Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma

Walker BA, Mavrommatis K, Wardell CP, Ashby TC, Bauer M, Davies FE, 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, Auclair D, Keats J, Bolli N, Fulciniti M, Szalat R, Moreau P, Durie B, Stewart AK, Goldschmidt H, Raab MS, Einsele H, Sonneveld P, San Miguel J, Lonial S, Jackson GH, Anderson KC, Avet-Loiseau H, Munshi N, Thakurta A, Morgan GJ (2018)

Publication Type: Journal article

Publication year: 2018

Journal

Book Volume: 132

Pages Range: 587-597

Journal Issue: 6

DOI: 10.1182/blood-2018-03-840132

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.

Involved external institutions

University of Arkansas United States (USA) (US) Celgene Corporation United States (USA) (US) Harvard University United States (USA) (US) Celgene Institute for Translational Research Europe (CITRE) Spain (ES) Rancho BioSciences United States (USA) (US) Multiple Myeloma Research Foundation (MMRF) United States (USA) (US) City of Hope Medical Center United States (USA) (US) Università degli studi di Milano Italy (IT) Université de Nantes France (FR) Samuel Oschin Comprehensive Cancer Institute United States (USA) (US) Mayo Clinic United States (USA) (US) Universitätsklinikum Heidelberg Germany (DE) Julius-Maximilians-Universität Würzburg Germany (DE) Erasmus University Medical Center (MC) Netherlands (NL) Clínica Universidad de Navarra Spain (ES) Emory University United States (USA) (US) Newcastle University United Kingdom (GB) National Institute for Health and Medical Research / Institut national de la santé et de la recherche médicale (INSERM) France (FR)

How to cite

APA:

Walker, B.A., Mavrommatis, K., Wardell, C.P., Ashby, T.C., Bauer, M., Davies, F.E.,... 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

MLA:

Walker, Brian A., et al. "Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma." Blood 132.6 (2018): 587-597.

BibTeX: Download