Network-driven drug repurposing approaches to treat coronary artery disease

项目摘要 冠状动脉疾病（CAD）是全球死亡和残疾的主要原因。甚至 在接受优化标准治疗方案治疗的患者中， 保持高。直接针对动脉粥样硬化（CAD的主要原因）的新策略包括 迫切需要。一种创新的方法是找到针对分子功能障碍的药物 导致动脉壁的动脉粥样硬化。系统遗传学是一种新的方法， 以调控基因网络形式存在的复杂性状（如CAD）的分子功能障碍 （RGN）。结合网络驱动的计算方法来重新利用现有药物 针对复杂疾病的网络，系统遗传学可以加速发现 治疗CAD的有效策略。在我们以前的工作中，使用系统遗传学方法，我们 已经确定了RGN 42--一个由RNA加工基因组成的CAD因果网络， 冠心病患者动脉粥样硬化血管壁的斯德哥尔摩动脉粥样硬化基因 表达（STAGE）研究。作为一个概念验证，我们沉默了四个关键驱动基因， RGN 42，并发现在体外泡沫细胞中胆固醇酯的积累是显著的。 影响。接下来，我们将系统生物学和计算药物严格结合起来， 重新利用分析，我们确定了几种化合物预测影响四个关键 RGN 42中影响泡沫细胞形成的驱动因子。初步的表型筛选显示， 我们的两种最受欢迎的化合物在体外强烈抑制泡沫细胞形成。 鉴于这些发现，我们假设RGN 42靶向化合物将显示抗- 动脉粥样硬化疗效我们建议严格验证FDA的临床前有效性， 批准或2a期准备测试化合物，目的是将发现转化为 人体临床试验在具体目标1中，我们将确定最有效的RGN 42靶向 化合物在体外防止泡沫细胞形成和在体内防止动脉粥样硬化的能力。在 具体目标2，我们将使用翻译前修饰来测量化合物的体内治疗功效。 在一个经过充分验证的动脉粥样硬化兔模型中的临床成像， 人类动脉粥样硬化斑块的复杂性优于小鼠模型。 使用复杂的非侵入性成像方式来测量 在动脉粥样硬化的经验证的大型动物模型中靶向RGN 42的化合物将提供 为我们的发现转化为临床试验提供了有力的证据。这项研究将为 一个转化平台，以加速现有药物的重新用途， 通过网络策略确定治疗CAD。

PROJECT SUMMARY Coronary artery disease (CAD) is the leading cause of mortality and disability worldwide. Even in patients treated with optimized standard-of-care regimens, residual morbidity and mortality remain high. New strategies that directly target atherosclerosis—the main cause of CAD—are urgently needed. One innovative approach is to find drugs that target the molecular dysfunctions that drive atherosclerosis in the arterial wall. Systems genetics is a new approach that models molecular dysfunctions of complex traits like CAD in the form of regulatory gene networks (RGNs). Combined with network-driven computational approaches to repurpose existing drugs targeting networks in complex diseases, systems genetics can speed up the discovery of powerful strategies to treat CAD. In our previous work, using a systems genetics approach, we have identified RGN42—a CAD-causal network consisting of RNA-processing genes acting in the atherosclerotic arterial wall of CAD patients of the Stockholm Atherosclerosis Gene Expression (STAGE) study. As a proof-of-concept, we silenced the four key drivers genes of RGN42 and found that cholesterol-ester accumulation in foam-cells in vitro was markedly affected. Next we applied a rigorous combination of systems biology and computational drug repurposing analyses and we identified several compounds predicted to influence the four key drivers in RGN42 that affect foam cell formation. Preliminary phenotypic screening revealed that two of our top-hit compounds strongly inhibit foam-cell formation in vitro. Given these findings, we hypothesize that RGN42-targeted compound(s) will show anti- atherosclerotic efficacy. We propose to rigorously validate the pre-clinical efficacy of either FDA approved or phase 2a-ready test compound(s), with the goal of translating the findings into human clinical trials. In specific Aim 1, we will identify the most effective RGN42-targeted compounds for their ability to prevent foam-cell formation in vitro and atherosclerosis in vivo. In Specific Aim 2, we will measure compound(s) therapeutic efficacy in vivo using translational pre- clinical imaging in a well-validated rabbit model of atherosclerosis that recapitulates the complexity of human atherosclerotic plaques better than mouse models. The use of sophisticated, non-invasive imaging modalities to measure the efficacy of compounds targeting RGN42 in a validated large animal model of atherosclerosis will provide robust evidence for the translation of our findings to clinical trials. This study will set the stage for a translational platform to speed the repurposing of existing drugs with new indications identified by network strategies to treat CAD.