Network-driven drug repurposing approaches to treat coronary artery disease

项目总结 冠心病(CAD)是世界范围内导致死亡和残疾的主要原因。连 在接受优化护理标准方案治疗的患者中，残余发病率和死亡率 保持高水平。直接针对动脉粥样硬化(冠心病的主要原因)的新策略是 急需之物。一种创新的方法是寻找针对分子功能障碍的药物 导致动脉壁出现动脉粥样硬化。系统遗传学是一种新的建模方法 复杂性状的分子功能障碍，如以调控基因网络的形式存在的CAD (RGNs)。与网络驱动的计算方法相结合，重新调整现有药物的用途 针对复杂疾病中的网络，系统遗传学可以加快发现 治疗冠心病的强大策略。在我们之前的工作中，使用系统遗传学的方法，我们 我发现了RGN42--一个由RNA处理基因组成的CAD因果网络 携带斯德哥尔摩动脉粥样硬化基因的冠心病患者的动脉粥样硬化 表达(阶段)研究。作为概念验证，我们让以下四个关键驱动因素的基因沉默 RGN42，发现体外培养的泡沫细胞中胆固醇酯蓄积明显。 受影响。接下来，我们应用了系统生物学和计算药物的严格结合 重新调整分析的目的，我们确定了几种预测会影响四个关键因素的化合物 RGN42中影响泡沫细胞形成的驱动程序。初步表型筛选显示 我们的两种最受欢迎的化合物在体外强烈抑制泡沫细胞的形成。 鉴于这些发现，我们假设RGN42靶向化合物(S)将显示出抗 动脉粥样硬化的功效。我们建议严格验证FDA的临床前疗效 批准的或2a阶段就绪的测试化合物(S)，目标是将结果转化为 人体临床试验。在具体目标1中，我们将确定最有效的RGN42目标 化合物具有防止体外泡沫细胞形成和体内动脉粥样硬化的能力。在……里面 具体目标2，我们将在体内测试复方(S)的治疗效果，采用翻译前 一种有效的动脉粥样硬化兔模型的临床成像 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 在经过验证的动脉粥样硬化大动物模型中靶向RGN42的化合物将提供 将我们的发现转化为临床试验的有力证据。这项研究将为 作为一个翻译平台，加快现有药物的新适应症的再利用 确定通过网络策略来治疗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.