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

Abstract

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.

Clinically relevant treatment of PDX models reveals patterns of neuroblastoma chemoresistance

“…To analyze the evolutionary trajectory of the genomic alterations across the PDX samples, DEVOLUTION ( 55 ) was used. The input is a matrix in which each row represents a genetic alteration in a particular sample, along with information about that genetic alteration’s genomic location, type of alteration, and MCF.…”

Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma

“…Spatiotemporal pro ling under chemotherapy reveals two contrasting evolutionary patterns NB is largely a copy-number aberration (CNA) driven disease [14][15][16][17][18][19][20][21] . We recently reported a software tool (DEVOLUTION) that allows integration of point mutations and CNA data, where the latter is curated according to constraints of chromosomal evolution 22 . To perform high-resolution mapping of subclone territories across anatomic tumor space, we applied DEVOLUTION to mutational data from archived para n embedded formalin-xed NB tissue (Fig.…”

Clinically-relevant treatment of PDX models reveals patterns of neuroblastoma chemoresistance

“…To analyze the evolutionary trajectory of the genomic alterations across the PDX-samples, DEVOLUTION ( 56 ) was used. The input is a matrix in which each row represents a genetic alteration in a particular sample, along with information about that genetic alteration’s genomic location, type of alteration and MCF.…”