Abstract
The utility of intratumour heterogeneity as a prognostic biomarker is the subject ofongoing clinical investigation. However, the relationship between this marker and itsclinical impact is mediated by an evolutionary process that is not well understood.Here, we employ a spatial computational model of tumour evolution to assess when,why and how intratumour heterogeneity can be used to forecast tumour growthrate and progression-free survival. We identify three conditions that can lead to apositive correlation between clonal diversity and subsequent growth rate: diversityis measured early in tumour development; selective sweeps are rare; and/or tumoursvary in the rate at which they acquire driver mutations. Opposite conditions typicallylead to negative correlation. In cohorts of tumours with diverse evolutionaryparameters, we find that clonal diversity is a reliable predictor of both growth rateand progression-free survival. We thus offer explanations—grounded in evolutionarytheory—for empirical findings in various cancers, including survival analyses reportedin the recent TRACERx Renal study of clear-cell renal cell carcinoma. Our work informsthe search for new prognostic biomarkers and contributes to the developmentof predictive oncology.