Genomic landscape and chronological reconstruction of driver events in multiple myeloma

Francesco Maura(Memorial Sloan Kettering Cancer Center), Niccolò Bolli(University of Milan), Nicos Angelopoulos(University of Essex), Kevin J. Dawson(Wellcome Sanger Institute), Daniel Leongamornlert(Wellcome Sanger Institute), Iñigo Martincorena(Wellcome Sanger Institute), Thomas J. Mitchell(Wellcome Sanger Institute), Anthony Fullam(Wellcome Sanger Institute), Santiago González(European Bioinformatics Institute), Raphaël Szalat(Harvard University), Federico Abascal(Wellcome Sanger Institute), Bernardo Rodríguez–Martín(Universidade de Santiago de Compostela), Mehmet Samur(Harvard University), Dominik Głodzik(Memorial Sloan Kettering Cancer Center), Marco Roncador(Wellcome Sanger Institute), Mariateresa Fulciniti(Harvard University), Yu Tai(Harvard University), Stéphane Minvielle(Centre National de la Recherche Scientifique), Florence Magrangeas(Centre National de la Recherche Scientifique), Philippe Moreau(Centre National de la Recherche Scientifique), Paolo Corradini(University of Milan), Kenneth C. Anderson(Harvard University), José M. C. Tubío(Universidade de Santiago de Compostela), David C. Wedge(Open Data Institute), Moritz Gerstung(European Bioinformatics Institute), Hervé Avet‐Loiseau(Inserm), Nikhil C. Munshi(Harvard University), Peter J. Campbell(Wellcome Sanger Institute)
Nature Communications
August 23, 2019
Cited by 271Open Access
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Abstract

The multiple myeloma (MM) genome is heterogeneous and evolves through preclinical and post-diagnosis phases. Here we report a catalog and hierarchy of driver lesions using sequences from 67 MM genomes serially collected from 30 patients together with public exome datasets. Bayesian clustering defines at least 7 genomic subgroups with distinct sets of co-operating events. Focusing on whole genome sequencing data, complex structural events emerge as major drivers, including chromothripsis and a novel replication-based mechanism of templated insertions, which typically occur early. Hyperdiploidy also occurs early, with individual trisomies often acquired in different chronological windows during evolution, and with a preferred order of acquisition. Conversely, positively selected point mutations, whole genome duplication and chromoplexy events occur in later disease phases. Thus, initiating driver events, drawn from a limited repertoire of structural and numerical chromosomal changes, shape preferred trajectories of evolution that are biologically relevant but heterogeneous across patients.


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