Modeling the HIV latent reservoir, latency reversal and immunotherapeutics for HIV cure

摘要 HIV治愈的一个主要障碍是在接受治疗的患者中持续存在的潜伏感染细胞的储备库 使用高效抗逆转录病毒治疗(ART)。这些潜伏感染细胞的激活可能会导致 在没有抗逆转录病毒药物治疗的情况下，艾滋病毒会反弹。在临床试验中，艾滋病毒呈现出截然不同的动态 在艺术停止之后。艾滋病毒在大多数人中迅速反弹，而在一小部分人中 对个人来说，艾滋病毒长期缓解或治疗后控制(PTC)是实现的。尽管 密集的研究，我们对病毒控制的决定因素缺乏清晰和连贯的理解 或艾滋病毒在抗逆转录病毒治疗后缓解的持续时间，这阻碍了有效治疗的发展 实现“功能性”治愈并最终达到绝育治愈的策略。 这笔赠款弥补了这一知识缺口。我们的中心假设是，PTC并不是单独驱动的 由单一因素造成的；相反，它是复杂的非线性相互作用产生的现象。 在免疫应答和潜伏库之间，包括复制能力强的 储油层和故障储油层。理解这种动态的相互作用将是 制定有效的干预措施，以获得良好的临床结果。我们将首先勾勒出 这些相互作用在通过整合最新的生物学来确定病毒控制中的作用 将发现转化为机械论的数学模型。我们将使用临床数据来验证该模型 从后处理控制器和非控制器，将估计的模型参数与 测量的生物学和免疫学标志物，以确定预测患者特征的 PTC。此外，我们将评估行动模式并量化下一代 潜伏期反转剂(LRA)AZD5582和一类有前途的双特异性抗体 免疫治疗学，双亲和重靶向分子。最后，我们将集成模型 这些制剂如何与潜在储藏者和免疫系统相互作用的模型一起工作 评估和预测LRAs和免疫疗法组合对 对储蓄者和临床结果的影响。 总之，我们的工作将为1)了解艾滋病毒控制和 ART术后的反弹动态，2)确定可能实现PTC的患者，3) 估计/预测治疗干预措施的影响，例如LRA和/或 免疫疗法，以及4)提出有效的干预措施，以实现“功能性”治愈 根据患者的特点选择合适的治疗方案。

SUMMARY A major barrier to HIV cure is the reservoir of latently infected cells that persists in patients treated with highly potent antiretroviral treatment (ART). Activation of these latently infected cells can lead to HIV rebound in the absence of ART. In clinical trials, HIV exhibits widely different dynamics after ART cessation. HIV rebounds rapidly in most individuals, whereas in a small fraction of individuals, prolonged HIV remission or post-treatment control (PTC) is achieved. Despite intensive research, we lack a clear and coherent understanding of the determinants of viral control or the duration of HIV remission after ART, which hinders the development of effective therapeutic strategies to achieve a ‘functional’ cure and ultimately a sterilizing cure. This grant addresses this gap in knowledge. Our central hypothesis is that PTC is not solely driven by a single factor; rather, it is a phenomenon emerging from complex nonlinear interactions between the immune response and the latent reservoir, including both the replication competent reservoir and the defective reservoir. Understanding this dynamical interaction will be key to develop effective interventions to achieve favorable clinical outcomes. We will first delineate the roles of these interactions in determining viral control through integration of recent biological findings into a mechanistic mathematical model. We will validate this model using clinical data from post-treatment controllers and non-controllers, correlate estimated model parameters with measured biological and immunological markers to identify patient characteristics that predict PTC. Further, we will estimate the mode of action and quantify the efficacy of a next-generation latency reversing agent (LRA), AZD5582, and a class of promising bispecific antibody-based immunotherapeutics, the Dual-Affinity Re-Targeting molecules. Finally, we will integrate models of how these agents work with a model of the interaction of the latent reservoir with the immune system to evaluate and predict the impact of combinations of LRAs and immunotherapeutics on the reservoir and on clinical outcomes. Altogether, our work will provide a theoretical foundation for 1) understanding HIV control and rebound dynamics after ART, 2) identifying patients who are likely to achieve PTC, 3) estimating/predicting the impact of therapeutic interventions such as LRAs and/or immunotherapeutics, and 4) suggesting effective interventions to achieve a ‘functional’ cure according to patient characteristics.