Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma

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 <i>IDH1</i>, <i>IDH2</i>, <i>HUWE1</i>, <i>KLHL6</i>, and <i>PTPN11</i> 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 <i>FGFR3</i>, <i>DIS3</i>, and <i>PRKD2</i>; t(11;14) with mutations in <i>CCND1</i> and <i>IRF4</i>; t(14;16) with mutations in <i>MAF</i>, <i>BRAF</i>, <i>DIS3</i>, and <i>ATM</i>; and hyperdiploidy with gain 11q, mutations in <i>FAM46C</i>, and <i>MYC</i> 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.