Developing risk model for prediction of gastric cancer risk based on polygenic risk score and non-genetic risk factors
Principal Investigator: Professor Guangfu Jin
Approved Research ID: 55862
Approval date: January 31st 2020
Previous risk prediction models apply established environmental and behavioral risk factors to estimate individual risk, and numerous models have been developed for cancer. Recent large-scale population studies have suggested that the combined effect of genetic variants might also serve as an efficient tool to discriminate cancer risk. Specially, polygenic risk scores calculated by summing the effects of genetic variants have been used to identify individuals at an increased risk of breast cancer. Gastric cancer is a multifactorial disease, and both environmental and genetic factors play a role in its etiology. Recently, several studies have included genetic risk factors and non-genetic factors to assess cancer risk more accurately. The purpose of this research is to construct GC risk models with both PRS and non-genetic risk factors and to evaluate the utility and effectiveness in predicting GC risk in independent prospective cohorts of Chinese population and European population. The findings will improve our understanding of cancer risk assessment model construction and therefore guide us to identify high-risk individuals more accurately. This research will make important contributions to the guidance of personalized prevention of gastric cancer.