Polygenic Risk Scores for Breast Cancer: Modern Approaches to Risk Prediction and Subtype Identification

Abstract

Breast cancer (BC), a complex disease characterized by the uncontrolled proliferation of breast cells, poses a major global health challenge. Its increasing prevalence is influenced by a combination of genetic, environmental, and lifestyle factors. While hereditary mutations in high-risk genes contribute to only a small percentage of cases, the majority may be influenced by common genetic variations that collectively determine individual susceptibility. The polygenic risk score (PRS) has emerged as a transformative tool that leverages the cumulative effects of multiple genetic variants to improve risk prediction beyond traditional single-gene models. When integrated with conventional risk factors, such as age, reproductive history, and modifiable lifestyle behaviors, PRS offers a more comprehensive approach to personalized risk assessment. Recent studies highlight its potential to guide targeted screening strategies, early interventions, and precision prevention efforts. This review provides insight into current PRS research and its clinical applications in BC risk stratification. It also explores the promise of PRS in shaping the future of precision oncology.