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A practical guide for mutational signature analysis in hematological malignancies

Authors :
Elias Campo
Daniel Leongamornlert
Bachisio Ziccheddu
Peter J. Campbell
Helen Davies
Nikhil C. Munshi
Andrea Degasperi
Serena Nik-Zainal
Hervé Avet-Loiseau
Niccolo Bolli
Francesco Maura
Romina Royo
Ferran Nadeu
Xose S. Puente
Luiza Moore
Degasperi, Andrea [0000-0001-6879-0596]
Moore, Luiza [0000-0001-5315-516X]
Nik-Zainal, Serena [0000-0001-5054-1727]
Apollo - University of Cambridge Repository
Barcelona Supercomputing Center
Universitat de Barcelona
Nadeu, Ferran [0000-0003-2910-9440]
Puente, Xose S. [0000-0001-9525-1483]
Source :
Nature Communications, Nature Communications, Vol 10, Iss 1, Pp 1-12 (2019), Dipòsit Digital de la UB, Universidad de Barcelona, Scopus, RUO. Repositorio Institucional de la Universidad de Oviedo, instname, Recercat. Dipósit de la Recerca de Catalunya, UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC)
Publication Year :
2019

Abstract

Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.<br />Mutational signature analysis provides important information about the mutational processes underpinning different stages of tumorigenesis. Here, the authors compare publicly available signature extraction tools and suggest a framework for the generation of accurate and reproducible signature data.

Details

ISSN :
20411723
Database :
OpenAIRE
Journal :
Nature Communications
Accession number :
edsair.doi.dedup.....83fc151ad8809d65370630f5b832efd8
Full Text :
https://doi.org/10.1038/s41467-019-11037-8