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Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Authors :
Luke Marsden
Colin Cooper
Jorge Zamora
Barbara Kremeyer
Jonathan Kay
Steven Hazell
Mahbubl Ahmed
Tim Dudderidge
Edward Rowe
Hongwei Zhang
William Howat
Freddie C. Hamdy
Tapio Visakorpi
Paul C. Boutros
Gunes Gundem
Bissan Al-Lazikani
S. Edwards
David C. Wedge
Inigo Martincorena
Charles E. Massie
Douglas F. Easton
Gerhardt Attard
Nicholas van As
Anne Y. Warren
Dan J. Woodcock
Naomi Livni
Johann S. de Bono
Nening Dennis
Adam Lambert
Clare Verrill
Alan Thompson
Niedzica Camacho
Daniel Leongamornlert
William B. Isaacs
Christopher S. Foster
Hayley C. Whitaker
Pardeep Kumar
Daniel Brewer
Christopher Greenman
Declan Cahill
Simon Tavaré
Yong-Jie Lu
Stuart McLaren
Ultan McDermott
David T. Jones
Sue Merson
Rosalind A. Eeles
Vincent Khoo
Steve Hawkins
Daniel M. Berney
Cyril Fisher
Hayley J. Luxton
Lucy Matthews
Ludmil B. Alexandrov
G. Steven Bova
Adam Butler
David Nicol
Andy G. Lynch
Michael Fraser
Tokhir Dadaev
Keiran Raine
Mohammed J. R. Ghori
Katalin Karaszi
Jon W. Teague
Chris Sander
Robert G. Bristow
Peter Van Loo
Nimish Shah
Chris Ogden
Paul Workman
Andrew Menzies
Lucy Stebbings
Stefan C. Dentro
Cathy Corbishley
Thomas J. Mitchell
Zsofia Kote-Jarai
Pelvender Gill
Andrew Futreal
Elizabeth Bancroft
David E. Neal
Sarah Thomas
Anthony C. H. Ng
Erik Mayer
Yongwei Yu
Vincent Gnanapragasam
Valeria Bo
University of St Andrews. Cellular Medicine Division
University of St Andrews. Statistics
University of St Andrews. School of Medicine
Source :
Nature genetics, vol 50, iss 5
Publication Year :
2018

Abstract

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials. Postprint

Details

Language :
English
ISSN :
15461718 and 10614036
Volume :
50
Database :
OpenAIRE
Journal :
Nature Genetics
Accession number :
edsair.doi.dedup.....8e3ffd6b6e74bb3d2b3dcdbbf64a4967