Full spatio-temporal analyses of migration and colonization in evolution—dense 3D mapping of cancer metastases provides new insights
Abstract
The process of migration and colonization is important in evolution; for example, modern humans experienced multiple waves of migrations out of Africa. However, no data cover the spatio-temporal patterns sufficiently to be truly informative. Metastatic cancer provides a unique in vivo model to study these processes through rapid somatic evolution. Here, we apply the high-resolution sampling technique (Dense 3D Crypt-scale Sampling) to analyze hundreds of spatially mapped micro-samples from the primary colorectal cancer and liver metastases in two representative cases. This would be analogous to recording the "out-of-Africa" events in two repeats. Our results support that liver metastases arise from polyphyletic and polyclonal seeding events where multiple, genetically distinct clones colonize a new site together. Following colonization, these multi-clonal populations can evolve into distinct spatial architectures: segregated territories formed by cells with low motility, or highly intermixed patterns driven by high motility. The colonization (or seeding) process begins within the first third of the primary tumor's progression, creating a large number of widespread but clinically undetectable micrometastatic colonies. These findings support a model where metastatic competence is not an intrinsic trait of a single "winner" clone but an emergent property of multiple concurrent clones. Collectively, our work supports metastasis as a multi-stage process initiated early in tumor development, characterized by continuous polyclonal dissemination and the formation of spatially distinct clonal architectures. This general pattern may echo the ecology of migration and colonization in organismal evolution.
Fields of Study & Subjects
Cancer Genomics and Diagnostics
Mathematical Biology Tumor Growth
Cancer Cells and Metastasis
Publication details
- Journal / source
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Volume
- 43
- Issue
- 2
- Publication date
- 9 January 2026
- Language
- EN