Field–Flow–Front mapping of breast cancer evolutionary dynamics in situ

Zhang, Y.; JI, J.; Gao, M.; Wu, Z.; Wu, C.; Wang, J.; Jia, H.; Yang, Y.; Liang, L.; Li, S.; Tu, Y.; Lei, L.; Pei, Y.; Yang, H.; Luo, S.; Liu, Y.; Li, R.; Li, J.; Wang, W.

doi:10.64898/2026.06.23.733638

bioRxiv · 10.64898/2026.06.23.733638

Field–Flow–Front mapping of breast cancer evolutionary dynamics in situ

Zhang, Y.·JI, J.·Gao, M.·Wu, Z.·Wu, C.·Wang, J.·Jia, H.·Yang, Y.·Liang, L.·Li, S.·Tu, Y.·Lei, L.·Pei, Y.·Yang, H.·Luo, S.·Liu, Y.·Li, R.·Li, J.·Wang, W.

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Abstract

Tumour progression reflects not only which clones arise but where, when and in what context they expand--dimensions genotype-centred reconstructions leave unresolved. Here we reconstruct breast cancer evolution in situ across 34 Visium HD, 16 Xenium, 32 MIBI-TOF and 10 CODEX samples, serial-section 3D reconstruction, single-cell and bulk transcriptomes, and genome-wide CRISPR dependency profiles. We partition tumours into 296 cancer microzones--stroma-bounded units within which expansion is reconstructed--and define in each a Cancer Progression Metric(CPM) coupling a transcriptomic clock to expansion geometry. Projected onto tissue, CPM yields a Field-Flow-Front model rendering progression as a continuous physical process and resolving subclonal architecture into spatially coherent domains rather than predefined branches. Unexpectedly, the most advanced fronts were not the most proliferative but low-dependency, slow-cycling populations with directional expansion, driven by an extracellular matrix programme whose evolutionary force exceeded inflammation by nearly an order of magnitude yet whose genes were the least cell-autonomous. Under chemotherapy it persisted while its clonal carriers reshuffled, marking a transferable, stroma-coupled front process--not a fixed clone--as the unit of advance. Distilled into an evolutionary advantage load, this front process predicted recurrence and survival across independent cohorts and improved on conventional staging, establishing a tissue-embedded paradigm for mapping tumour evolutionary dynamics, from local fronts to patient outcome.

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Zhang, Y., JI, J., Gao, M., Wu, Z., Wu, C., Wang, J., Jia, H., Yang, Y., Liang, L., Li, S., Tu, Y., Lei, L., Pei, Y., Yang, H., Luo, S., Liu, Y., Li, R., Li, J., Wang, W.. 2026-06-23. Field–Flow–Front mapping of breast cancer evolutionary dynamics in situ. https://doi.org/10.64898/2026.06.23.733638

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