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癌症组织的数据丰富空间分析:天文学为病理学提供信息。

Data-Rich Spatial Profiling of Cancer Tissue: Astronomy Informs Pathology.

机构信息

Department of Physics and Astronomy, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, Maryland.

The Mark Foundation Center for Advanced Genomics and Imaging, Johns Hopkins University, Baltimore, Maryland.

出版信息

Clin Cancer Res. 2022 Aug 15;28(16):3417-3424. doi: 10.1158/1078-0432.CCR-19-3748.

Abstract

Astronomy was among the first disciplines to embrace Big Data and use it to characterize spatial relationships between stars and galaxies. Today, medicine, in particular pathology, has similar needs with regard to characterizing the spatial relationships between cells, with an emphasis on understanding the organization of the tumor microenvironment. In this article, we chronicle the emergence of data-intensive science through the development of the Sloan Digital Sky Survey and describe how analysis patterns and approaches similarly apply to multiplex immunofluorescence (mIF) pathology image exploration. The lessons learned from astronomy are detailed, and the new AstroPath platform that capitalizes on these learnings is described. AstroPath is being used to generate and display tumor-immune maps that can be used for mIF immuno-oncology biomarker development. The development of AstroPath as an open resource for visualizing and analyzing large-scale spatially resolved mIF datasets is underway, akin to how publicly available maps of the sky have been used by astronomers and citizen scientists alike. Associated technical, academic, and funding considerations, as well as extended future development for inclusion of spatial transcriptomics and application of artificial intelligence, are also addressed.

摘要

天文学是最早采用大数据并利用其来描述恒星和星系之间空间关系的学科之一。如今,医学,特别是病理学,在描述细胞之间空间关系方面也有类似的需求,重点是了解肿瘤微环境的组织。本文通过 Sloan 数字巡天计划的发展,记录了数据密集型科学的出现,并描述了分析模式和方法如何同样适用于多重免疫荧光(mIF)病理学图像探索。详细介绍了天文学方面的经验教训,并描述了利用这些经验教训开发的新 AstroPath 平台。AstroPath 正被用于生成和显示肿瘤免疫图谱,可用于 mIF 免疫肿瘤生物标志物的开发。AstroPath 作为可视化和分析大规模空间分辨 mIF 数据集的开放资源正在开发中,就像天文学家和公民科学家都使用公开的天空地图一样。本文还讨论了相关的技术、学术和资金考虑因素,以及纳入空间转录组学和应用人工智能的扩展未来发展。

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