Division of Pharmacotherapy and Experimental Therapeutics, School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, United States.
Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, United States.
Elife. 2023 Jul 25;12:e83659. doi: 10.7554/eLife.83659.
Effector T cells need to form immunological synapses (IS) with recognized target cells to elicit cytolytic effects. Facilitating IS formation is the principal pharmacological action of most T cell-based cancer immunotherapies. However, the dynamics of IS formation at the cell population level, the primary driver of the pharmacodynamics of many cancer immunotherapies, remains poorly defined. Using classic immunotherapy CD3/CD19 bispecific T cell engager (BiTE) as our model system, we integrate experimental and theoretical approaches to investigate the population dynamics of IS formation and their relevance to clinical pharmacodynamics and treatment resistance. Our models produce experimentally consistent predictions when defining IS formation as a series of spatiotemporally coordinated events driven by molecular and cellular interactions. The models predict tumor-killing pharmacodynamics in patients and reveal trajectories of tumor evolution across anatomical sites under BiTE immunotherapy. Our models highlight the bone marrow as a potential sanctuary site permitting tumor evolution and antigen escape. The models also suggest that optimal dosing regimens are a function of tumor growth, CD19 expression, and patient T cell abundance, which confer adequate tumor control with reduced disease evolution. This work has implications for developing more effective T cell-based cancer immunotherapies.
效应 T 细胞需要与被识别的靶细胞形成免疫突触(IS),以引发细胞毒性效应。促进 IS 的形成是大多数基于 T 细胞的癌症免疫疗法的主要药理作用。然而,在细胞群体水平上 IS 形成的动力学,即许多癌症免疫疗法药效动力学的主要驱动因素,仍然定义不明确。我们使用经典的免疫治疗 CD3/CD19 双特异性 T 细胞衔接器(BiTE)作为我们的模型系统,整合实验和理论方法来研究 IS 形成的群体动力学及其与临床药效动力学和治疗抵抗的相关性。当将 IS 的形成定义为一系列受分子和细胞相互作用驱动的时空协调事件时,我们的模型对实验结果进行了一致的预测。这些模型预测了患者的肿瘤杀伤药效动力学,并揭示了 BiTE 免疫治疗下肿瘤在解剖部位的演变轨迹。我们的模型强调了骨髓作为潜在的避难所,允许肿瘤的进化和抗原逃逸。这些模型还表明,最佳的给药方案是肿瘤生长、CD19 表达和患者 T 细胞丰度的函数,这可以在减少疾病演变的情况下提供足够的肿瘤控制。这项工作对于开发更有效的基于 T 细胞的癌症免疫疗法具有重要意义。