Research Question: How do modifiable environmental and lifestyle exposures, clinical factors, genetic susceptibility, and multi-omic signatures jointly influence cancer tumorigenesis and prognosis, and which of these associations are causal and actionable for early detection and prevention?
Specific Aims: Across major cancer types, we aim to:
1.Quantify epidemiologic associations between broad exposures (smoking, diet, BMI, air pollution, infections and so on) and cancer incidence and mortality.
2.Characterize genetic susceptibility through genome-wide association studies (GWAS) and polygenic risk scores (PRS), and quantify gene-environment (GxE) interactions influencing cancer prognosis.
3.Identify proteomic, metabolomic, and serologic signatures for early cancer detection, subtype classification, and prognosis.
4.Apply Mendelian randomization to test the causal effects of modifiable exposures (adiposity, smoking, lipid levels and so on) on cancer tumorigenesis and prognosis.
Scientific Rationale: Cancer is a leading global health burden driven by a complex interaction of environmental exposures, lifestyle, comorbidities, inherited genetic susceptibility, and molecular alterations. Leveraging the UK Biobank’s rich exposure, genetic, and multi-omic data, we will combine GWAS/PRS, GxE analysis, and Mendelian randomization to identify causal modifiable factors and predictive molecular signatures for cancer prevention.
Objectives: We will create an atlas of modifiable and non-modifiable cancer determinants to reveal shared and cancer-specific drivers. We will validate PRS and multi-omic signatures for risk prediction and prognosis, and provide causal evidence to prioritize prevention strategies.
This project will be led by the student as a first-author academic research paper. All analyses are non-commercial, comply with UK Biobank ethics and data access rules, and all scripts and phenotype definitions will be documented for reproducibility.
