SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication
Abstract Background Cellular communication is vital for the proper functioning of multicellular organisms. A comprehensive analysis of cellular communication demands the consideration not only of the binding between ligands and receptors but also of a series of downstream signal transduction reactio...
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| Format: | Article |
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BMC
2025-02-01
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| Series: | BMC Biology |
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| Online Access: | https://doi.org/10.1186/s12915-025-02141-x |
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| author | Jingtao Liu Litian Ma Fen Ju Chenguang Zhao Liang Yu |
| author_facet | Jingtao Liu Litian Ma Fen Ju Chenguang Zhao Liang Yu |
| author_sort | Jingtao Liu |
| collection | DOAJ |
| description | Abstract Background Cellular communication is vital for the proper functioning of multicellular organisms. A comprehensive analysis of cellular communication demands the consideration not only of the binding between ligands and receptors but also of a series of downstream signal transduction reactions within cells. Thanks to the advancements in spatial transcriptomics technology, we are now able to better decipher the process of cellular communication within the cellular microenvironment. Nevertheless, the majority of existing spatial cell–cell communication algorithms fail to take into account the downstream signals within cells. Results In this study, we put forward SpaCcLink, a cell–cell communication analysis method that takes into account the downstream influence of individual receptors within cells and systematically investigates the spatial patterns of communication as well as downstream signal networks. Analyses conducted on real datasets derived from humans and mice have demonstrated that SpaCcLink can help in identifying more relevant ligands and receptors, thereby enabling us to systematically decode the downstream genes and signaling pathways that are influenced by cell–cell communication. Comparisons with other methods suggest that SpaCcLink can identify downstream genes that are more closely associated with biological processes and can also discover reliable ligand-receptor relationships. Conclusions By means of SpaCcLink, a more profound and all-encompassing comprehension of the mechanisms underlying cellular communication can be achieved, which in turn promotes and deepens our understanding of the intricate complexity within organisms. |
| format | Article |
| id | doaj-art-6578dacf4f8f4bc6bf8543b97bc909ca |
| institution | OA Journals |
| issn | 1741-7007 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Biology |
| spelling | doaj-art-6578dacf4f8f4bc6bf8543b97bc909ca2025-08-20T02:12:59ZengBMCBMC Biology1741-70072025-02-0123111510.1186/s12915-025-02141-xSpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communicationJingtao Liu0Litian Ma1Fen Ju2Chenguang Zhao3Liang Yu4School of Computer Science and Technology, Xidian UniversitySchool of Computer Science and Technology, Xidian UniversityDepartment of Rehabilitation Medicine, Xijing Hospital, Fourth Military Medical UniversityDepartment of Rehabilitation Medicine, Xijing Hospital, Fourth Military Medical UniversitySchool of Computer Science and Technology, Xidian UniversityAbstract Background Cellular communication is vital for the proper functioning of multicellular organisms. A comprehensive analysis of cellular communication demands the consideration not only of the binding between ligands and receptors but also of a series of downstream signal transduction reactions within cells. Thanks to the advancements in spatial transcriptomics technology, we are now able to better decipher the process of cellular communication within the cellular microenvironment. Nevertheless, the majority of existing spatial cell–cell communication algorithms fail to take into account the downstream signals within cells. Results In this study, we put forward SpaCcLink, a cell–cell communication analysis method that takes into account the downstream influence of individual receptors within cells and systematically investigates the spatial patterns of communication as well as downstream signal networks. Analyses conducted on real datasets derived from humans and mice have demonstrated that SpaCcLink can help in identifying more relevant ligands and receptors, thereby enabling us to systematically decode the downstream genes and signaling pathways that are influenced by cell–cell communication. Comparisons with other methods suggest that SpaCcLink can identify downstream genes that are more closely associated with biological processes and can also discover reliable ligand-receptor relationships. Conclusions By means of SpaCcLink, a more profound and all-encompassing comprehension of the mechanisms underlying cellular communication can be achieved, which in turn promotes and deepens our understanding of the intricate complexity within organisms.https://doi.org/10.1186/s12915-025-02141-xSpatial transcriptomeCell–cell communicationDownstream pathwaysCommunication patterns |
| spellingShingle | Jingtao Liu Litian Ma Fen Ju Chenguang Zhao Liang Yu SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication BMC Biology Spatial transcriptome Cell–cell communication Downstream pathways Communication patterns |
| title | SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication |
| title_full | SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication |
| title_fullStr | SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication |
| title_full_unstemmed | SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication |
| title_short | SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell–cell communication |
| title_sort | spacclink exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell cell communication |
| topic | Spatial transcriptome Cell–cell communication Downstream pathways Communication patterns |
| url | https://doi.org/10.1186/s12915-025-02141-x |
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