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

对月经排出物细胞外囊泡进行定量蛋白质组学分析，以发现子宫内膜异位症的非侵入性诊断生物标志物

• 批准号: 10547052
• 负责人: Pranav Sharma
• 金额: $ 30.99万
• 依托单位: XOSOMIX LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10547052
• 关键词: Affect; Age; Bioinformatics; Biological; Biological Markers; Biology; Cells; Chronic; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Communication; Complex; Data; Data Set; Databases; Detection; Diagnosis; Diagnostic tests; Disease; Disease model; Economics; Electrons; Endometrial; FDA approved; Failure; Foundations; Functional disorder; Future; Gland; Goals; Grant; Heterogeneity; Histologic; Human; Induced pluripotent stem cell derived neurons; Inflammation; Lesion; Location; Mass Spectrum Analysis; Mediating; Menstrual cycle; Mutation; Nervous system structure; Neurodevelopmental Disorder; Noise; Operative Surgical Procedures; Organ; Pathogenesis; Patients; Pelvic Pain; Phase; Play; Prevalence; Proteins; Proteome; Proteomics; Quality of life; Reporting; Rett Syndrome; Role; Sampling; Signal Transduction; Symptoms; Systemic disease; Techniques; Testing; Tissues; United States; Uterine cavity; Validation; Woman; Work; analysis pipeline; assay development; autism spectrum disorder; biomarker discovery; biomarker panel; cell type; chronic pelvic pain; cohort; comorbidity; cost; diagnostic assay; diagnostic biomarker; diagnostic tool; economic cost; endometrial stroma; endometriosis; exosome; experimental study; extracellular vesicles; improved; instrumentation; interest; loss of function; noninvasive diagnosis; pain patient; psychologic; reproductive; therapeutic target

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.

抽象的： 子宫内膜异位症是由子宫内膜腺和子宫腔外的基质扩展引起的疾病。 仅在美国，大约有10％的生殖年龄妇女受到了400万的影响 子宫内膜异位症；由于未诊断的病例率高，预计真正的患病率将更高。 患有患者 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 用于子宫内膜异位症的诊断工具或生物标志物。关键原因之一是缺乏对 临床症状，组织学表现和潜在功能障碍之间的相关性导致 疾病。此外，子宫内膜异位症通常与其他一系列疾病有关，从而产生高生物标志物 噪音。细胞外囊泡（EV）被所有细胞分泌，被认为介导细胞间和 人体间的交流，众所周知可以传达特定的疾病状态。电动汽车已经过去了 假设在子宫内膜异位症的发病机理和诊断中发挥作用。在疾病中，EV含量已知 要改变以反映疾病类型的高度特异性。我们试图克服低信号，高噪声 子宫内膜异位症生物标志物发现障碍1）专注于电动汽车，该疾病的细胞使者， 在月经中存在2）使用最敏感，定量蛋白质组学技术和3） 使用队列/生物标志物。我们仅蛋白质组学技术的改进会增加10倍 显着的定量差异。结合起来，它们提出了非常重要的概念，技术和 仪器超越过去的研究。我们将使用同骨进行多路复用定量​​蛋白质组学 来自手术确认的子宫内膜异位症患者的月经流出EV的串联质量标签（TMT）和 将它们与子宫内膜异位症的对照进行比较，例如包括慢性骨盆疼痛在内的症状，但没有 在手术中检测到子宫内膜异位症。它将为我们提供一个特定于患者的高质量数据库 月经流出物中分泌的外泌体的蛋白质组学含量，并识别其上的功能信号网络， 为从月经流出的探索电动汽车奠定基础。这笔赠款的目的是确定 子宫内膜异位症在月经流出电动汽车上的同类群体/面板，可用于测定 II期的开发和临床验证。