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

总结 尽管使用降脂药物进行了优化治疗，例如经过充分验证的他汀类药物或新型PCSK 9 尽管心血管疾病已成为抑制剂的替代品，但心血管疾病仍然是全球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风险动脉粥样硬化斑块发展的已知关键驱动因素 (such如心肌梗塞和中风），并且代表了进一步减少 心血管风险然而，直到最近，新疗法的临床转化，或已经 FDA批准的通过靶向炎症降低心血管风险的药物已被证明是困难的。的一部分 这些研究所面临的挑战是，这些治疗化合物已经基于单- 靶向药物发现。然而，常见的复杂疾病的生物结构，如心血管疾病， 疾病，更好地解释了基因调控网络（GRN）内和跨组织的作用。确定新 使用现有的药物来恢复动脉粥样硬化血管中GRN的功能是一个突破性的和成本- 有效治疗CVD的策略。利用创新和严格的系统遗传学和 计算药物再利用分析，我们以前已经确定了现有的化合物预测， 影响RGN 42中四个关键驱动基因的功能，RGN 42是一个在动脉粥样硬化中起作用的CVD因果网络。 影响泡沫细胞形成的患者动脉壁。在之前的工作（R21 TR 001739）中，我们严格验证了 使用多模态方法靶向RGN 42的热门化合物Auranofin的临床前疗效 包括体外实验、体内小鼠工作和体内18F-FDG PET成像， 在兔动脉粥样硬化模型中的炎症。我们的数据表明金诺芬单独或联合使用 他汀类药物有效地减少动脉粥样硬化斑块炎性细胞（巨噬细胞）的含量， 在兔模型中斑块炎症的发展。根据这些结果，我们建议开展 计划进行临床试验，以测试金诺芬对心血管疾病患者的影响。我们的具体 该应用的目的是i）确定最佳目标群体，因为我们确定治疗剂量和持续时间， ii）确定一般研究设计和替代成像终点以确定药物功效 在我们的患者群体中;和iii）鉴定与药物功效相关的血液生物标志物和分子特征， 并将这些标记与成像结果结合起来。我们预计，我们未来的临床试验结果将 代表了未来更广泛的III期临床研究的基础，以更好地建立金诺芬的使用 在心血管疾病中。

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.