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使用QuPath和R对人类多重肿瘤组织进行全切片图像分析的方案。

Protocol for whole-slide image analysis of human multiplexed tumor tissues using QuPath and R.

作者信息

Franken Amelie, Bila Michel, Lambrechts Diether

机构信息

Laboratory for Translational Genetics, VIB-KU Leuven Center for Cancer Biology, 3000 Leuven, Belgium.

Laboratory of Experimental Oncology, Department of Oncology, KU Leuven, UZ Leuven, 3000 Leuven, Belgium.

出版信息

STAR Protoc. 2024 Dec 20;5(4):103270. doi: 10.1016/j.xpro.2024.103270. Epub 2024 Oct 24.

Abstract

The spatial organization of cells within tissues aids in understanding physiological and pathological processes, as well as elucidating the mechanisms of action underlying treatments. We present a protocol for analyzing image-based spatial proteomics data. To illustrate, we focus on whole-slide images of human multiplexed tumor tissues acquired using the PhenoCycler-Fusion 2.0 platform from Akoya Biosciences. We describe steps for cell segmentation, cell phenotyping, intercellular distance calculation, and data visualization. For complete details on the use and execution of this protocol, please refer to Franken et al..

摘要

组织内细胞的空间组织有助于理解生理和病理过程,以及阐明治疗背后的作用机制。我们提出了一种分析基于图像的空间蛋白质组学数据的方案。为了说明这一点,我们重点关注使用Akoya Biosciences公司的PhenoCycler-Fusion 2.0平台获取的人类多重肿瘤组织的全切片图像。我们描述了细胞分割、细胞表型分析、细胞间距离计算和数据可视化的步骤。有关本方案使用和执行的完整详细信息,请参阅Franken等人的文献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b78/11541771/31bea8ce050a/fx1.jpg

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