Integration of polygenic risk scores with modifiable risk factors improves risk prediction: results from a pan-cancer analysis

ABSTRACT Cancer risk is determined by a complex interplay of genetic and modifiable risk factors. Combining individual germline risk variants into polygenic risk scores (PRS) creates a personalized genetic susceptibility profile that can be leveraged for disease prediction. Using data from the UK Biobank cohort (413,753 individuals; 22,755 incident cases), we systematically quantify the added predictive value of augmenting conventional cancer risk factors with PRS for 16 cancer types. Our results indicate that incorporating PRS in addition to family history of cancer and modifiable risk factors improves prediction accuracy, but the magnitude of incremental improvement varies substantially between cancers. We also demonstrate the utility of PRS for risk stratification. Individuals with high genetic risk (PRS≥80th percentile) have significantly divergent 5-year absolute risk trajectories across strata based on family history and modifiable risk factors. Finally, we estimate that high genetic risk accounts for 4.0% to 30.3% of new cancer cases, which exceeds the impact of many lifestyle-related risk factors. In summary, we provide novel quantitative data illustrating the importance of integrating PRS into personalized cancer risk assessment.