Multi-scale Spatial Mapping of Human Lymphatic Vessels

摘要： 淋巴疾病在美国影响着1000多万患者，而且严重 未得到充分研究。淋巴水肿是最常见的淋巴疾病，被认为是 美国最重要的癌症生存问题。值得注意的是，我们的主要理解是 淋巴系统的图谱来自动物模型。全面的解剖学参考资料来自 人类的淋巴系统目前还不存在。我们提出了淋巴组织的发育 作为美国国立卫生研究院人类生物分子图谱计划(HuBMAP)的一部分。具体来说， 通过包括贝丝以色列女执事医学中心在内的机构财团 南加州大学、宾夕法尼亚大学、斯坦福大学和印第安纳大学，我们将获得 健康个体的淋巴管收集器和毛细淋巴管在整个健康谱和 将这些样本中的每一个注册到相关的被子体，从而允许与 HuBMAP。这些样本将进行空间转录组分析。此外，我们还将执行3D 全身淋巴收集器的放射成像。空间转录组分析与3D 成像数据将被处理并传输到HuBMAP集成、可视化和项目 (蜂巢)协作型。淋巴组织测绘中心与HuBMAP一起，将提供精细的细节 淋巴系统的解剖精确度更好地指导未来的外科手术。空间上的 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.