학술논문

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma
Document Type
Report
Source
Cell. Oct 5, 2017, Vol. 171 Issue 2, 481
Subject
Lymphomas -- Analysis
Automobile drivers -- Analysis
Biological sciences
Language
English
ISSN
0092-8674
Abstract
To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1016/j.cell.2017.09.027 Byline: Anupama Reddy (1,2,22), Jenny Zhang (1,2,22), Nicholas S. Davis (1,22), Andrea B. Moffitt (1,22), Cassandra L. Love (1), Alexander Waldrop (1), Sirpa Leppa (3), Annika Pasanen (3), Leo Meriranta (3), Marja-Liisa Karjalainen-Lindsberg (3), Peter Norgaard (4), Mette Pedersen (4), Anne O. Gang (4), Estrid Hogdall (4), Tayla B. Heavican (5), Waseem Lone (5), Javeed Iqbal (5), Qiu Qin (1), Guojie Li (1), So Young Kim (1), Jane Healy (1), Kristy L. Richards (6), Yuri Fedoriw (6), Leon Bernal-Mizrachi (7), Jean L. Koff (7), Ashley D. Staton (7), Christopher R. Flowers (7), Ora Paltiel (8), Neta Goldschmidt (8), Maria Calaminici (9), Andrew Clear (9), John Gribben (9), Evelyn Nguyen (10), Magdalena B. Czader (10), Sarah L. Ondrejka (11), Angela Collie (11), Eric D. Hsi (11), Eric Tse (12), Rex K.H. Au-Yeung (12), Yok-Lam Kwong (12), Gopesh Srivastava (12), William W.L. Choi (12), Andrew M. Evens (13), Monika Pilichowska (13), Manju Sengar (14), Nishitha Reddy (15), Shaoying Li (16), Amy Chadburn (17), Leo I. Gordon (18), Elaine S. Jaffe (19), Shawn Levy (20), Rachel Rempel (1), Tiffany Tzeng (1), Lanie E. Happ (1), Tushar Dave (1), Deepthi Rajagopalan (1), Jyotishka Datta (1), David B. Dunson (21), Sandeep S. Dave [sandeep.dave@duke.edu] (1,2,23,*) Keywords exome sequencing; genetic mutations; diffuse large B cell lymphoma; DLBCL; TCGA; The Cancer Genome Atlas Highlights * Exome sequencing in 1,001 DLBCL patients comprehensively identifies 150 driver genes * Unbiased CRISPR screen in DLBCL cell lines identifies essential oncogenes * Integrative analysis connects genomics, CRISPR hits, and clinical outcome * A genomic risk model of survival outperforms existing risk-assessment methods Summary Diffuse large B cell lymphoma (DLBCL) is the most common form of blood cancer and is characterized by a striking degree of genetic and clinical heterogeneity. This heterogeneity poses a major barrier to understanding the genetic basis of the disease and its response to therapy. Here, we performed an integrative analysis of whole-exome sequencing and transcriptome sequencing in a cohort of 1,001 DLBCL patients to comprehensively define the landscape of 150 genetic drivers of the disease. We characterized the functional impact of these genes using an unbiased CRISPR screen of DLBCL cell lines to define oncogenes that promote cell growth. A prognostic model comprising these genetic alterations outperformed current established methods: cell of origin, the International Prognostic Index comprising clinical variables, and dual MYC and BCL2 expression. These results comprehensively define the genetic drivers and their functional roles in DLBCL to identify new therapeutic opportunities in the disease. Author Affiliation: (1) Duke Cancer Institute and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA (2) Department of Medicine, Duke University Medical Center, Durham, NC, USA (3) Helsinki University Hospital Cancer Center and University of Helsinki, Helsinki, Finland (4) Herlev and Gentofte Hospital, Copenhagen University, Herlev, Denmark (5) Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA (6) Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC, USA (7) Winship Cancer Institute, Emory University, Atlanta, GA, USA (8) Hadassah-Hebrew University Medical Center, Jerusalem, Israel (9) Barts Cancer Institute of Queen Mary University of London, London, UK (10) Pathology, Indiana University, Indianapolis, IN, USA (11) Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA (12) Queen Mary Hospital, University of Hong Kong, Hong Kong (13) Tufts University Medical Center, Boston, MA, USA (14) Tata Memorial Center, Mumbai, India (15) Vanderbilt University Medical Center, Nashville, TN, USA (16) MD Anderson Cancer Center, Houston, TX, USA (17) Columbia-Presbyterian Hospital, New York, NY, USA (18) Northwestern University Medical School, Chicago, IL, USA (19) National Cancer Institute, Bethesda, MD, USA (20) Hudson Alpha Institute for Biotechnology, Huntsville, AL, USA (21) Department of Statistical Science, Duke University, Durham, NC, USA * Corresponding author Article History: Received 31 July 2017; Revised 5 September 2017; Accepted 18 September 2017 (miscellaneous) Published: October 5, 2017 (footnote)22 These authors contributed equally (footnote)23 Lead Contact