Determinants of the efficacy of HIV latency-reversing agents and implications for drug and treatment design

Determinants of the efficacy of HIV latency-reversing agents and implications for drug and treatment design
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DOI:
10.1172/jci.insight.123052
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发表时间:
2018-10-18
期刊:
影响因子:
8
通讯作者:
Perelson, Alan S.
Perelson, Alan S.
中科院分区:
医学1区
文献类型:
--
作者:
Ke, Ruian;Conway, Jessica M.;Perelson, Alan S.

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艾滋病毒根除研究的重点是开发潜伏期逆转剂(LRA)。然而,还不了解潜伏储层减少的速率如何受到潜伏逆转过程中的不同步骤的影响。此外,由于目前的LRA是针对宿主的,因此LRA治疗可能是间歇性的,以避免宿主毒性。很少有仔细研究的系列效应脉动LRA治疗尚未完成。这种缺乏明确性使得难以评估候选LRA的疗效或预测长期治疗结果。我们构建了一个数学模型,描述了LRA治疗下潜伏感染细胞的动力学。模型分析表明,除了增加感染细胞的免疫识别和清除外,HIV抗原表达的持续时间(即,脆弱期)在确定LRA的效力方面发挥着重要作用,特别是在实现有效清除的情况下。与持续暴露于上帝抵抗军相比,如果在存在和不存在上帝抵抗军的情况下,患者的脆弱期较长且清除率较高,则患者可能受益于脉冲性上帝抵抗军暴露。总体而言,模型框架作为一个有用的工具,以评估疗效和合理设计的LRA和组合策略。
HIV eradication studies have focused on developing latency-reversing agents (LRAs). However, it is not understood how the rate of latent reservoir reduction is affected by different steps in the process of latency reversal. Furthermore, as current LRAs are host-directed, LRA treatment is likely to be intermittent to avoid host toxicities. Few careful studies of the serial effects of pulsatile LRA treatment have yet been done. This lack of clarity makes it difficult to evaluate the efficacy of candidate LRAs or predict long-term treatment outcomes. We constructed a mathematical model that describes the dynamics of latently infected cells under LRA treatment. Model analysis showed that, in addition to increasing the immune recognition and clearance of infected cells, the duration of HIV antigen expression (i.e., the period of vulnerability) plays an important role in determining the efficacy of LRAs, especially if effective clearance is achieved. Patients may benefit from pulsatile LRA exposures compared with continuous LRA exposures if the period of vulnerability is long and the clearance rate is high, both in the presence and absence of an LRA. Overall, the model framework serves as a useful tool to evaluate the efficacy and the rational design of LRAs and combination strategies.