Extended Data Fig. 1: Saturated model of driver advantages.
(a) Ki67 immunohistochemistry (IHC) score in patient tumour (PT) regions where a particular driver is present. (b) Schematic figure of probabilistic growth of tumour voxels, with the growth probability of a tumour voxel defined by the strongest driver. (c) A table summarising the assumed levels of growth probabilities endowed by individual drivers. (d) Whole-tumour CCF of parental and largest subclones in in-silico tumours under Volume Growth (i) and Surface Growth (ii-iii), respectively. Average fitness in a tumour slice for each simulation is presented as a heat map. Driver acquisition probabilities in these sets of simulations are \(p_{driver} = 6 \times 10^{ - 4}\) in (i), \(6 \times 10^{ - 4}\) in (ii), 1×10−3 in (iii), respectively. ‘Parental (3p loss, VHL)’ clone is shown along with up to five subclones with a whole-tumour CCF of 0.01 or higher. All remaining subclones are represented in the ‘other’ group.
