Inferring parameters of cancer evolution in chronic lymphocytic leukemia.

ABSTRACT: As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer, where two longitudinal samples are available for sequencing. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occu

SUBMITTER: Lee ND 

PROVIDER: S-EPMC9668150 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature