Validation of lung cancer polygenic risk scores in a high-risk case-control cohort

Purpose: Screening with low-dose CT reduces lung cancer (LC) mortality. Risk prediction models used for screening selection do not include genetic variables. Here, we investigate the performance of previously published polygenic risk scores (PRS) for LC, considering their potential to improve screening selection.
Methods: We validated nine PRSs in a high-risk case-control cohort, comprising genotype data from 652 surgical patients with LC and 550 cancer-free, high-risk (PLCOM2012 score ≥1.51%) participants of the Manchester LHC, a community-based LC screening programme (n=550). Discrimination (area under the curve, AUC) between cases and controls was assessed for each PRS independently and alongside clinical risk factors.
Results: Median age was 67, 53% were female, 46% were current smokers, 76% were National Lung Screening Trial eligible. 80% of cases were early stage. Median PLCOM2012 score among controls was 3.4%. All PRSs significantly improved discrimination, AUC increased between +0.002 (p=0.02) and +0.015 (Conclusion: PRSs may improve LC risk prediction and screening selection. Further research, particularly examining clinical utility and cost-effectiveness, is required.