Cross-tissue multicellular coordination and its rewiring in cancer

The multicellular coordination that underlies tissue homeostasis and disease progression is of fundamental interest<sup>1-5</sup>. However, how diverse cell types are organized within tissue niches for cohesive functioning remains largely unknown. Here we systematically characterized cross-tissue coordinated cellular modules in healthy tissues, uncovering their spatiotemporal dynamics and phenotypic associations, and examined their rewiring in cancer. We first compiled a comprehensive single-cell transcriptomic atlas from 35 human tissues, revealing substantial inter-tissue variability in cellular composition. By leveraging covariance in cellular abundance, we identified 12 cellular modules with distinct cellular compositions, tissue prevalences and spatial organizations, and demonstrated coordinated intercellular communication within cellular modules using in situ spatial and in vivo perturbation data. Among them, two immune cellular modules in the spleen showed contrasting chronological dynamics with ageing. Analysis of multicellular changes in the breast revealed a menopausal trajectory associated with fibroblast dynamics. Furthermore, interrogation across cancer types uncovered simultaneous rewiring of two types of multicellular ecosystem during tumour progression, including the loss of tissue-specific healthy organization and the emergence of a convergent cancerous ecosystem. These findings reveal fundamental organizing principles of multicellular ecosystems in health and cancer, laying a foundation for further investigations into tissue-level functional coordination across diverse contexts.

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Publication Details

Journal
Nature
Published
2025-05-28
DOI
https://doi.org/10.1038/s41586-025-09053-4
Citations
23
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
18.54
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article

Cross-tissue multicellular coordination and its rewiring in cancer

Yihan Chen, Qiang Shi, Yang Li, Dongfang Wang et al.
23 citations
Nature
Single-cell and spatial transcriptomics
18.54
article

Cross-tissue multicellular coordination and its rewiring in cancer

Yihan Chen, Qiang Shi, Yang Li, Dongfang Wang, Zemin Zhang, Yu Yang, Shishang Qin, Linnan Zhu, Yang Gao
article en
23 citations

Abstract

The multicellular coordination that underlies tissue homeostasis and disease progression is of fundamental interest<sup>1-5</sup>. However, how diverse cell types are organized within tissue niches for cohesive functioning remains largely unknown. Here we systematically characterized cross-tissue coordinated cellular modules in healthy tissues, uncovering their spatiotemporal dynamics and phenotypic associations, and examined their rewiring in cancer. We first compiled a comprehensive single-cell transcriptomic atlas from 35 human tissues, revealing substantial inter-tissue variability in cellular composition. By leveraging covariance in cellular abundance, we identified 12 cellular modules with distinct cellular compositions, tissue prevalences and spatial organizations, and demonstrated coordinated intercellular communication within cellular modules using in situ spatial and in vivo perturbation data. Among them, two immune cellular modules in the spleen showed contrasting chronological dynamics with ageing. Analysis of multicellular changes in the breast revealed a menopausal trajectory associated with fibroblast dynamics. Furthermore, interrogation across cancer types uncovered simultaneous rewiring of two types of multicellular ecosystem during tumour progression, including the loss of tissue-specific healthy organization and the emergence of a convergent cancerous ecosystem. These findings reveal fundamental organizing principles of multicellular ecosystems in health and cancer, laying a foundation for further investigations into tissue-level functional coordination across diverse contexts.

NatureVol. 643(8071)
Shenzhen Bay Laboratory (CN), Center for Life Sciences (CN), Chongqing Medical University (CN)
Zero hunger
Openalex Percentile: Top 0%
Single-cell and spatial transcriptomics
18.54
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