Xuemin Wang

Dietary Factors and Endometrial Cancer Risk: A Mendelian Randomization Study

Given the strong association between obesity and endometrial cancer risk, dietary factors may play an important role in the development of this cancer. However, observational studies of micro- and macronutrients and their role in endometrial cancer risk have been inconsistent. Clarifying these relationships are important to develop nutritional recommendations for cancer prevention. We performed two-sample Mendelian randomization (MR) to investigate the effects of circulating levels of 15 micronutrients (vitamin A (retinol), folate, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, β-carotene, calcium, copper, iron, magnesium, phosphorus, selenium, and zinc) as well as corrected relative macronutrient intake (protein, carbohydrate, sugar and fat) on risks of endometrial cancer and its subtypes (endometrioid and non-endometrioid histologies). Genetically predicted vitamin C levels were found to be strongly associated with endometrial cancer risk. There was some evidence that genetically predicted relative intake of macronutrients (carbohydrate, sugar and fat) affects endometrial cancer risk. No other significant association were observed. Conclusions: In summary, these findings suggest that vitamin C and macronutrients influence endometrial cancer risk but further investigation is required.

10 Years of GWAS discovery in endometrial cancer: Aetiology, function and translation

Endometrial cancer is a common gynaecological cancer with increasing incidence and mortality. In the last decade, endometrial cancer genome-wide association studies (GWAS) have provided a resource to explore aetiology and for functional interpretation of heritable risk variation, informing endometrial cancer biology. Indeed, GWAS data have been used to assess relationships with other traits through correlation and Mendelian randomisation analyses, establishing genetic relationships and potential risk factors. Cross-trait GWAS analyses have increased statistical power and identified novel endometrial cancer risk variation related to other traits. Functional analysis of risk loci has helped prioritise candidate susceptibility genes, revealing molecular mechanisms and networks. Lastly, risk scores generated using endometrial cancer GWAS data may allow for clinical translation through identification of patients at high risk of disease. In the next decade, this knowledge base should enable substantial progress in our understanding of endometrial cancer and, potentially, new approaches for its screening and treatment.