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A PhD determining how prostate cancer evolves by analysing molecular subtypes in single-cell sequencing data (BREWERD_U23FMH)

   Faculty of Medicine and Health Science

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  Prof D Brewer  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project


Prostate cancer (PCa) is alarmingly common (12% of men are diagnosed) and often fatal (9% of male cancer deaths). The identification of molecular disease subtypes is a critical step in developing an effective personalised approach to treatment. Several molecular subtype frameworks have been proposed by applying unsupervised machine learning techniques to bulk gene expression data, including DESNT developed by ourselves. 

Single-cell sequencing has emerged as a powerful tool for studying tumours at the level of individual cells. An increasing number of PCa expression datasets at the single cell level have been generated. No one has yet investigated existing subtypes in single cell data. This provides an opportunity for us to investigate the cancer biology behind existing subtypes and discover new ones. 

Research methodology 

In this PhD you will gather all PCa single cell RNAseq datasets and process them through a common analytical pipeline. For each cell, you will determine existing subtypes and analyse them to determine their biological relevance. Finally, you will apply cutting-edge mathematics approaches to discover new subtypes that could improve patient care.   


This is a PhD in bioinformatics/data analysis. During the PhD, you will learn how to deal with "Big Data," high performance computing, pipeline development, and statistical analyses. We have extensive experience helping people to become experts at the forefront of cancer, biology, and data science. A training programme designed specifically for you will be created. You will be a member of the Norwich Medical School's Cancer Genetics team, which is an interdisciplinary team comprised of bioinformaticians and lab-based scientists. We will provide specialist support through our international collaborations. We have a broad interest in translational cancer molecular studies with the goal of improving patient care including urine-based biomarker development, whole genome sequencing studies, cancer-subtype detection, and bacteria in cancer studies. 

Person specification 

A minimum of a 2:1 honour degree in Computer Science, Physics, Mathematics, Engineering, Biological Sciences, Biochemistry, or Biomedical Science.  

Funding Notes

This PhD project is in a Faculty of Medicine and Health Sciences competition for funded studentships. These studentships are funded for 3 years and comprise UK fees, an annual stipend of £17,668 and £1,000 per annum for research training (RTSG). Overseas applicants (including EU) may apply but are required to fund the difference between Home and International tuition fees.


Suvà, M. L. & Tirosh, I. Single-Cell RNA Sequencing in Cancer: Lessons Learned and Emerging Challenges. Molecular Cell 75, 7–12 (2019).
Luca, B. et al. A novel stratification framework for predicting outcome in patients with prostate cancer. British journal of cancer 122, 1467–1476 (2020).
Luca, B.-A. et al. Convergence of Prognostic Gene Signatures Suggests Underlying Mechanisms of Human Prostate Cancer Progression. Genes 11, 802 (2020).
ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82–93 (2020).
Wedge, D. C. et al. Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets. Nature genetics 50, 682–692 (2018).
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