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A practical guide for mutational signature analysis in hematological malignancies

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), c...

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Detalles Bibliográficos
Autores principales: Maura, Francesco, Degasperi, Andrea, Nadeu, Ferran, Leongamornlert, Daniel, Davies, Helen, Moore, Luiza, Royo, Romina, Ziccheddu, Bachisio, Puente, Xose S., Avet-Loiseau, Herve, Campbell, Peter J., Nik-Zainal, Serena, Campo, Elias, Munshi, Nikhil, Bolli, Niccolò
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611883/
https://www.ncbi.nlm.nih.gov/pubmed/31278357
http://dx.doi.org/10.1038/s41467-019-11037-8
Descripción
Sumario: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.