Protocol for whole-slide image analysis of human multiplexed tumor tissues using QuPath and R
Year: 2024
Type: article
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. 1 • Step-by-step guide for analyzing image-based spatial proteomics data • Cell segmentation and supervised phenotyping in QuPath • R scripts for calculating and visualizing intercellular distances • Compatible with various tissue types and technological platforms Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. 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.
Source: STAR Protocols
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,500
Funders: AstraZeneca, European Resuscitation Council, Vlaams Supercomputer Centrum, European Commission, Fonds Wetenschappelijk Onderzoek, KU Leuven, Vlaams Instituut voor Biotechnologie, Stichting Tegen Kanker, Kom op tegen Kanker, Vlaamse regering, Horizon 2020 Framework Programme, H2020 European Research Council
Awards: G1600813387, G2477129014, G324259913, Epigenetic and Spatial Single-cell Profiling in the context of Cancer Immunotherapy, G3992850285, G3993334097, G434337789, RESISTANCE UNDER COMBINATORIAL TREATMENT IN ER+ AND ER- BREAST CANCER., G7460206250, Integrated IMMUnoprofiling of large adaptive CANcer patients cohorts
OpenAlex ID: W4403730819