PD-1/PD-L1阻断剂的免疫检查点治疗建模揭示了其反应动力学的细微差异和组合的潜在协同作用
Immune checkpoint therapy modeling of PD-1/PD-L1 blockades reveals subtle difference in their response dynamics and potential synergy in combination
摘要：
免疫检查点疗法是最有前途的免疫治疗方法之一，可能能够对各种癌症类型产生持久的治疗反应。尽管在过去十年中取得了很大进展，但仍然存在关键的开放问题，特别是关于量化和预测治疗效果以及结合不同免疫检查点阻断的潜在最佳方案。为了阐明这个问题，我们在这里开发了癌症免疫治疗的临床相关的动态系统模型，重点是免疫检查点PD-1/PD-L1阻断。我们的模型允许在没有治疗的情况下获得适应性免疫抗性，而免疫检查点阻断可以逆转这种抗性并增强效应细胞的抗肿瘤活性。我们的数值分析预测，对于广泛的模型参数，抗PD-1药物通常不如抗PD-L1药物有效。我们还观察到，抗PD-1和抗PD-L1阻断剂的组合治疗导致期望的协同效应。我们的建模框架为未来对免疫检查点治疗方案的组合疗法进行数据驱动分析以及对逐个患者的优化治疗进行彻底调查奠定了基础。
英文摘要：
Immune checkpoint therapy is one of the most promising immunotherapeutic methods that are likely able to give rise to durable treatment response for various cancer types. Despite much progress in the past decade, there are still critical open questions with particular regards to quantifying and predicting the efficacy of treatment and potential optimal regimens for combining different immune-checkpoint blockades. To shed light on this issue, here we develop clinically-relevant, dynamical systems models of cancer immunotherapy with a focus on the immune checkpoint PD-1/PD-L1 blockades. Our model allows the acquisition of adaptive immune resistance in the absence of treatment, whereas immune checkpoint blockades can reverse such resistance and boost anti-tumor activities of effector cells. Our numerical analysis predicts that anti-PD-1 agents are commonly less effective than anti-PD-L1 agents for a wide range of model parameters. We also observe that combination treatment of anti-PD-1 and anti-PD-L1 blockades leads to a desirable synergistic effect. Our modeling framework lays the ground for future data-driven analysis on combination therapeutics of immune-checkpoint treatment regimes and thorough investigation of optimized treatment on a patient-by-patient basis.
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