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The dysregulation of the human proteome is a valuable window into the biology of tumour aggressiveness and immune responses to the presence of cancer. Proteins are also often direct targets for cancer treatments and so an expanded understanding of proteins related to cancer prognosis may provide insight into novel pathways for improving cancer survival.

This DPhil project will use novel genetic epidemiological methods and resources from large genetic consortia to investigate the role that proteins may play in the progression of colorectal, prostate, lung, and breast cancers using methods such as Mendelian randomisation (MR) and colocalization.

MR is a statistical method to estimate potentially causal associations between a risk factor, such as the level of a protein in blood, and progression of a disease. MR uses knowledge of inherited genetic variants to estimate the association of genetically predicted exposures on the risk for a disease and can, in special cases, be analogised to an in silico randomised control trial (RCT). As an example, we have previously used MR and observational data from prospective cohorts to triangulate associations between insulin-like growth factor (IGF)-I and breast, prostate, and colorectal cancers.

As part of our ongoing work, we have curated a database of genetic variants that modify the biological function and abundance of almost 3,000 proteins. With these resources, combined with access to large-scale genetic studies of cancer prognosis, a prospective student will conduct MR analyses to identify novel proteins related to cancer prognosis. Subsequent analyses investigating a potential role for proteins in the somatic tumour environment, including tumour tissue expression and mutational signatures, also represent an important avenue of research within this project that can be pursued by a prospective student.

This project is an exciting opportunity for a postgraduate student to contribute to the evidence on potentially measurable biological determinants of cancer prognosis working in the Cancer Epidemiology Unit, Nuffield Department of Population Health.


This project will provide the successful applicant with excellent training in large scale cancer and genetic epidemiology and the statistical analysis of germline and somatic genetic and molecular data. In completion of this project there will be opportunities to network with other investigators both locally and with international collaborators. Additionally, a student be trained to conduct literature reviews and write academic papers for peer-reviewed journals. In doing so they will work closely with a strong interdisciplinary team of researchers with expertise in epidemiology, cancer, biomarker and molecular epidemiology, statistics, Mendelian randomization.


It is anticipated that the student will make research visits to our collaborators, including EPIC collaborators at the WHO International Agency for Research on Cancer (IARC), Lyon, France. Training will be provided within the Department of data analysis, record linkage between multiple research databases, and statistical methods and, if necessary, by external courses.


This project will suit someone with an interest in genetic epidemiology and cancer who is looking to expand their skills and experience in epidemiological study design, the statistical analysis of biomarker, molecular, lifestyle and other epidemiological data and Mendelian randomization analyses.

Candidates should have a strong background in a biomedical, life sciences or statistical discipline. Previous postgraduate training or experience in epidemiology and/or medical statistics is preferred.