Chronic infection, host immunity, and cancer risk [MRC PHRU]
OPH/23/37
BACKGROUND
Worldwide, chronic infection of pathogens causes >2 million new cancer cases each year, with about two-thirds in less developed countries including China. While the role of several pathogens (e.g. H. pylori, HBV, HCV, EBV, and HPV) in aetiology of certain cancers are well established, there is still limited data about their relevance for other cancer types, about the long-term health consequence of other chronic infections (e.g. certain types of herpes virus, Chlymedia), and about the roles of host immunity and pathogen subtypes in disease aetiology. Large prospective studies, such as the China Kadoorie Biobank (CKB), are well positioned to address various evidence gaps.
In CKB serological data on 20 pathogens will be generated shortly among ~40,000 participants (30,000 cancer cases and 10,000 sub-cohorts) using a custom-designed multiplex serological panel, along with HBV viral sequencing data among ~4000 HBV-infected participants. These, together with available lifestyle, genetic, and health outcome data, will enable comprehensive assessment of causal roles of multiple pathogen infections in aetiology of site-specific cancers and certain other diseases.
RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING
A CRUK-funded scholarship is available for this project.
The specific project will be developed according to the student’s interests and aptitude, and may cover following key objectives:
- To examine the associations of chronic infection of particular pathogens with risks of site-specific cancers (e.g. lymphoma) and certain other diseases;
- To assess the role of host immune genetics (e.g. HLA) in susceptibility to development of specific types of chronic infection and cancer;
- To determine the value of serological markers, in combination with other lifestyle and genetic factors, in predicting the risks of infection-related cancers;
- To estimate the burden of different cancers attributable to chronic infection of particular pathogens.
The student will work within a multi-disciplinary team, and will gain training and research experience in systematic literature review, study design and planning, data analysis and scientific writing. By the end of the DPhil, the student will be competent to review the literature, to plan, undertake and interpret analyses of large datasets, and to report research findings, including publications in peer-reviewed journals as lead author and presentation at conferences.
FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING
The student will be based within the CKB group at the Big Data Institute Building. There are excellent facilities and a world-class community of population health, data science, infectious disease, and genomic medicine researchers. There will be in-house training in epidemiology, statistics, and genetics and opportunities to work with external research institutes.
PROSPECTIVE STUDENT
Candidates should have a 2.1 in first degree and MSc in epidemiology, statistics, genetics, biomedical science, or other related subjects, with a strong interest in population health.