Every which way? On predicting tumor evolution using cancer progression models.

ABSTRACT: Successful prediction of the likely paths of tumor progression is valuable for diagnostic, prognostic, and treatment purposes. Cancer progression models (CPMs) use cross-sectional samples to identify restrictions in the order of accumulation of driver mutations and thus CPMs encode the paths of tumor progression. Here we analyze the performance of four CPMs to examine whether they can be used to predict the true distribution of paths of tumor progression and to estimate evolutionary unpredictability. Employing simulations we show that if fitness landscapes are single peaked (have a single fitness maximum) there is good agreement between true and predicted distributions of paths of tumor progression when sample sizes are large, but performance is poor with the currently common much smaller

SUBMITTER: Diaz-Uriarte R 

PROVIDER: S-EPMC6693785 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature