Network-driven drug repurposing in cardiovascular disease: NDRA clinical trial planning

摘要 尽管使用降脂药物进行了优化治疗，如经过良好验证的他汀类药物或新型PCSK9 心血管疾病仍然是世界范围内发病率和死亡率的主要原因。炎症 是导致严重临床事件的高危动脉粥样硬化斑块的已知关键驱动因素 (如心肌梗塞和中风)，是进一步减少 心血管风险。然而，直到最近，新疗法的临床翻译，或已经 FDA批准的通过针对炎症来降低心血管风险的药物已被证明是困难的。部分内容 这些研究面临的挑战是，这些治疗性化合物是基于单一的- 目标药物发现。然而，常见复杂疾病的生物学结构，如心血管疾病 疾病，更好地解释为基因调控网络(GRN)作用于组织内和跨组织。确定新的 使用现有的药物来恢复动脉粥样硬化血管中GRN的功能是一项开创性的和成本- 治疗脑血管病的有效策略。使用创新和严格的系统遗传学和 计算药物再用途分析，我们之前已经确定了现有的化合物预计将 RGN 42中四个关键驱动基因对动脉粥样硬化中心血管疾病因果网络功能的影响 影响泡沫细胞形成的患者的动脉壁。在之前的工作(R21TR001739)中，我们严格验证了 多模式靶向RGN42的头号靶向化合物金诺芬的临床前疗效 包括体外实验、体内小鼠工作和体内翻译的18F-FDG PET成像 动脉粥样硬化兔模型的炎症反应。我们的数据表明，Auranofin单独或联合使用 他汀类药物能有效降低动脉粥样硬化斑块炎性细胞(巨噬细胞)的含量，阻止 斑块炎症在兔模型中的发展。基于这些结果，我们建议进行 计划一项临床试验，以测试金诺芬对心血管疾病患者的疗效。我们的特定 这项应用的目的是i)确定最佳目标人群，因为我们认为治疗剂量和持续时间 Auranofin；ii)确定一般研究设计和替代成像终点以确定药物疗效 在我们的患者群体中；以及iii)识别与药物疗效相关的血液生物标志物和分子签名， 并将这些标记物与成像结果联系起来。我们预计，我们未来的临床试验结果将 为未来更广泛的第三阶段临床研究奠定基础，以更好地确定金诺芬的使用 在心血管疾病方面。

Summary Despite optimized treatments with lipid lowering drugs, such as the well-validated statins or novel PCSK9 inhibitors, cardiovascular disease still remains the main cause of morbidity and mortality worldwide. Inflammation is a known key driver in the development of atherosclerotic plaques at high-risk for causing severe clinical events (such as myocardial infarction and stroke) and represents a promising therapeutic target to further reduce cardiovascular risk. However, up until recently, clinical translation of new therapies, or the repurposing of already FDA-approved drugs that lower cardiovascular risk by targeting inflammation, has proven difficult. Part of the challenge faced by these studies is that these therapeutic compounds have been identified based on single- target drug discovery. However, the biological architecture of common complex disorders, like cardiovascular disease, is better explained by gene regulatory networks (GRN) acting within and across tissues. Identifying new uses for existing drugs to restore the function of GRN in atherosclerotic vessels is a groundbreaking and cost- effective strategy to treat CVD. Using an innovative and rigorous combination of systems genetics and computational drug repurposing analyses, we have previously identified existing compounds predicted to influence the function of four key driver genes in RGN 42, a CVD-causal network acting in the atherosclerotic arterial wall of patients that affect foam cell formation. In previous work (R21TR001739), we rigorously validated the pre-clinical efficacy of Auranofin, the top-hit compound targeting RGN42 using a multimodality approach encompassing in vitro experiments, in vivo mouse work and translational in vivo 18F-FDG PET imaging of inflammation in a rabbit model of atherosclerosis. Our data demonstrates that auranofin alone or in combination with statin effectively reduces atherosclerotic plaque inflammatory cells (macrophages) content and halts the development of plaque inflammation in the rabbit model. Based on these results, we propose to engage in the planning of a clinical trial to test the effects of Auranofin in patients with cardiovascular disease. Our specific aims for this application are i) to identify the optimal target population, as we as treatment dose and duration for Auranofin; ii) to determine the general study design and surrogate imaging endpoints to determine drug efficacy in our patient population; and iii) to identify blood biomarkers and molecular signatures related to drug efficacy, and to ingrate these markers with imaging results. We anticipate that the results of our future clinical trial will represent the basis for future, more extensive Phase III clinical studies to better establish the use of Auranofin in cardiovascular disease.