Brian A. Walker, Konstantinos Mavrommatis, Christopher P. Wardell, T. Cody Ashby, Michael Bauer, Faith 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 Auclair, Jonathan Keats, Niccolo Bolli, Mariateresa Fulciniti, Raphael Szalat, Phillipe 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 Morgan

• Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have definedPatients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.…