Leveraging Omics-Based Computational Approaches to Identify and Validate Novel Therapeutic Candidates for Endometriosis

摘要--项目3 子宫内膜异位症是一种常见的雌激素依赖型炎症性疾病，可导致慢性盆腔衰弱。 1.76亿人的疼痛包括严重的痛经和性交困难、不孕不育和生活质量下降 世界各地的妇女和青少年。子宫内膜异位症相关疼痛的治疗主要是手术和/或内科治疗。 手术切除疾病会导致50%的疼痛在2-5年内复发。医疗，主要是 几十年来没有变化，包括非类固醇抗炎药(NSAIDs)和降低 雌激素水平或相反的行为，并导致不同的症状缓解。的发展和可用性 大规模基因组、转录和其他分子图谱技术，与 药物靶标网络概念的部署和表型筛选的力量，提供了 推进合理药物再利用和药物数据驱动发展的前所未有的机遇 组合。项目3的目标是利用子宫内膜异位症转录学数据，结合公开的 可用的药物筛选数据，并应用计算药物再利用管道来识别单一药物和 基于表达逆转扰乱分子网络的现有药物的联合治疗 从疾病相关的细胞功能障碍，并验证选定的药物在人子宫内膜细胞体外和 子宫内膜异位症疼痛的动物模型。在目标1中，我们将使用基于转录的计算药物- 基于表达逆转的重新定位潜在的单药和联合疗法 利用公共转录组数据。我们的假设是，药物之间的反向表达模式 重新定位候选对象和疾病签名将导致治疗预测。在目标2中，我们将 确定感兴趣化合物(CoI)抑制原发疾病炎症信号反应的能力 人类免疫和子宫内膜细胞通过使用体外高通量质量标签条形码分析。 我们假设在硅胶中发现的最有希望的cois(目标1)将改善子宫内膜异位症的症状。 通过抑制子宫内膜和/或免疫细胞中的促炎信号反应。最后，在目标3中，我们将 在临床前子宫内膜异位症模型中确定感兴趣的化合物缓解疼痛的有效性。我们 假设用于治疗子宫内膜异位症的Cois将改变子宫内膜异位症 缓解疼痛的微环境。我们预计这项研究将作为研究新的 在子宫内膜组织中发现新的靶点和药物再利用以及功能验证 在临床前模型中进行测试，如果成功，将进行女性子宫内膜异位症相关疼痛的临床试验。我们 希望这一新的方法将改变对癌症的激素治疗模式 与子宫内膜异位症相关的盆腔疼痛，并将治疗选择扩大到新的治疗方法和现有的治疗方法 重新调整用途以改善数百万受影响妇女和青少年的生活并扩大#年的研究渠道 这个空间。

ABSTRACT – PROJECT 3 Endometriosis is a common, estrogen-dependent, inflammatory disorder that causes debilitating chronic pelvic pain including severe dysmenorrhea and dyspareunia, infertility, and a reduced quality of life for 176 million women and teens worldwide. Treatment of endometriosis-associated pain is mainly surgical and/or medical. Surgical removal of disease results in 50% relapse of pain within 2-5 years. Medical treatments, largely unchanged over decades, comprise nonsteroidal anti-inflammatory drugs (NSAIDs) and hormones that lower estrogen levels or oppose its actions, and result in variable symptom relief. The development and availability of large-scale genomic, transcriptomic, and other molecular profiling technologies, in combination with the deployment of the network concept of drug targets and the power of phenotypic screening, provide an unprecedented opportunity to advance rational drug repurposing and data-driven development of drug combinations. The goal of Project 3 is to leverage endometriosis transcriptomics data combined with publicly available drug screening data and apply a computational drug-repurposing pipeline to identify single agent and combination therapies from existing drugs based on expression reversal perturbing molecular networks away from disease-associated cellular dysfunction, and validate select drugs in human endometrial cells in vitro and an animal model of endometriosis pain. In Aim 1, we will use transcriptomic-based computational drug- repurposing to identify potential new single agent and combination therapeutics based on expression reversal leveraging public transcriptomics data. Our hypothesis is that the inverse expression profiles between the drug repositioning candidates and the disease signatures will result in therapeutic predictions. In Aim 2, we will determine the capacity of compounds of interest (COIs) to inhibit inflammatory signaling responses in primary human immune and endometrial cells through the use of an ex vivo high-throughput mass-tag barcoding assay. We hypothesize that the most promising COIs identified in silico (Aim 1) will improve endometriosis symptoms by inhibiting pro-inflammatory signaling responses in endometrial and/or immune cells. Finally, in Aim 3 we will determine the efficacy of compounds of interest to alleviate pain in a preclinical endometriosis model. We hypothesize that the COIs identified for the treatment of endometriosis will alter the endometriotic microenvironment to alleviate pain. We anticipate this study will serve as the basis for studies on newly discovered novel targets and drug-repurposing as well as functional validation in endometrial tissue as well as testing in preclinical models, and if successful, clinical trials for endometriosis-associated pain in women. We hope that this novel approach will change the paradigm of “one size fits all” hormonal treatment for endometriosis-associated pelvic pain and expand therapeutic options to new therapies and established therapies repurposed to improve the lives of millions of affected women and teens and expand the research pipeline in this space.