Inferring clonal evolution of tumors from single nucleotide somatic mutations
Wei Jiao, Shankar Vembu, Amit G. Deshwar, Lincoln Stein, Quaid Morris

TL;DR
This paper introduces PhyloSub, a Bayesian nonparametric model that reconstructs tumor evolutionary history from somatic SNV data, enabling insights into subclonal lineages and their relationships.
Contribution
It provides a novel statistical framework for inferring tumor phylogeny from SNV frequencies, including conditions for unique reconstruction and uncertainty representation.
Findings
Successfully infers linear and branching tumor lineages
Accurately estimates subclonal population frequencies
Demonstrates effectiveness on real leukemia datasets
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…
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Taxonomy
TopicsCancer Genomics and Diagnostics · Genetic factors in colorectal cancer · Evolution and Genetic Dynamics
