The Silent Threat in Breast Cancer: A Systems Biology Approach to Decoding Tumour Cell Dormancy and the Drivers of Metastasis
Project Overview:
The project, "The Silent Threat in Breast Cancer: A Systems Biology Approach to Decoding Tumour Cell Dormancy and the Drivers of Metastasis," addresses a critical challenge in oncology: understanding why some breast cancer cells remain dormant for years before reactivating to cause incurable metastatic relapse. Despite advances in treatment, breast cancer remains the leading cause of cancer-related death for women in the UK, with late relapse posing a significant clinical problem. The biological mechanisms that allow tumour cells to enter and maintain this dormant, treatment-resistant state are not well understood.
Research Focus:
This interdisciplinary PhD project will investigate the molecular mechanisms of metastatic dormancy using a unique collection of RNA-sequencing datasets from novel breast cancer dormancy models developed by the supervisory team. The student will employ advanced bioinformatics and systems biology approaches to decode the molecular programmes and regulatory networks underlying mitotic quiescence and tumour cell dormancy across various breast cancer subtypes. The project will also utilize cutting-edge 10X Genomics Xenium spatial transcriptomic profiling to validate key dormancy mechanisms and explore how dormant cells survive within their native microenvironment. The ultimate goal is to build a mechanistic framework explaining how breast cancer cells persist long-term and what triggers their reactivation, providing vital insights to help prevent metastatic relapse.
Training and Environment:
The successful applicant will gain hands-on experience in high-performance computing, bioinformatic analytics, network biology, and spatial omics, supported by an expert supervisory team with extensive experience in cancer cell biology and multi-omics analysis. The student will join a vibrant research community and benefit from the structured training environment of the Yorkshire Bioscience Doctoral Training Partnership (YBDTP), which brings together world-class bioscience research and innovation across the Yorkshire and Teesside region. The YBDTP offers interdisciplinary collaboration and a comprehensive doctoral training programme, equipping students with research and professional skills for both academic and non-academic careers.
Supervisory Team:
Supervisors include Dr Lewis Quayle (
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), Associate Professor Nik Georgopoulos (
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), and Professor Penelope D Ottewell (
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). For informal enquiries, contact Dr Lewis Quayle at l.quayle@shu.ac.uk.
Funding:
This is a fully funded four-year studentship for UK (home) students, including a tax-free annual stipend aligned with the higher of the net Real Living Wage (£22,152 for 2025/26) or the standard UKRI rate (£20,780 for 2025/26), research costs, and tuition fees at the UK rate.
Eligibility and Requirements:
Applicants must have, or expect to gain, at least an upper second-class honours degree (or equivalent) in a biological, chemical, or physical science, or mathematics. A strong interest in cancer and interdisciplinary research is essential. English language requirements are IELTS 7 with a minimum of 6.5 in all areas (or equivalent), with qualifications taken within the last two years. The programme welcomes applicants from all backgrounds, especially those underrepresented in science.
Application Process:
To apply, complete the expression of interest form for the Yorkshire Bioscience Doctoral Training Partnership by 5pm (UK time), Wednesday 7th January 2026. You may apply for up to two YBDTP projects. For project-specific questions, contact the supervisor; for application process queries, email YBDTP@leeds.ac.uk. Shortlisted candidates will be invited for interview in February 2026. Successful applicants must confirm acceptance within 10 days of offer.
References and Further Reading:
Relevant literature and recent research by the supervisory team are listed in the position description, providing a strong foundation for the project.