Year: 2019
Type: preprint
Study design: Observational Study
Abstract: Summary The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive classification and analysis of SVs in multiple myeloma, interrogating a large cohort of 762 patients with whole genome and RNA sequencing. We identified 100 SV hotspots involving 31 new candidate driver genes, including drug targets BCMA ( TNFRSF17 ) and SLAMF7 . Complex SVs, including chromothripsis and templated insertions, were present in 61 % of patients and frequently resulted in the simultaneous acquisition of multiple drivers. After accounting for all recurrent events, 63 % of SVs remained unexplained. Intriguingly, these rare SVs were associated with up to 7-fold enrichment for outlier gene expression, indicating that many rare driver SVs remain unrecognized and are likely important in the biology of individual tumors.
Authors: Even H Rustad, Venkata D Yellapantula, Dominik Glodzik, Kylee H Maclachlan, Benjamin Diamond, Eileen M Boyle, Cody Ashby, Patrick Blaney, Gunes Gundem, Malin Hultcrantz, Daniel Leongamornlert, Nicos Angelopoulos, Daniel Auclair, Yanming Zhang, Ahmet Dogan, Niccolò Bolli, Elli Papaemmanuil, Kenneth C. Anderson, Philippe Moreau, Herve Avet-Loiseau, Nikhil Munshi, Jonathan Keats, Peter J Campbell, Gareth J Morgan, Ola Landgren, Francesco Maura
Institutions: Memorial Sloan Kettering Cancer Center, NYU Langone’s Laura and Isaac Perlmutter Cancer Center, New York University, University of Arkansas for Medical Sciences, Wellcome Sanger Institute, University of Essex, Multiple Myeloma Research Foundation, University of Milan, Fondazione IRCCS Istituto Nazionale dei Tumori, Harvard University, Dana-Farber Cancer Institute, Centre National de la Recherche Scientifique, Inserm, Centre de Recherche en Cancérologie et Immunologie Intégrée Nantes Angers, Université de Nantes, Université d'Angers, Nantes Université, Centre de Recherches en Cancérologie de Toulouse, VA Boston Healthcare System, Translational Genomics Research Institute
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2995957854