Fig. 2: Spatial segregation with cell mixing accelerates evolution.

a A Muller plot of tumor evolution represents genotypes color-coded by driver (k_d) value. The horizontal axis is time (cell generations), with height corresponding to genotype frequency. Descendant genotypes are shown emerging from inside their parents. b A tumor’s “realized fitness” can be quantified as the time-varying slope of the evolutionary trajectory. c Tumors evolve on the genetic (mutation burden; x-axis) and phenotypic (average drivers; y-axis) axes. For low mixing, smaller regions impose higher selection pressure, accelerating the acquisition of drivers in the population (vertical axis). Simulations are run to identical tumor size (25% of the total domain). d The domain is segregated into regions where cells disperse are allowed to mix between segregated regions at a low rate (0.01; c; left column) or high rate (0.1; e right column). e As mixing increases, tumor evolution “collapses” back onto the unsegregated single region case shown in black in (b). Snapshots are shown every 500 generations. Simulations repeated for 3 by 3 regions (f, g), 7 by 7 regions (h, i), and 11 by 11 regions (j, k). Parameters: T_p = 5 ⋅ 10⁶, T_d = 700, s_d = 0.1, s_p = 10⁻³, μ = 10⁻⁸. See attached video V3.