TY - JOUR
T1 - Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma
AU - Walker, Brian A.
AU - Mavrommatis, Konstantinos
AU - Wardell, Christopher P.
AU - Cody Ashby, T.
AU - Bauer, Michael
AU - Davies, Faith E.
AU - Rosenthal, Adam
AU - Wang, Hongwei
AU - Qu, Pingping
AU - Hoering, Antje
AU - Samur, Mehmet
AU - Towfic, Fadi
AU - Ortiz, Maria
AU - Flynt, Erin
AU - Yu, Zhinuan
AU - Yang, Zhihong
AU - Rozelle, Dan
AU - Obenauer, John
AU - Trotter, Matthew
AU - Auclair, Daniel
AU - Keats, Jonathan
AU - Bolli, Niccolo
AU - Fulciniti, Mariateresa
AU - Szalat, Raphael
AU - Moreau, Philippe
AU - Durie, Brian
AU - Keith Stewart, A.
AU - Goldschmidt, Hartmut
AU - Raab, Marc S.
AU - Einsele, Hermann
AU - Sonneveld, Pieter
AU - Miguel, Jesus San
AU - Lonial, Sagar
AU - Jackson, Graham H.
AU - Anderson, Kenneth C.
AU - Avet-Loiseau, Herve
AU - Munshi, Nikhil
AU - Thakurta, Anjan
AU - Morgan, Gareth J.
N1 - Publisher Copyright:
© 2018 by The American Society of Hematology.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - 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.
AB - 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.
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U2 - 10.1182/blood-2018-03-840132
DO - 10.1182/blood-2018-03-840132
M3 - Article
C2 - 29884741
AN - SCOPUS:85051379277
SN - 0006-4971
VL - 132
SP - 587
EP - 597
JO - Blood
JF - Blood
IS - 6
ER -