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

为 HIV 治愈建立 HIV 潜伏库、潜伏期逆转和免疫疗法的模型

• 批准号: 10206031
• 负责人: Ruian Ke
• 金额: $ 58.95万
• 依托单位: TRIAD NATIONAL SECURITY, LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10206031
• 关键词: Address; Affinity; Aftercare; Agonist; Antibodies; Biological; Biological Markers; Bispecific Antibodies; CD8-Positive T-Lymphocytes; CD8B1 gene; Cells; Characteristics; Clinical; Clinical Data; Clinical Trials; Combined Modality Therapy; Complex; Coupled; Data; Data Set; Development; Disease remission; Effectiveness; Effector Cell; Exhibits; Favorable Clinical Outcome; Foundations; Future; Grant; HIV; HIV-1; Immune; Immune response; Immune system; Immunologic Markers; Immunotherapeutic agent; In Vitro; Individual; Integration Host Factors; Interruption; Intervention; Knowledge; Lead; Light; Macaca; Macaca mulatta; Measurement; Measures; Medical; Modeling; Outcome; Patients; Public Health; Research; Response Latencies; Role; System; TLR7 gene; Testing; Therapeutic; Therapeutic Intervention; Treatment outcome; Viral; Viral Load result; Withholding Treatment; Work; acute infection; antiretroviral therapy; base; design; detection limit; effective intervention; effective therapy; experimental study; in vivo; latent HIV reservoir; mathematical model; neutralizing antibody; next generation; outcome prediction; pandemic disease; patient population; response; therapeutic development; therapeutically effective; tool; treatment strategy; viral rebound

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.

概括 艾滋病毒治疗的主要障碍是持续在接受治疗的患者中的潜在感染细胞的依据 具有高潜在的抗逆转录病毒治疗（ART）。这些潜在感染的细胞的激活可以导致 在没有艺术的情况下反弹。在临床试验中，HIV表现出广泛不同的动力学 在戒酒之后。大多数人的艾滋病毒迅速反弹，而在一小部分 实现了长时间的HIV缓解或治疗后控制（PTC）。尽管 密集研究，我们对病毒控制的决定者缺乏清晰而连贯的理解 或ART后HIV缓解的持续时间，这阻碍了有效治疗的发展 实现“功能性”治疗并最终进行消毒的策略。 该赠款在知识上解决了这一差距。我们的中心假设是PTC不仅是驱动的 一个因素；相反，这是复杂非线性相互作用的一种现象 在免疫反应和潜在储层之间，包括胜任的复制 水库和缺陷的水库。了解这种动态互动将是 制定有效的干预措施以实现有利的临床结果。我们将首先描述 这些相互作用在确定病毒控制中的作用，通过近期生物学的整合 发现成一个机械数学模型。我们将使用临床数据验证该模型 从后处理控制器和非控制器中，将估计的模型参数与 测量的生物学和免疫学标记物，以确定预测的患者特征 PTC。此外，我们将估计行动方式并量化下一代的效率 潜伏期逆转剂（LRA），AZD5582和一类基于双特异性抗体的承诺 免疫治疗剂，双亲和力重新定位分子。最后，我们将整合模型 这些代理如何与潜在储层与免疫的相互作用的模型一起工作 评估和预测LRA和免疫疗法组合对的系统 水库和临床结果。 总之，我们的工作将为1）理解艾滋病毒控制和 艺术后的反弹动态，2）识别可能实现PTC的患者，3） 估计/预测理论干预措施（例如LRA和/或）的影响 免疫疗法和4）提出有效的干预措施以实现“功能”治疗 根据患者特征。