Quantitative proteomic profiling of extracellular vesicles from menstrualeffluent for the discovery of non-invasive diagnostic biomarkers of endometriosis

摘要： 子宫内膜异位症是一种由子宫内膜腺体和间质向子宫腔外延伸引起的疾病。 大约10%的育龄妇女，仅在美国就有400多万，受到以下因素的影响： 子宫内膜异位症;由于未确诊病例的高比率，预计真正的患病率要高得多。 严重的身体，心理和经济痛苦已被记录在患者患有 子宫内膜异位症尽管有巨大的兴趣和未满足的需求，但没有FDA批准的非侵入性 子宫内膜异位症的诊断工具或生物标志物。其中一个主要原因是缺乏对 临床症状、组织学表现和导致 疾病此外，子宫内膜异位症通常与一系列其他疾病有关， 噪声细胞外囊泡（EV）由所有细胞分泌，并且被认为介导细胞间以及细胞内的细胞毒性。 器官间的通信，并已知传达特定的疾病状态。电动汽车一直是 假设在子宫内膜异位症的发病机制和诊断中发挥作用。在疾病中，已知EV含量 以一种高度特异性的方式来反映疾病类型。我们力求克服低信号、高噪声 子宫内膜异位症生物标志物发现的障碍：1）关注EV，疾病的细胞信使， 存在于月经流出物中，2）使用最先进的、高灵敏度的定量蛋白质组学技术，和3） 使用生物标志物的群组/组。我们在蛋白质组学技术上的进步， 显著的数量差异。结合起来，它们提出了一个非常重要的概念，技术， 仪器跨越过去的研究。我们将使用同量异位素进行多重定量蛋白质组学 手术证实的子宫内膜异位症患者月经流出物EV上的串联质量标签（TMT）， 将其与患有子宫内膜异位症样症状（包括慢性盆腔疼痛）但没有 子宫内膜异位症在手术中被发现。它将为我们提供一个患者特异性，高质量的数据库， 月经流出物中分泌的外泌体的蛋白质组含量，并鉴定其上的功能性信号传导网络， 为开发月经流出物中的EV奠定基础。该补助金的目标是确定 月经流出物EV上子宫内膜异位症的生物标志物的群组/组，其可以用于测定 第二阶段的开发和临床验证。

Abstract: Endometriosis is a disease caused by the extension of endometrial glands and stroma outside the uterine cavity. Approximately 10% of reproductive age women, more than 4 million in the United States alone, are affected by endometriosis; the true prevalence is expected to be much higher due to the high rate of undiagnosed cases. Significant physical, psychological, and economic suffering has been documented in patients suffering from endometriosis. In spite of the tremendous interest and unmet need, there is no FDA-approved non-invasive diagnostic tool or biomarker for endometriosis. One of the key reasons is the lack of understanding of the correlation between clinical symptoms, histological manifestations, and underlying dysfunction resulting in disease. In addition, endometriosis is often associated with a range of other disorders, creating a high biomarker noise. Extracellular vesicles (EV) are secreted by all cells and are thought to mediate intercellular as well as inter-organ communication and are known to communicate the specific disease state. EVs have been hypothesized to play a role in the pathogenesis and diagnosis of endometriosis. In disease, EV content is known to be altered to reflect the disease type in a highly specific way. We seek to overcome the low signal, high noise hurdle of endometriosis biomarker discovery by 1) focusing on EVs, the cellular messengers of the disease, present in menstrual effluent 2) using state of the art, highly sensitive, quantitative proteomic technique, and 3) using cohort/panel of biomarkers. Our improvement in proteomic technique alone results in 10-fold more significant quantitative differences. In combination, they present a very significant conceptual, technical, and instrumentation leap over past studies. We will perform the multiplexed quantitative proteomics using isobaric tandem mass tags (TMT) on menstrual effluent EVs from surgically confirmed endometriosis patients and compare them to controls with endometriosis like symptoms including chronic pelvic pain, but with no endometriosis being detected at the surgery. It will provide us a patient specific, high-quality database of proteomic content of exosomes secreted in menstrual effluent and identify functional signaling networks on them, to lay down the foundation for the exploration of EVs from menstrual effluent. The goal of this grant is to identify the cohort/panel of biomarkers of endometriosis on menstrual effluent EVs, that can be taken to assay development and clinical validation in phase II.