Inferring clonal evolution of tumors from single nucleotide somatic
mutations
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by
Wei Jiao, Shankar Vembu, Amit G. Deshwar, Lincoln Stein, Quaid Morris
2013
Abstract
High-throughput sequencing allows the detection and quantification of
frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor
cell populations. In some cases, the evolutionary history and population
frequency of the subclonal lineages of tumor cells present in the sample can be
reconstructed from these SNV frequency measurements. However, automated methods
to do this reconstruction are not available and the conditions under which
reconstruction is possible have not been described.
We describe the conditions under which the evolutionary history can be
uniquely reconstructed from SNV frequencies from single or multiple samples
from the tumor population and we introduce a new statistical model, PhyloSub,
that infers the phylogeny and genotype of the major subclonal lineages
represented in the population of cancer cells. It uses a Bayesian nonparametric
prior over trees that groups SNVs into major subclonal lineages and
automatically estimates the number of lineages and their ancestry. We sample
from the joint posterior distribution over trees to identify evolutionary
histories and cell population frequencies that have the highest probability of
generating the observed SNV frequency data. When multiple phylogenies are
consistent with a given set of SNV frequencies, PhyloSub represents the
uncertainty in the tumor phylogeny using a partial order plot. Experiments on a
simulated dataset and two real datasets comprising tumor samples from acute
myeloid leukemia and chronic lymphocytic leukemia patients demonstrate that
PhyloSub can infer both linear (or chain) and branching lineages and its
inferences are in good agreement with ground truth, where it is available.
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