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

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.<sup>1</sup>.

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Publication Details

Journal
STAR Protocols
Published
2024-10-24
DOI
https://doi.org/10.1016/j.xpro.2024.103270
Citations
5
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.17

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article

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

Amelie Franken, Michel Bila, Diether Lambrechts
5 citations
STAR Protocols
Single-cell and spatial transcriptomics
1.17
article

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

Amelie Franken, Michel Bila, Diether Lambrechts
article en
5 citations

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.<sup>1</sup>.

STAR ProtocolsVol. 5(4)
VIB-KU Leuven Center for Cancer Biology (BE), KU Leuven (BE)
AstraZeneca, Vlaams Supercomputer Centrum, European Commission, Fonds Wetenschappelijk Onderzoek, KU Leuven, Kom op tegen Kanker, Vlaamse regering
Openalex Percentile: Top 21%
Single-cell and spatial transcriptomics
1.17
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