Project 2: Delineating virus and host cell-derived biomarkers predicting time to HIV rebound after treatment interruption

项目 2：描绘病毒和宿主细胞衍生的生物标志物，预测治疗中断后 HIV 反弹的时间

• 批准号: 10223996
• 负责人: Warner C. Greene
• 金额: $ 76.27万
• 依托单位: J. DAVID GLADSTONE INSTITUTES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-08 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10223996
• 关键词: Aftercare; Antiviral Agents; Apoptosis; Automobile Driving; Bioinformatics; Biological Assay; Biological Markers; Biological Process; Biostatistics Core; Blood; Blood Cells; Blood specimen; CASP1 gene; CD4 Positive T Lymphocytes; Cell Therapy; Cells; Chemicals; Chronic; Cleaved cell; DNA; Data; Data Set; Disease remission; Ensure; Future; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic; Goals; Gold; HIV; Hour; Immune; Individual; Inflammation; Interleukin-1 beta; Interleukin-15; Interleukin-18; Interruption; Length; Leukapheresis; Libraries; Logistics; Maintenance; Measurement; Measures; Mediating; Mediator of activation protein; Messenger RNA; MicroRNAs; Morbidity - disease rate; Patients; Peripheral Blood Mononuclear Cell; Plasma; Population; Positioning Attribute; Process; Production; Proteins; Proviruses; RNA; Research; Rest; Risk; Scientist; Surrogate Endpoint; T memory cell; T-Lymphocyte; Testing; Therapeutic; Therapeutic Intervention; Time; Tissues; United States National Institutes of Health; Viral; Viral Load result; Viremia; Virus; Work; acute infection; antiretroviral therapy; antiviral immunity; base; chronic infection; clinical decision-making; cohort; complex data; cost; curative treatments; cytokine; design; digital; drug development; exhaustion; extracellular vesicles; inflammatory marker; insight; latent HIV reservoir; memory CD4 T lymphocyte; miRNA expression profiling; mortality; novel; patient subsets; potential biomarker; predictive marker; programmed cell death protein 1; research clinical testing; specific biomarkers; transcriptome sequencing; viral DNA; viral RNA; viral rebound; volunteer

Project Summary/Abstract Although antiretroviral therapy (ART) inhibits HIV replication and decreases morbidity and mortality, it does not cure. Interruption of ART is routinely followed by viral rebound springing from a small but durable reservoir of latently infected, long lived, memory CD4 T cells. New chemical-, immune- and gene-and cell- based therapies are now being developed that will be aimed at eradicating this reservoir (difficult to achieve) or reducing its size and boosting boosting antiviral immunity sufficiently that ART can be safely stopped without high level viral rebound (functional cure). The search for curative therapies would be greatly facilitated by the availability of a set of robust biomarkers that can accurately predict whether a specific therapeutic is effective or not. Such biomarkers could help ensure that only the most promising candidates advance to analytic treatment interruption––the current gold standard for clinical testing of cure therapeutics. ATI studies need to be minimized because they are inherently costly, logistically challenging and create potential risks for patients during viral rebound. These biomarkers might also provide key insight into what biological processes are most promising for attacking the reservoir and achieving the desired delay in time to rebound. We hypothesize that highly robust virus-specific and host–specific biomarkers can be identified in blood that accurately predict the duration of viral remission after treatment interruption as well as impending viral rebound. To pursue identification of both virus- and host-directed biomarkers, blood samples from 125 HIV infected subjects (both treated during acute and chronic infection) obtained before ATI and after viral rebound will be analyzed by three different approaches: (1) Resting blood CD4 T cells will be tested with a novel digital droplet PCR assay (IPDA) that selectively detects intact proviral DNA in the reservoir––these intact viruses represent the key small fraction of the proviruses in the reservoir that are replication competent and thus able to drive viral rebound. Low IPDA results prior to ATI could be associated with long times to viral rebound; this assay can be performed in 6 hours and only requires the equivalent of a 20 ml blood draw; (2) RNA from both CD4 T and non-CD4 T cells will be subjected to RNA-Seq and miRNA-Seq analyses to identify patterns of gene expression associated with markedly delayed or accelerated times to viral rebound and (3) Measurement of pyroptotic inflammatory markers in cells and plasma as biomarkers predicting rapid loss of viral control or impending viral rebound during ATI. The complex data sets generated by RNA-Seq will analyzed with the help of the Bioinformatics and Biostatistics core. This project will also closely interface with both Projects 1 and 2 where complementary approaches will be pursued searching for biomarkers in blood cells and in plasma or circulating extracellular vesicles. By careful execution of this comprehensive virus- and host-directed search, our project team should be strongly positioned to discover a robust set of new biomarkers that could truly galvanize future HIV cure research.

项目摘要/摘要 虽然抗逆转录病毒疗法(ART)可以抑制艾滋病毒的复制，降低发病率和死亡率，但它 并不能治愈。艺术的中断之后，通常会出现病毒般的反弹，从一个小但持久的 潜伏感染、长寿、记忆的CD4T细胞的蓄水池。新的化学、免疫、基因和细胞 目前正在开发旨在根除这种蓄水池的基础疗法(难以实现)或 缩小其体积并增强足够的抗病毒免疫力，使ART可以安全地停止 高水平病毒反弹(功能治愈)。寻找根治疗法将极大地促进 一组强大的生物标志物的可用性，可以准确地预测特定的治疗是否有效 或者不去。这样的生物标记物可以帮助确保只有最有希望的候选者才能进入分析 治疗中断--目前治疗疗法临床测试的黄金标准。ATI研究需要 将成本降至最低，因为它们本身成本高昂，在后勤方面具有挑战性，并会给患者带来潜在风险 在病毒反弹期间。这些生物标志物也可能提供对生物过程最重要的洞察 有望攻克油层，及时实现预期的延时反弹。我们假设 可以在血液中识别高度强健的病毒特异性和宿主特异性生物标志物，准确地预测 治疗中断后病毒缓解的持续时间以及即将出现的病毒反弹。 为了同时识别病毒和宿主导向的生物标记物，125名艾滋病毒患者的血液样本 感染者(在急性和慢性感染期间均接受治疗)在ATI前和病毒反弹后获得 将通过三种不同的方法进行分析：(1)将静息血液中的CD4T细胞用一种新型的数字技术进行检测 滴状聚合酶链式反应试验(IPDA)选择性地检测水库中完整的前病毒DNA--这些完整的病毒 代表储存库中具有复制能力的前病毒的关键小部分 以推动病毒反弹。ATI前的低IPDA结果可能与病毒反弹的时间较长有关；这 化验可以在6小时内进行，只需要相当于20毫升的抽血；(2)来自两个地方的核糖核酸 将对CD4T和非CD4T细胞进行RNA-Seq和miRNA-Seq分析，以确定 与显著延迟或加速病毒反弹时间相关的基因表达和(3)测量 细胞和血浆中嗜热炎症标志物作为预测病毒控制或迅速消失的生物标志物 在ATI期间即将出现病毒反弹。我们将利用该工具对RNA-Seq生成的复杂数据集进行分析 生物信息学和生物统计学核心。该项目还将与项目1和项目2密切对接 将采用互补的方法在血细胞和血浆中寻找生物标志物 循环中的细胞外小泡。通过仔细执行这种针对病毒和宿主的全面搜索， 我们的项目团队应该能够发现一组强大的新生物标记物，这些标记物可以真正 激励未来的艾滋病毒治疗研究。