DEVOLUTION-A method for phylogenetic reconstruction of aneuploid cancers based on multiregional genotyping data

Natalie Andersson et al. present DEVOLUTION, an algorithm and tool that allows researchers to reconstruct tumor clonal lineages from copy number and/or sequencing data. They validate this method on a diverse cohort of pediatric cancers, demonstrating its potential applications for cancer research. Phylogenetic reconstruction of cancer cell populations remains challenging. There is a particular lack of tools that deconvolve clones based on copy number aberration analyses of multiple tumor biopsies separated in time and space from the same patient. This has hampered investigations of tumors rich in aneuploidy but few point mutations, as in many childhood cancers and high-risk adult cancer. Here, we present DEVOLUTION, an algorithm for subclonal deconvolution followed by phylogenetic reconstruction from bulk genotyping data. It integrates copy number and sequencing information across multiple tumor regions throughout the inference process, provided that the mutated clone fraction for each mutation is known. We validate DEVOLUTION on data from 56 pediatric tumors comprising 253 tumor biopsies and show a robust performance on simulations of bulk genotyping data. We also benchmark DEVOLUTION to similar bioinformatic tools using an external dataset. DEVOLUTION holds the potential to facilitate insights into the development, progression, and response to treatment, particularly in tumors with high burden of chromosomal copy number alterations.

Automated summary

The study introduces an algorithm and tool called DEVOLUTION that enables researchers to reconstruct tumor clonal lineages from diverse pediatric cancers, demonstrating its potential applications for cancer research.