QuantumClone: clonal assessment of functional mutations in cancer based on a genotype-aware method for clonal reconstruction
Year: 2018
Type: article
Abstract: Motivation: In cancer, clonal evolution is assessed based on information coming from single nucleotide variants and copy number alterations. Nonetheless, existing methods often fail to accurately combine information from both sources to truthfully reconstruct clonal populations in a given tumor sample or in a set of tumor samples coming from the same patient. Moreover, previously published methods detect clones from a single set of variants. As a result, compromises have to be done between stringent variant filtering [reducing dispersion in variant allele frequency estimates (VAFs)] and using all biologically relevant variants. Results: We present a framework for defining cancer clones using most reliable variants of high depth of coverage and assigning functional mutations to the detected clones. The key element of our framework is QuantumClone, a method for variant clustering into clones based on VAFs, genotypes of corresponding regions and information about tumor purity. We validated QuantumClone and our framework on simulated data. We then applied our framework to whole genome sequencing data for 19 neuroblastoma trios each including constitutional, diagnosis and relapse samples. We confirmed an enrichment of damaging variants within such pathways as MAPK (mitogen-activated protein kinases), neuritogenesis, epithelial-mesenchymal transition, cell survival and DNA repair. Most pathways had more damaging variants in the expanding clones compared to shrinking ones, which can be explained by the increased total number of variants between these two populations. Functional mutational rate varied for ancestral clones and clones shrinking or expanding upon treatment, suggesting changes in clone selection mechanisms at different time points of tumor evolution. Availability and implementation: Source code and binaries of the QuantumClone R package are freely available for download at https://CRAN.R-project.org/package=QuantumClone. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Source: Bioinformatics
Authors: Paul Deveau, Leo Colmet Daage, Derek Oldridge, Virginie Bernard, Angela Bellini, Mathieu Chicard, Nathalie Clement, Eve Lapouble, Valerie Combaret, Anne Boland, Vincent Meyer, Jean-Francois Deleuze, Isabelle Janoueix-Lerosey, Emmanuel Barillot, Olivier Delattre, John M Maris, Gudrun Schleiermacher, Valentina Boeva
Institutions: Université Paris-Sud, Inserm, Université Paris Sciences et Lettres, École Nationale Supérieure des Mines de Paris, Institut Curie, Children's Hospital of Philadelphia, University of Pennsylvania, Centre Léon Bérard, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Centre National de Recherche en Génomique Humaine, Institut de biologie François Jacob, La Ligue Contre le Cancer, Centre National de la Recherche Scientifique, Institut Cochin, Université Paris Descartes
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $2,588
Funders: Annenberg Foundation, Worldwide Cancer Research, Children’s Oncology Group, Agence Nationale de la Recherche, Fondation ARC pour la Recherche sur le Cancer, Institut National Du Cancer, Fondation Nelia et Amadeo Barletta, Direction Générale de l’offre de Soins, National Institutes of Health, National Cancer Institute, National Institute on Minority Health and Health Disparities
Awards: G1145202234, G1592728031, Identifying Strategies to Increase Engagement in Clinical Trials in Pediatric SCD, G2247820705, G236362872, G2579310621, G2807974981, G304773848, Determinants de l'Identité : de la molécule à l'individu, G3503792436, G386607036, G3898041522, G454707396, G4599119665, G4774453313, G4866930200, G6233551980, G7240651115, G7873813289, G7999552054, Université Sorbonne Paris Cité, G860380395, G9000211056, G9000297332
OpenAlex ID: W2782970566