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Precise detection of cell-type-specific domains in spatial transcriptomics.
Ruan, Zhihan; Zhou, Weijun; Liu, Hong; Wei, Jinmao; Pan, Yichen; Yan, Chaoyang; Wei, Xiaoyi; Xiang, Wenting; Yan, Chengwei; Chen, Shengquan; Liu, Jian.
Afiliação
  • Ruan Z; Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300350, China.
  • Zhou W; Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China.
  • Liu H; The Second Surgical Department of Breast Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin 300060, China.
  • Wei J; Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300350, China.
  • Pan Y; Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300350, China.
  • Yan C; Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300350, China.
  • Wei X; Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China.
  • Xiang W; Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300350, China.
  • Yan C; Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300350, China.
  • Chen S; School of Mathematical Sciences, Nankai University, Tianjin 300350, China.
  • Liu J; State Key Laboratory of Medicinal Chemical Biology, College of Computer Science, Nankai University, Tianjin 300350, China. Electronic address: jianliu@nankai.edu.cn.
Cell Rep Methods ; 4(8): 100841, 2024 Aug 19.
Article em En | MEDLINE | ID: mdl-39127046
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.
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Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Microambiente Tumoral / Transcriptoma Limite: Animals / Female / Humans Idioma: En Revista: Cell Rep Methods Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Microambiente Tumoral / Transcriptoma Limite: Animals / Female / Humans Idioma: En Revista: Cell Rep Methods Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China