Abstract
BackgroundHigh-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. But automated methods to do this reconstruction are not available and the conditions under which reconstruction is possible have not been described.ResultsWe 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.ConclusionsPhyloSub can be applied to frequencies of any “binary” somatic mutation, including SNVs as well as small insertions and deletions. The PhyloSub and partial order plot software is available from https://github.com/morrislab/phylosub/.
Highlights
High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations
We provide software that takes as input a set of read counts for a set of SNVs and the copy number status of each SNV, performs inference in the PhlyoSub model to estimate the number of major subclonal lineages, the mutational profile of each lineage, and the proportion of each lineage within the tumor cell population from which the read data was drawn
A subclonal lineage contains all of the SNVs associated with its parent, so its full genotype can be reconstructed by taking the union of the SNVs associated with its node and all of its ancestral nodes
Summary
High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations. Recent attempts to reconstruct subclonal phylogenies have employed much deeper targeted sequencing [15] of tumor-associated single nucleotide variants (SNVs) to achieve higher accuracy in estimated SNV frequencies [9,10,16,17]. These SNV frequencies were used to partially reconstruct the evolutionary history of tumors based on a single [10,16] or multiple [9] samples of same tumor. If one makes the infinite sites assumption about tumor evolution, namely that every SNV only appeared once, it is possible to use SNV frequencies to automatically reconstruct full or partial subclonal phylogenies while inferring the multiple SNV genotypes of the major subclonal lineages in the tumor
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