Temporal tissue dynamics from a spatial snapshot.

Somer, Jonathan; Mannor, Shie; Alon, Uri · Nature · 2026

basic_science · Level V

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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.

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