Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma

Brian A. Walker, Konstantinos Mavrommatis, Christopher P. Wardell, T. Cody Ashby, Michael Bauer, Faith E. Davies, Adam Rosenthal, Hongwei Wang, Pingping Qu, Antje Hoering, Mehmet Samur, Fadi Towfic, Maria Ortiz, Erin Flynt, Zhinuan Yu, Zhihong Yang, Dan Rozelle, John Obenauer, Matthew Trotter, Daniel AuclairJonathan Keats, Niccolo Bolli, Mariateresa Fulciniti, Raphael Szalat, Philippe Moreau, Brian Durie, A. Keith Stewart, Hartmut Goldschmidt, Marc S. Raab, Hermann Einsele, Pieter Sonneveld, Jesus San Miguel, Sagar Lonial, Graham H. Jackson, Kenneth C. Anderson, Herve Avet-Loiseau, Nikhil Munshi, Anjan Thakurta, Gareth J. Morgan

Research output: Contribution to journalArticle

80 Scopus citations

Abstract

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1273 newly diagnosed patients with MM, we identified 63 driver genes, some of which are novel, including IDH1, IDH2, HUWE1, KLHL6, and PTPN11. Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more driver gene abnormalities are associated with worse outcomes, as are identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in FGFR3, DIS3, and PRKD2; t(11;14) with mutations in CCND1 and IRF4; t(14;16) with mutations in MAF, BRAF, DIS3, and ATM; and hyperdiploidy with gain 11q, mutations in FAM46C, and MYC rearrangements. These associations indicate that the genomic landscape of myeloma is predetermined by the primary events upon which further dependencies are built, giving rise to a nonrandom accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens.

Original languageEnglish (US)
Pages (from-to)587-597
Number of pages11
JournalBlood
Volume132
Issue number6
DOIs
StatePublished - Aug 9 2018

ASJC Scopus subject areas

  • Biochemistry
  • Immunology
  • Hematology
  • Cell Biology

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  • Cite this

    Walker, B. A., Mavrommatis, K., Wardell, C. P., Cody Ashby, T., Bauer, M., Davies, F. E., Rosenthal, A., Wang, H., Qu, P., Hoering, A., Samur, M., Towfic, F., Ortiz, M., Flynt, E., Yu, Z., Yang, Z., Rozelle, D., Obenauer, J., Trotter, M., ... Morgan, G. J. (2018). Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma. Blood, 132(6), 587-597. https://doi.org/10.1182/blood-2018-03-840132