Multi-scale Spatial Mapping of Human Lymphatic Vessels

摘要： 在美国，淋巴疾病影响超过1000万患者， 替补演员淋巴水肿是最常见的淋巴系统疾病，被认为是一种 美国最重要的癌症生存问题。值得注意的是，我们的初步理解是， 和淋巴系统的绘图来自动物模型。一个全面的解剖参考， 人体淋巴系统目前还不存在。我们提出淋巴组织的发展 作为NIH人类生物分子图谱计划（HuBMAP）的一部分。具体地说， 通过一个机构联盟，包括贝丝以色列女执事医疗中心， 南加州、宾夕法尼亚大学、斯坦福大学和印第安纳州大学，我们将收购 在整个健康范围内的健康个体中的淋巴收集器和毛细淋巴管， 将这些样品中的每一个配准到相关的血管小体，从而允许与 HuBMAP。这些样本将进行空间转录组分析。此外，我们将执行3D 全身淋巴收集器的放射成像。空间转录组分析和3D 成像数据将被处理并传输到HuBMAP集成、可视化和参与系统 （蜂巢）协作。淋巴组织绘图中心与HuBMAP一起，将提供详细的信息， 淋巴系统的解剖学精确性更好地为未来的外科手术提供信息。空间 转录组分析将为未来的药物治疗提供潜在的靶点。

Abstract: Lymphatic disease affects over 10 million patients in the United States and are grossly understudied. Lymphedema, the most commonly occurring lymphatic disease, is considered one on of the most significant cancer survivorship issues in the United States. Of significant note, our primary understanding and mapping of the lymphatic system come from animal models. A comprehensive anatomic reference from the human lymphatic system does not currently exist. We propose the development of a lymphatic tissue mapping center (TMC) as a part of the NIH Human Biomolecular Atlas Program (HuBMAP). Specifically, through a consortium of institutions including the Beth Israel Deaconess Medical Center, University of Southern California, University of Pennsylvania, Stanford University, and Indiana University, we will acquire both lymphatic collectors and lymphatic capillaries in healthy individuals across the entire health spectrum and register each of these samples to the associated angiosome thereby allowing coordination with HuBMAP. These samples will undergo spatial transcriptome analysis. Moreover, we will perform 3D radiologic imaging of lymphatic collectors throughout the body. The spatial transcriptome analysis and 3D imaging data will be processed and transferred to the HuBMAP Integration, Visualization, and Engagement (HIVE) Collaborative. The lymphatic tissue mapping center, alongside HuBMAP, will provide fine detail anatomic precision of the lymphatic system better informing future surgical interventions. The spatial transcriptome analysis will provide potential targets for future pharmacologic therapeutics.