Temporal tissue dynamics from a spatial snapshot

Physiological and pathological processes such as inflammation and cancer emerge from interactions between cells over time<sup>1</sup>. However, methods to follow cell populations over time within the native context of a human tissue are lacking because a biopsy offers only a single snapshot. Here we present one-shot tissue dynamics reconstruction (OSDR), an approach to estimate a dynamical model of cell populations based on a single tissue sample. OSDR uses spatial proteomics to learn how the composition of cellular neighbourhoods influences division rate, providing a dynamical model of cell population change over time. We apply OSDR to human breast cancer data<sup>2-4</sup>, and reconstruct two fixed points of fibroblasts and macrophage interactions<sup>5,6</sup>. These fixed points correspond to hot and cold fibrosis<sup>7</sup>, in agreement with co-culture experiments that measured these dynamics directly<sup>8</sup>. We then use OSDR to discover a pulse-generating excitable circuit of T and B cells in the tumour microenvironment, suggesting temporal flares of anticancer immune responses. Finally, we study longitudinal biopsies from a triple-negative breast cancer clinical trial<sup>3</sup>, in which OSDR predicts the collapse of the tumour cell population in responders but not in non-responders, based on early-treatment biopsies. OSDR can be applied to a wide range of spatial proteomics assays to enable analysis of tissue dynamics based on patient biopsies.

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Publication Details

Journal
Nature
Published
2026-01-21
DOI
https://doi.org/10.1038/s41586-025-09876-1
Citations
2
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
44.47

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article

Temporal tissue dynamics from a spatial snapshot

Jonathan Somer, Uri Alon
2 citations
Nature
Single-cell and spatial transcriptomics
44.47
article

Temporal tissue dynamics from a spatial snapshot

Jonathan Somer, Uri Alon
article en
2 citations

Abstract

Physiological and pathological processes such as inflammation and cancer emerge from interactions between cells over time<sup>1</sup>. However, methods to follow cell populations over time within the native context of a human tissue are lacking because a biopsy offers only a single snapshot. Here we present one-shot tissue dynamics reconstruction (OSDR), an approach to estimate a dynamical model of cell populations based on a single tissue sample. OSDR uses spatial proteomics to learn how the composition of cellular neighbourhoods influences division rate, providing a dynamical model of cell population change over time. We apply OSDR to human breast cancer data<sup>2-4</sup>, and reconstruct two fixed points of fibroblasts and macrophage interactions<sup>5,6</sup>. These fixed points correspond to hot and cold fibrosis<sup>7</sup>, in agreement with co-culture experiments that measured these dynamics directly<sup>8</sup>. We then use OSDR to discover a pulse-generating excitable circuit of T and B cells in the tumour microenvironment, suggesting temporal flares of anticancer immune responses. Finally, we study longitudinal biopsies from a triple-negative breast cancer clinical trial<sup>3</sup>, in which OSDR predicts the collapse of the tumour cell population in responders but not in non-responders, based on early-treatment biopsies. OSDR can be applied to a wide range of spatial proteomics assays to enable analysis of tissue dynamics based on patient biopsies.

NatureVol. 650(8101)
Technion – Israel Institute of Technology (IL), Weizmann Institute of Science (IL)
Cancer Research UK, European Commission, Israel Academy of Sciences and Humanities
Good health and well-being
Openalex Percentile: Top 0%
Single-cell and spatial transcriptomics
44.47
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