, the preclinical-to-clinical translation of CAR-T therapies targeting solid tumors is still a challenging task because of their unique "live cell" nature and the substantial variability in patients' pathophysiology.

Methods: We have developed a multiscale quantitative systems pharmacology (QSP) model to facilitate the clinical translation of CAR-T therapies in solid tumors. Our mechanistic modeling framework integrates the essential biological features that impact CAR-T cell fate and antitumor cytotoxicity, from cell-level CAR-antigen interaction and activation, to in vivo CAR-T biodistribution, proliferation and phenotype transition, and finally to clinical-level patient tumor heterogeneity and response variability. This modeling framework has been calibrated and validated by multimodal experimental data including published preclinical and clinical data of various CAR-T products and original preclinical data of a novel claudin18.2-targeted CAR-T product LB1908.

Results: We demonstrated the general utility of this framework in facilitating clinical translation and characterizing the paired cellular kinetics-cytotoxicity response of different antigen-targeting solid tumor CAR-T cell therapies. As an example, we generated model-based virtual patients and prospectively simulated the response to claudin18.2-targeted CAR-T therapies under different dosing strategies, including step-fractionated dosing and convenient flat dose-based regimens, to inform future clinical trial implementation.

Conclusions: Our translational QSP platform offers an innovative pathway to integrate multiscale knowledge and inform clinical decision-making of novel solid tumor-targeting CAR-T therapies.

基于机械数据的多尺度定量系统药理学建模框架使CAR-T治疗在实体肿瘤中的临床转化和疗效评估成为可能。
背景:嵌合抗原受体(CAR)-T细胞治疗代表了一种创新的、潜在的革命性的癌症治疗方式。尽管CAR-T疗法在治疗血癌方面取得了巨大成功,但在治疗实体肿瘤方面却表现出明显较低的有效性。此外,针对实体肿瘤的CAR-T疗法的临床前到临床转化仍然是一项具有挑战性的任务,因为它们独特的“活细胞”性质和患者病理生理的巨大变异性。方法:我们建立了一个多尺度定量系统药理学(QSP)模型,以促进CAR-T疗法在实体瘤中的临床转化。我们的机制建模框架整合了影响CAR-T细胞命运和抗肿瘤细胞毒性的基本生物学特征,从细胞水平的car -抗原相互作用和激活,到体内CAR-T生物分布、增殖和表型转变,最后到临床水平的患者肿瘤异质性和反应变异性。该建模框架已通过多模态实验数据进行校准和验证,包括各种CAR-T产品的临床前和临床数据,以及新型claudin18.2靶向CAR-T产品LB1908的原始临床前数据。结果:我们证明了该框架在促进临床翻译和表征不同抗原靶向实体肿瘤CAR-T细胞疗法的配对细胞动力学-细胞毒性反应方面的一般效用。作为一个例子,我们生成了基于模型的虚拟患者,并前瞻性地模拟了不同剂量策略下对claudin18.2靶向CAR-T治疗的反应,包括步进分步给药和方便的平剂量方案,为未来的临床试验实施提供信息。结论:我们的翻译QSP平台提供了一种创新的途径来整合多尺度知识,并为新型实体肿瘤靶向CAR-T疗法的临床决策提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal for Immunotherapy of Cancer
Journal for Immunotherapy of Cancer Biochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
17.70
自引率
4.60%
发文量
522
审稿时长
18 weeks
期刊介绍: The Journal for ImmunoTherapy of Cancer (JITC) is a peer-reviewed publication that promotes scientific exchange and deepens knowledge in the constantly evolving fields of tumor immunology and cancer immunotherapy. With an open access format, JITC encourages widespread access to its findings. The journal covers a wide range of topics, spanning from basic science to translational and clinical research. Key areas of interest include tumor-host interactions, the intricate tumor microenvironment, animal models, the identification of predictive and prognostic immune biomarkers, groundbreaking pharmaceutical and cellular therapies, innovative vaccines, combination immune-based treatments, and the study of immune-related toxicity.
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