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

  • David C. Wedge, Gunes Gundem, Thomas Mitchell, Dan J. Woodcock, Inigo Martincorena, Mohammed Ghori, Jorge Zamora, Adam Butler, Hayley Whitaker, Zsofia Kote-Jarai, Ludmil B. Alexandrov, Peter Van Loo, Charlie E. Massie, Stefan Dentro, Anne Y. Warren, Clare Verrill, Dan M. Berney, Nening Dennis, Sue Merson, Steve Hawkins, William Howat, Yong-Jie Lu, Adam Lambert, Jonathan Kay, Barbara Kremeyer, Katalin Karaszi, Hayley Luxton, Niedzica Camacho, Luke Marsden, Sandra Edwards, Lucy Matthews, Valeria Bo, Daniel Leongamornlert, Stuart McLaren, Anthony Ng, Yongwei Yu, Hongwei Zhang, Tokhir Dadaev, Sarah Thomas, Douglas F. Easton, Mahbubl Ahmed, Elizabeth Bancroft, Cyril Fisher, Naomi Livni, David Nicol, Simon Tavaré, Pelvender Gill, Christopher Greenman, Vincent Khoo, Nicholas Van As, Pardeep Kumar, Christopher Ogden, Declan Cahill, Alan Thompson, Erik Mayer, Edward Rowe, Tim Dudderidge, Vincent Gnanapragasam, Nimish C. Shah, Keiran Raine, David Jones, Andrew Menzies, Lucy Stebbings, Jon Teague, Steven Hazell, Cathy Corbishley, Johann de Bono, Gerhardt Attard, William Isaacs, Tapio Visakorpi, Michael Fraser, Paul C. Boutros, Robert G. Bristow, Paul Workman, Chris Sander, Freddie C. Hamdy, Andrew Futreal, Ultan McDermott, Bissan Al-Lazikani, Andrew G. Lynch, G. Steven Bova, Christopher S. Foster, Daniel S. Brewer, David E. Neal, Colin S. Cooper, Rosalind A. Eeles
  • Nature Genetics, April 2018, Springer Science + Business Media
  • DOI: 10.1038/s41588-018-0086-z

Detecting new potential lines of attack against prostate cancer based on genetic information

What is it about?

We obtained genetic information from the tumours of 112 men with prostate cancer and pooled it with data from other studies, together analysing samples from 930 prostate cancer patients. A detailed genetic analysis with the latest Big Data approaches identified a large numbers of genetic changes that underlie the development and spread of prostate cancer. 22 previously unidentified changes that drive prostate cancer were identified. A timeline of genetic changes in prostate cancer was also established. The genetic information was linked with a map of the network of associated proteins. Using canSAR, a comprehensive database for cancer drug discovery, 80 of the proteins in the network were possible drug targets. Some 11 of these were targeted by existing licensed drugs and seven by drugs in clinical trials, while 62 were identified as potential targets to explore.

Why is it important?

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. New knowledge and treatments are required to make sure patients have the best possible outcome. While further research is needed before the potential new targets could be explored in clinical trials, the new study has opened up many potential ways of targeting the disease. For example, the research raised the possibility that BRAF and ATM proteins could be targeted in prostate cancer – and research is already under way in these areas. The timeline of genetic changes in prostate cancer could in future improve ways to spot the disease – as current methods of diagnosis, such as PSA testing, are unreliable. The timeline could also help predict the way prostate cancer evolves in individual patients, which might allow treatment to be adapted to combat drug resistance.


Dr Daniel S. Brewer
University of East Anglia

This paper used approximately the first 100 samples sequenced as part of the CRUK-ICGC prostate UK project. It combines this data with existing data and drug information to identify potentially important changes in the genetic code of a cancerous cell and possible ways to reverse these modifications through the use of developed drugs. This work has identified 80 potential lines of attack against prostate cancer.

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The following have contributed to this page: Dr Daniel S. Brewer