Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.


Worldwide Epstein-Barr virus (EBV) accounts for >0.2 million cancer cases annually, with certain countries in Southeast Asia and North Africa having particularly high EBV-associated disease burden (e.g. nasopharyngeal cancer [NPC]). The mechanisms of cancer causation by EBV remain an area of active investigation. Since EBV-associated cancers are often diagnosed at advanced stages with poor survival rates, identification of biomarkers present in EBV-positive individuals may aid early detection and prediction of prognosis. We have developed and optimised Luminex-based Multiplex sero-panels that includes 54 (12 EBV-related) infective biomarkers (or antigens) covering 16 pathogens. The Multiplex panels are being used in assays of the stored baseline samples from ~400 incident cases of NPC, 200 incident cases of gastric cancer and ~800 randomly selected sub-cohort participants in the prospective China Kadoorie Biobank (CKB) study of >512,000 adults to assess the roles of chronic infections in cancer aetiology. 


This DPhil project will assess the associations of chronic EBV infection with risks of NPC and gastric cancer in CKB. The specific objectives include:

  1. To examine the risks of NPC and gastric cancer associated with chronic EBV infection, both overall and by individual antigen biomarkers;
  2. To assess the roles of co-infection of EBV and H. pylori in development of gastric cancer;
  3. To undertake genetic analyses assessing the roles of host immunity (eg, HLA-related variants) in the relationship of EBV infection and cancer risks;
  4. To develop risk prediction models for NPC and gastric cancer incorporating lifestyle factors, chronic infections and genetic factors.

There will be in-house training opportunities in epidemiology, genetics, bioinformatics and statistical analysis and attendance at relevant courses. By the end of the DPhil, the student will be competent to plan, undertake and interpret analyses of large-scale epidemiological and genetic data, and to report research findings, including 3-5 publications in peer-reviewed journals and presentation at national/international conferences.


The project will be based within the CKB research group, part of the Nuffield Department of Population Health and based in the Big Data Institute (BDI) building. There are excellent facilities and a world-class community of population health, laboratory, genetic and data scientists. There will be opportunities to collaborate across scientific disciplines and participate in international collaborations. Training will be provided within the Department on data analysis and statistical methods and, if necessary, by external courses.


Candidates should have a strong background in biomedical or quantitative sciences and postgraduate training in epidemiology, biology, genetics, statistics or a related subject, with interest in epidemiology, genetics and/or infection-related disease research. The project requires some previous statistical and programming training/experience.