Precise detection of cell-type-specific domains in spatial transcriptomics

Cell-type-specific domains are the anatomical domains in spatially resolved transcriptome (SRT) tissues where particular cell types are enriched coincidentally. It is challenging to use existing computational methods to detect specific domains with low-proportion cell types, which are partly overlapped with or even inside other cell-type-specific domains. Here, we propose De-spot, which synthesizes segmentation and deconvolution as an ensemble to generate cell-type patterns, detect low-proportion cell-type-specific domains, and display these domains intuitively. Experimental evaluation showed that De-spot enabled us to discover the co-localizations between cancer-associated fibroblasts and immune-related cells that indicate potential tumor microenvironment (TME) domains in given slices, which were obscured by previous computational methods. We further elucidated the identified domains and found that Srgn may be a critical TME marker in SRT slices. By deciphering T cell-specific domains in breast cancer tissues, De-spot also revealed that the proportions of exhausted T cells were significantly increased in invasive vs. ductal carcinoma.

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Publication Details

Journal
Cell Reports Methods
Published
2024-08-01
DOI
https://doi.org/10.1016/j.crmeth.2024.100841
Citations
5
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.17
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article

Precise detection of cell-type-specific domains in spatial transcriptomics

Xiaoyi Wei, Chaoyang Yan, Jinmao Wei, Yichen Pan et al.
5 citations
Cell Reports Methods
Single-cell and spatial transcriptomics
1.17
article

Precise detection of cell-type-specific domains in spatial transcriptomics

Xiaoyi Wei, Chaoyang Yan, Jinmao Wei, Yichen Pan, Shengquan Chen, Wenting Xiang, Zhihan Ruan, Zhihong Liu, Jian Liu, Weijun Zhou, Chengwei Yan
article en
5 citations

Abstract

Cell-type-specific domains are the anatomical domains in spatially resolved transcriptome (SRT) tissues where particular cell types are enriched coincidentally. It is challenging to use existing computational methods to detect specific domains with low-proportion cell types, which are partly overlapped with or even inside other cell-type-specific domains. Here, we propose De-spot, which synthesizes segmentation and deconvolution as an ensemble to generate cell-type patterns, detect low-proportion cell-type-specific domains, and display these domains intuitively. Experimental evaluation showed that De-spot enabled us to discover the co-localizations between cancer-associated fibroblasts and immune-related cells that indicate potential tumor microenvironment (TME) domains in given slices, which were obscured by previous computational methods. We further elucidated the identified domains and found that Srgn may be a critical TME marker in SRT slices. By deciphering T cell-specific domains in breast cancer tissues, De-spot also revealed that the proportions of exhausted T cells were significantly increased in invasive vs. ductal carcinoma.

Cell Reports MethodsVol. 4(8)
Sun Yat-sen University (CN), Nankai University (CN), Tianjin Medical University Cancer Institute and Hospital (CN), Fifth Affiliated Hospital of Sun Yat-sen University (CN), Zhujiang Hospital (CN), Southern Medical University (CN)
Openalex Percentile: Top 22%
Single-cell and spatial transcriptomics
1.17
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