Estimating the predictability of cancer evolution.

ABSTRACT:

Motivation

How predictable is the evolution of cancer? This fundamental question is of immense relevance for the diagnosis, prognosis and treatment of cancer. Evolutionary biologists have approached the question of predictability based on the underlying fitness landscape. However, empirical fitness landscapes of tumor cells are impossible to determine in vivo. Thus, in order to quantify the predictability of cancer evolution, alternative approaches are required that circumvent the need for fitness landscapes.

Results

We developed a computational method based on conjunctive Bayesian networks (CBNs) to quantify the predictability of cancer evolution directly from mutational data, without the need for measuring or estimating fitness. Using simulated data derived from >200 diffe

SUBMITTER: Hosseini SR 

PROVIDER: S-EPMC6612861 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature