4.8 Article

Genomic landscape and chronological reconstruction of driver events in multiple myeloma

Journal

NATURE COMMUNICATIONS
Volume 10, Issue -, Pages -

Publisher

NATURE RESEARCH
DOI: 10.1038/s41467-019-11680-1

Keywords

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Funding

  1. AIL (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS)
  2. SIES (Societa Italiana di Ematologia Sperimentale)
  3. Memorial Sloan Kettering Cancer Center NCI Core Grant [P30 CA 008748]
  4. AIRC (Associazione Italiana per la Ricerca sul Cancro) through a MFAG [17658]
  5. European Research Council under the European Union's Horizon 2020 research and innovation program [817997]
  6. Department of Veterans Affairs Merit Review Award [I01BX001584-01]
  7. NIH [P01-155258, 5P50CA100707-13]

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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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