Developing a non-invasive, definitive diagnostic for endometriosis using biomarkers in menstrual effluence

摘要 子宫内膜异位症是一种复杂的疾病，平均而言，从症状开始到发病有十年的间隔。 诊断。此外，由于目前手术性质的子宫内膜异位症的诊断(腹腔镜)，研究 涉及确诊病例的研究很难获得，招募人员的成本也很高。腹腔镜术 (恢复时间2-6周)，然后进行组织学检查被认为是诊断的金标准。 然而，即使接受手术治疗，50%的患者仍有复发，这突显了这样一个事实 无论采取何种手术或治疗措施，子宫内膜异位症都表现出周期性的激活状态。 因此，一种非侵入性的、可靠的子宫内膜异位症生物标志物检测是一个重要的未得到满足的医学需求。 子宫内膜异位症的非侵入性诊断将促使疾病的更早发现，并可能从根本上 通过防止疾病进展来改变患者的预后。月经液是生殖的丰富来源 可用于疾病诊断的组织。下一代简正在开发一种月经流出物 收集工具，智能棉签系统(STS)，解决了非侵入性样本获取的问题 并方便地将样品运送到实验室。 为了开发一种可靠的子宫内膜异位症生物标志物，我们使用STS设备的初步数据 表明我们可以在月经流出物中检测到多种RNA物种，其中一些以前 在其他相关研究中发现的。我们相信，STS提供了无与伦比的月经便利 并显著提高了样品处理效率。这些因素以及已演示的实用程序 作为RNAseq样本的STS(在其他研究中)将该建议与其他非侵入性建议区分开来 子宫内膜异位症的检测方法。 我们的目标是通过检查基因组，开发一种非侵入性的子宫内膜异位症是/否诊断试验。 月经期间子宫内膜组织脱落到卫生棉条上的征象。为了进一步识别和评估 月经液中基因组标志物的表现，我们将纳入72例阴性或阳性患者 子宫内膜异位症的手术确认：首先，从先导数据中确认先前识别的生物标记物 来评估疾病的诊断。其次，我们将使用RNAseq数据的统计分类来检验 约300例腹腔镜手术前后的患者样本匹配，以确认miRNA和 与患者调查数据一致的信使核糖核酸生物标记物。

Summary Endometriosis is a complex disease that on average, involves a ten-year gap between symptom onset and diagnosis. Moreover, due to the current surgical nature of endometriosis diagnosis (laparoscopy), research studies involving confirmed cases are both difficult to obtain and costly to recruit for. Laparoscopic surgery (recovery times 2-6 weeks) followed by histological confirmation is considered the gold standard for diagnosis. However, even with surgical intervention, 50% of patients have recurrence, underlining the fact that endometriosis shows periodic states of activation, regardless of surgical or therapeutic intervention. Consequently, a non-invasive, reliable biomarker test for endometriosis is a significant unmet medical need. A non-invasive diagnostic for endometriosis would motivate earlier detection of disease and could fundamentally change a patient’s prognosis by preventing disease progression. Menstrual fluid is a rich source of reproductive tissue that can be utilized for disease diagnosis. Next Gen Jane are developing a menstrual effluent competent collection tool, the Smart Tampon System (STS) which addresses issues of non-invasive sample accessibility and ease of sample transport to a laboratory. Toward development of a reliable biomarker for endometriosis, our preliminary data with the STS device indicates we can detect multiple RNA species in menstrual effluent, some of which have been previously discovered in other related studies. We believe that the STS provides unparalleled ease of access to menstrual effluent and markedly improves sample handling efficiencies. These factors alongside the demonstrated utility of the STS as a sample for RNASeq (amongst other studies) differentiates this proposal from other non-invasive approaches to detection of endometriosis. Our goal is to develop a non-invasive ”yes/no” diagnostic test for endometriosis by examining the genomic signatures of endometrial tissue shed into a tampon during menstruation. In order to further identify and evaluate the performance of genomic markers in menstrual fluid, we will enroll 72 patients with a negative or positive surgical confirmation of endometriosis in order to: Firstly, confirm previously identified biomarkers from pilot data that evaluates diagnosis of disease. Secondly, we will use statistical classification of RNASeq data to examine ~300 pre- and post- laparoscopy matched patient samples to confirm sensitivity and specificity of miRNA and mRNA biomarkers in concert with patient survey data.