Molecular biomarkers and cancer risk: insights from UK Biobank
- 8 September 2025 to 2 December 2025
- Project No: D26059
- DPhil Project 2026
Background
Cancer is a leading cause of morbidity and mortality globally, accounting for an estimated 20 million new cases and 9.7 million deaths in 2022. Both genetic and nongenetic factors are implicated in the aetiology of cancer. Factors that have been linked to cancer in epidemiological studies include family history, genetic composition, obesity, tobacco use, physical inactivity, alcohol consumption, reproductive history and medical factors. Known risk factors account for only a limited proportion of cancer burden with a considerable proportion of cancer cases still remaining unexplained. This highlights the need for more research to identify novel risk factors for cancer.
Many lifestyle and environmental exposures linked to cancer alter levels of metabolites and other biomolecules, and such alterations can potentially influence the development of cancer some years before cancer is diagnosed. Understanding metabolic disturbances that play a role in cancer development is important as it can improve early diagnosis, identify high-risk groups for targeted screening, and enable precision preventative strategies.
The UK Biobank is a large-scale prospective cohort of 500,000 participants which contains an unprecedented wealth of data on lifestyle, environment, genetics and biomarkers and provides an opportunity to investigate biomarkers, lifestyle, and cancer risk.
The exact project will be shaped by the student with the supervisors, but will involve the identification of novel risk factors for cancer by integrating lifestyle, environmental, and biomarker data, using appropriate methodology.
Secondary aims could involve investigating the relationship between circulating proteins/metabolites and cancer incidence and to assess whether biomarkers mediate the effects of lifestyle factors (e.g., smoking, diet, obesity) on cancer risk using mediation analysis. Sensitivity analyses could also be undertaken to determine to what extent any associations found differ by population subgroups (e.g, age, sex, tumour subtype).
research experience, research methods and skills training
This project will provide the successful applicant with excellent training in large-scale molecular epidemiology and the statistical analysis of prospective data. It will provide opportunities to network with other researchers. The student will receive training in conducting literature reviews and writing academic papers for peer-reviewed journals and will work closely with a strong interdisciplinary team of researchers with expertise in epidemiological study design, biomarker and molecular epidemiology, statistics and clinical medicine.
PROSPECTIVE STUDENT
The ideal candidate will have a Master’s degree in epidemiology or statistics and will be expected to have knowledge and experience in epidemiological study design and related concepts and be adept in statistical analysis. The student will analyse the data using UK Biobank’s Research Analysis Platform and will be using Rstudio as the main statistical language.