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CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data.
Kim, Hyobin; Kumar, Amit; Lövkvist, Cecilia; Palma, António M; Martin, Patrick; Kim, Junil; Bhoopathi, Praveen; Trevino, Jose; Fisher, Paul; Madan, Esha; Gogna, Rajan; Won, Kyoung Jae.
Afiliación
  • Kim H; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA.
  • Kumar A; Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
  • Lövkvist C; Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA.
  • Palma AM; School of Medicine, Institute of Molecular Medicine, Virginia Commonwealth University, Richmond, VA, USA.
  • Martin P; Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.
  • Kim J; Novo Nordisk Foundation Center for Stem Cell Medicine, reNEW, University of Copenhagen, Copenhagen, Denmark.
  • Bhoopathi P; Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA.
  • Trevino J; School of Medicine, Institute of Molecular Medicine, Virginia Commonwealth University, Richmond, VA, USA.
  • Fisher P; Instituto Superior Tecnico, Universidade de Lisboa, Lisboa, Portugal.
  • Madan E; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA.
  • Gogna R; Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
  • Won KJ; School of Systems Biomedical Science, Soongsil University, Seoul, Korea.
Mol Syst Biol ; 19(11): e11670, 2023 Nov 09.
Article en En | MEDLINE | ID: mdl-37815040
ABSTRACT
Cells have evolved their communication methods to sense their microenvironments and send biological signals. In addition to communication using ligands and receptors, cells use diverse channels including gap junctions to communicate with their immediate neighbors. Current approaches, however, cannot effectively capture the influence of various microenvironments. Here, we propose a novel approach to investigate cell neighbor-dependent gene expression (CellNeighborEX) in spatial transcriptomics (ST) data. To categorize cells based on their microenvironment, CellNeighborEX uses direct cell location or the mixture of transcriptome from multiple cells depending on ST technologies. For each cell type, CellNeighborEX identifies diverse gene sets associated with partnering cell types, providing further insight. We found that cells express different genes depending on their neighboring cell types in various tissues including mouse embryos, brain, and liver cancer. Those genes are associated with critical biological processes such as development or metastases. We further validated that gene expression is induced by neighboring partners via spatial visualization. The neighbor-dependent gene expression suggests new potential genes involved in cell-cell interactions beyond what ligand-receptor co-expression can discover.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Transcriptoma / Neoplasias Hepáticas Límite: Animals Idioma: En Revista: Mol Syst Biol Asunto de la revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Transcriptoma / Neoplasias Hepáticas Límite: Animals Idioma: En Revista: Mol Syst Biol Asunto de la revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos