A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis

Brian A. Walker(University of Arkansas for Medical Sciences), Konstantinos Mavrommatis, Christopher P. Wardell(University of Arkansas for Medical Sciences), Cody Ashby(University of Arkansas for Medical Sciences), Michael Bauer(University of Arkansas for Medical Sciences), Faith E. Davies(University of Arkansas for Medical Sciences), Adam Rosenthal(Cancer Research And Biostatistics), Hongwei Wang(Cancer Research And Biostatistics), Pingping Qu(Cancer Research And Biostatistics), Antje Hoering(Cancer Research And Biostatistics), Mehmet Samur(Harvard University), Fadi Towfic, María Ortiz, Erin Flynt, Zhinuan Yu, Zhihong Yang, Dan Rozelle(Rancho BioSciences (United States)), John C. Obenauer(Rancho BioSciences (United States)), Matthew Trotter, Daniel Auclair(Multiple Myeloma Research Foundation), Jonathan J. Keats(Translational Genomics Research Institute), Niccolò Bolli(University of Milan), Mariateresa Fulciniti(Harvard University), Raphaël Szalat(Harvard University), Philippe Moreau(Nantes Université), Brian G.M. Durie(Cedars-Sinai Medical Center), A. Keith Stewart(Mayo Clinic in Arizona), Hartmut Goldschmidt(Heidelberg University), Marc S. Raab(German Cancer Research Center), Hermann Einsele(University of Würzburg), Pieter Sonneveld(Erasmus MC Cancer Institute), Jesús F. San Miguel(Clinica Universidad de Navarra), Sagar Lonial(Emory University), Graham Jackson(Newcastle University), Kenneth C. Anderson(Harvard University), Hervé Avet‐Loiseau(Inserm), Nikhil Munshi(Harvard University), Anjan Thakurta, Gareth J. Morgan(University of Arkansas for Medical Sciences)
Leukemia
July 2, 2018
Cited by 451Open Access
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Abstract

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 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.


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