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Although the majority of lung cancer is attributed to tobacco smoke, approximately 25% of lung cancers worldwide occur in lifelong never smokers. Lung cancer in never smokers (LCINS) is the 7th largest cause of cancer-related mortality in the world and has been related to several environmental risk factors for LCINS, such as passive smoking, occupational exposure and indoor air pollution. LCINS is more frequent in women, suggesting that hormonal-related factors may be involved. Several genetic studies have identified genetic variants associated with LCINS, e.g. CYP1A1 Ile462Val and XRCC1 Arg399Gln, but these were conducted in Western populations, with no dominant genetic factors confirmed across racial and ethnic groups. This is particularly important in China where the lifestyles are very different from Western countries, particular for women, e.g. regular smoking is rare, reproductive profiles differ and few use HRT.

China Kadoorie Biobank (CKB) is a large blood-based prospective study, covering 0.5 million adults aged 30-79 years recruited from 10 diverse regions in China during 2004-8. There were 316,209 never-smokers, including 30,118 men (14.5% of all men recruited) and 286,091 women (95% of all women). A subset of ~91,000 randomly selected participants have been genotyped for several genetic variants (SNPs) previously associated with smoking behaviour and lung cancer, and genome-wide SNP genotyping is underway for ~100,000 participants. By 1.1.2014, there were already 1405 LCINS cases (199 men and 1206 women).

Research Experience, Research Methods and Training

The DPhil student will study the association between the risk of lung cancer and environmental factors and gene-environmental interactions, among Chinese never smokers through:

  • Conducting thorough literature reviews;
  • Providing reliable estimates of the strength of the relationships between environmental risk factors and LCINS;
  • Using genetic data to explore gene:environment interactions, causal associations, and identify novel genetic risk factors for LCINS.

The specific line of investigation will be subject to further discussion and personal interest.

The candidate will work within a multi-disciplinary team and will gain research experience in systematic literature reviews, study design and planning, epidemiological and statistical methodology, statistical programming, data analysis and data presentation.

Field Work, Secondments, Industry Placements and Training

By the end of the DPhil, it is expected that the student will be competent to plan, undertake and interpret statistical analysis of large-scale epidemiological data, to publish 3-5 peer-reviewed papers and to report research findings at relevant meetings.

Prospective Candidate

Candidate should have at least 2.1 degree in medical sciences and an MSc in public health fields. The project will requires some previous statistical and programming training/experience.



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