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Our Research
All of our research is aimed at using cancer biology to answer clinically relevant questions in translational cancer research, with a particular focus on prostate cancer. We develop or use large-scale ‘omic datasets from human tumour samples and apply novel analytic and experimental techniques to them to reveal cancer aetiology and develop clinical tests. Our research is focused on four topics.
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Joint Group Leader: Professor Colin Cooper
View my research profileI am a leading cancer genetics researcher and co-lead the Cancer Genetics Team. I studied science at the University of Warwick and completed my PhD in biochemistry at the University of Birmingham. I formerly worked at the Institute of Cancer Research and was Chair of Molecular Biology at the University of London.
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Joint Group Leader: Professor Dan Brewer
View my research profileI am a group leader within the Cancer Genetics Team, Norwich Medical School, with over two decades of experience in cancer bioinformatics in translational research. After completing my first degree in Physics (MSci) at Imperial College London, I went on to study for an MRes in Biological Complexity and PhD in Computational Biology at University College London. I was employed as a Bioinformatics Officer at the Institute of Cancer Research (ICR) before moving to the University of East Anglia in 2013.
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Sequencing studies
We play a key role in the UK International Cancer Genome Consortium Prostate Cancer and subsequently the Pan Prostate Cancer Group. These initiatives collect and analyse the whole genome sequences, transcriptomes and methylomes of prostate cancer samples. They have provided critical insights into the molecular mechanism of development of early and advanced prostate cancer.
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Urine biomarker development
We led the Movember GAP1 Urine Biomarker Project that enabled the discovery of Prostate Urine Risk (PUR) score that has a significant association with the aggressiveness of prostate cancer and can be used to predict how long men remain on active surveillance before they progress. We are currently being funded to progress the future implementation of the PUR test in the clinic as an aid in shared decision making between patients and clinicians.
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Subtypes in cancer
Within a single cancer disease type, sub classification is important to accurately determine prognosis, optimise treatment pathways, and help develop targeted drugs. Prostate cancer does not have well defined molecular subtypes, despite the heterogeneity associated with the disease. We have successfully applied a Bayesian clustering method to prostate cancer and have found that different cancer subtypes can be identified in a single tumour sample, including a subtype called DESNT associated with poor prognosis. We are in the process of translating DESNT for use in a clinical setting.
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Cancer and bacteria
Bacteria play a suspected role in the development of several cancer types. We have demonstrated a striking association between the presence of bacteria in urine sediments and prostate cancer with a high risk of progression, and we are currently investigating the potential mechanisms of interaction. We have also developed an analytic pipeline (SEPATH) that identifies infectious agents in whole genome sequencing data. This pipeline has been further developed and applied to the whole genome sequence data of 40,000 cancer genomes from Genomics England’s 100,000 Genome project, 1000 prostate cancer genomes from the ICGC PanProstate project and 2500 geneomes from the ICGC PanCancer project.
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Recent Group Publications
Genomic evolution shapes prostate cancer disease type
View the publication onlineWoodcock DJ, Sahli A, Teslo R, Bhandari V, Gruber AJ, Ziubroniewicz A, et al. Cell Genomics [Internet]. 2024 Mar [cited 2024 Apr 26];4(3):100511.
Microbiomes of Urine and the Prostate Are Linked to Human Prostate Cancer Risk Groups
View the publication onlineHurst R, Meader E, Gihawi A, Rallapalli G, Clark J, Kay GL, et al. European Urology Oncology [Internet]. 2022 Aug [cited 2022 Sep 20];5(4):412–9.
The architecture of clonal expansions in morphologically normal tissue from cancerous and non-cancerous prostates
View the publication onlineBuhigas C, Warren AY, Leung WK, Whitaker HC, Luxton HJ, Hawkins S, et al. Molecular Cancer [Internet]. 2022 Sep 22 [cited 2022 Sep 22];21(1):183.
A novel stratification framework for predicting outcome in patients with prostate cancer
View the publication onlineLuca B alexandru, Moulton V, Ellis C, Edwards DR, Campbell C, Cooper RA, et al. British Journal of Cancer [Internet]. 2020 May 20;122(10):1467–76.
A four-group urine risk classifier for predicting outcomes in patients with prostate cancer
View the publication onlineConnell SP, Yazbek-Hanna M, McCarthy F, Hurst R, Webb M, Curley H, et al. BJU International [Internet]. 2019 Oct 20;124(4):609–20.