Female Reproductive Tissue Mapping Center

摘要 胎盘、子宫、卵巢和输卵管协同作用，以实现成功的妊娠结局。 这些器官在整个生命周期中在结构和功能上都经历了显著的变化，与 通过直接和远距离的细胞-细胞相互作用相互作用。在这里，我们建议生成和集成来自 体内成像和体外组织病理学、生物力学和多组体空间轮廓数据，以便 生成健康的人类女性生殖器官的参考多比例3D地图，表示一系列 存在于女性生命中不同阶段的正常生理状态。这些将作为关键的框架 为未来旨在发现组织结构和功能的扰动如何导致器官的研究提供参考 功能障碍和疾病。我们的团队装备精良，拥有临床产科专业知识和 妇科和胎盘/围产期和妇科病理学，成像，空间分子图谱，单- 细胞组学、细胞外基质(ECM)生物学、生物力学测试、数据管理和计算 生物学。我们将利用我们成熟的翻译研究基础设施来招募不同的 健康的孕妇和非怀孕的绝经前后妇女接受 良性适应症的妇科手术。然后，我们将使用核磁共振和超声波进行体内成像 勾勒出组织结构、血流、炎症、钙化和其他特征。在分娩/手术后， 组织将以多种方式进行快速采样、处理和存储(新鲜、快速冷冻、保存在 用于最佳核酸分析和FFPE的解决方案)，以支持使用各种 分子方法，并保留额外的样本以供未来研究。详细回顾临床数据和 将对邻近组织切片进行正式的组织病理学评估，以确认正常组织 是从结果正常的受试者身上获得的。最初的体外分析将包括生物力学 测试，细胞外基质蛋白质组学，以及散装和单细胞RNAseq和ATACseq。这些研究的结果 将对研究进行分析，以确定后续成像质量细胞术(IMC)和空间成像的靶点 转录学研究。这些数据类型将被集成，以支持映射 不同的细胞类型以及细胞和周围细胞外基质之间的微观水平，以及 在宏观水平上，组织结构与生物力学特性和成像特征之间的关系。 胎盘中独特的内皮细胞群和绒毛外的内皮拟态 滋养细胞将提供与其他以内皮为中心的HuBMAP项目整合的独特机会(例如 淋巴系统、内皮图谱和肾脏图谱)。与其他HuBMAP中心的密切互动将是 为统一数据和元数据标准、共享资源(例如抗体)而建立 与正在开发/使用CODEX和MIBI-TOF的HuBMAP中心合作，迅速采用新技术， 协作数据分析，并与蜂巢和更广泛的科学界快速共享数据。

SUMMARY The placenta, uterus, ovary, and fallopian tube act in concert to achieve successful pregnancy outcomes. These organs undergo marked changes in structure and function throughout the lifespan, coordinating with one another via direct and distant cell-cell interactions. Here, we propose to generate and integrate data from in vivo imaging and ex vivo histopathologic, biomechanical, and multi-omic spatial profiling data, in order to generate reference multiscale 3D maps of healthy human female reproductive organs representing a range of normal physiologic states that exist at different points in a woman’s life. These will serve as key frames of reference for future studies aiming to discover how perturbation of tissue structure and function leads to organ dysfunction and disease. Our team is well-equipped to achieve this goal, with expertise in clinical Obstetrics & Gynecology and Placental/Perinatal and Gynecologic Pathology, imaging, spatial molecular profiling, single- cell omics, extracellular matrix (ECM) biology, biomechanical testing, data management, and computational biology. We will leverage our well-established translational research infrastructure to recruit diverse cohorts of healthy pregnant women and non-pregnant premenopausal and postmenopausal women undergoing gynecologic surgery for benign indications. We will then perform in vivo imaging using MRI and ultrasound to delineate tissue structure, perfusion, inflammation, calcifications, and other features. After delivery/surgery, tissues will be rapidly sampled, processed, and stored in multiple ways (fresh, flash frozen, preserved in solutions for optimal nucleic acid analysis, and FFPE) to enable generation of high-quality data using a variety of molecular approaches, with extra samples retained for future studies. Detailed review of clinical data and formal histopathologic evaluation of adjacent tissue sections will be performed to confirm that normal tissue has been obtained from subjects with normal outcomes. Initial ex vivo analysis will include biomechanical testing, extracellular matrix proteomics, and bulk and single-cell RNAseq and ATACseq. The results of these studies will be analyzed to identify targets for the subsequent imaging mass cytometry (IMC) and spatial transcriptomic studies. These data types will be integrated to enable mapping of the relationships among different cell types and between cells and the surrounding extracellular matrix on the microscopic level, and between tissue architecture and the biomechanical properties and imaging features on a macroscopic level. The unique populations of endothelial cells in the placenta and the endothelial mimicry of the extravillous trophoblast will provide unique opportunities to integrate with other endothelial-centric HuBMAP projects (e.g. lymphatic system, endothelial atlas, and kidney atlas). Close interactions with other HuBMAP Centers will be established to enable harmonization of data and metadata standards, sharing of resources (e.g. antibodies with HuBMAP Centers that are developing/using CODEX and MIBI-TOF), rapid adoption of new technologies, collaborative data analysis, and rapid sharing of data with the HIVE and the broader scientific community.