Blood 2018 06 08() pii 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 1,273 newly diagnosed patients with multiple myeloma we identify 63 driver genes, some of which are novel including , , , , and Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more mutations in driver genes are associated with a worse outcome, as are those with 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 , and ; t(11;14) with mutations in and ; t(14;16) with mutations in , , and ; and hyperdiploidy with gain 11q, mutations in and rearrangements. These associations indicate that the genomic landscape of myeloma is pre-determined by the primary events upon which further dependencies are built, giving rise to a non-random accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens.