Elements and evolutionary determinants of genomic divergence between paired primary and metastatic tumors
Fig 5
Spatial computational model verifies that the growth mode governs the dependence of M-P divergence on seeding time.
(A) Mathematical models illuminate the expected patterns of Bmd and Bp under neutral (left) and selective dynamics (right, corresponding to the second and third columns of panel B), respectively. Detailed example plots of mathematical analyses can be found in Fig 7 and S1 Appendix. The variant genealogy schema of seeding cells is also shown. (B) Virtual tumors with three representative clonal kinetics and the changing patterns of M-P divergence along with the metastatic seeding time. Upper panel: the genealogy trajectories (gray lines) of metastatic seeding cells (green dots) during the expansion of the primary tumor in a three-dimensional lattice. The Euclidean distance from a cell to the center of the lattice is shown against the fraction of the final primary tumor size when the corresponding seeding cell is born and disseminated. A cell’s distance to the center is strongly correlated with its mutation burden (S3 Fig), reflecting the spatial constraints imposed in our model. The tumor size fraction is plotted at its cube root scale to reflect the clock of actual time. Blue dots represent progenitor cells that are detectable at a frequency higher than 0.01. Middle panel: Bm is plotted against the tumor size fraction when the seeding cell disseminates, where black dots and gray bars indicate the running mean and standard deviation of Bm, respectively. Lower panel: change of Bp with different seeding time, blue dots and bars represent the running mean and standard deviation of Bp, respectively. (C) The subclonal expansion occurrence is strongly associated with drops and valleys of Bm in spatial simulations (see Methods).