Mutations driving CLL and their evolution in progression and relapse Journal Article

Author(s): Landau, Dan A; Tausch, Eugen; Taylor-Weiner, Amaro N; Stewart, Chip N; Reiter, Johannes G; Bahlo, Jasmin; Kluth, Sandra; Božić, Ivana; Lawrence, Michael S; Böttcher, Sebastian; Carter, Scott L; Cibulskis, Kristian; Mertens, Daniel J; Sougnez, Carrie L; Rosenberg, Mara W; Hess, Julian M; Edelmann, Jennifer; Kless, Sabrina; Kneba, Michael; Ritgen, Matthias; Fink, Anna M; Fischer, Kirsten; Gabriel, Stacey B; Lander, Eric S; Nowak, Martin A; Döhner, Hartmut; Hallek, Michael J; Neuberg, Donna S; Getz, Gad A; Stilgenbauer, Stephan; Wu, Catherine J
Article Title: Mutations driving CLL and their evolution in progression and relapse
Affiliation IST Austria
Abstract: Which genetic alterations drive tumorigenesis and how they evolve over the course of disease and therapy are central questions in cancer biology. Here we identify 44 recurrently mutated genes and 11 recurrent somatic copy number variations through whole-exome sequencing of 538 chronic lymphocytic leukaemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized putative cancer drivers (RPS15, IKZF3), and collectively identify RNA processing and export, MYC activity, and MAPK signalling as central pathways involved in CLL. Clonality analysis of this large data set further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pre-treatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution. Thus, large sequencing data sets of clinically informative samples enable the discovery of novel genes associated with cancer, the network of relationships between the driver events, and their impact on disease relapse and clinical outcome.
Journal Title: Nature
Volume: 526
Issue 7574
ISSN: 0028-0836
Publisher: Nature Publishing Group  
Date Published: 2015-10-22
Start Page: 525
End Page: 530
DOI: 10.1038/nature15395
Notes: J.G.R. was supported by the European Research Council (ERC) start grant 279307: Graph Games, Austrian Science Fund (FWF) grant no. P23499-N23, and FWF NFN grant no S11407-N23 RiSE.
Open access: no