Pathogenic Variant Status of High-Risk Genes, Polygenic, Epidemiological Risk Factors, and Utilization of Risk Management Options in Breast Cancer

Breast cancer is a heterogeneous disease with multiple established risk factors, which include high-penetrance germline variants in cancer predisposition genes such as ATM, BRCA1, BRCA2, CHEK2, and PALB2. Additionally, individual and behavioral factors such as age at menarche, parity, number of births, age at first full-term pregnancy, breastfeeding, age at natural menopause, height, pre- and post-menopausal body mass index (BMI), use of menopausal hormone treatment (PMH) and oral contraceptives (OC), history of benign breast disease (BBD), smoking and alcohol consumption have been consistently observed to be associated with breast cancer risk and may potentially modify the risk associated with pathogenic variants (PV). However, existing gene-environment interaction (GE) studies of rare PVs in breast cancer predisposition genes have been limited by sample size and the number of interactions assessed. GE studies have rarely been replicated1–5, due to issues related to statistical power, exposure measurement errors, and difficulties in harmonizing data across different studies. Further, breast cancer is often treated as one disease, without consideration of molecular subtypes, primarily defined by estrogen receptor (ER) status, ignoring well-known differences in etiologies. Further, women who have been identified to have an elevated lifetime risk of breast cancer through genetic testing for hereditary cancer syndromes can benefit from risk management options such as enhanced screening and preventive surgery. However, these recommended risk management strategies are underutilized in current clinical practice, and healthcare utilization patterns following genetic testing remain poorly understood, particularly in underserved populations facing access barriers to genetic services. In this dissertation, we explored how genetic, epidemiological, and behavioral factors collectively influence breast cancer risk. Specifically, we aimed to 1) examine GE interactions between high penetrance breast cancer susceptibility genes and well-established epidemiological risk factors; 2) assess the impact of modifiable epidemiological risk factors on breast cancer risk across categories defined by nonmodifiable risk factors including a polygenic risk score (PRS) of common genetic variants; 3) examine the uptake of recommended risk management strategies for breast cancer subsequent to the disclosure of genetic testing results. To achieve these aims, we first explored GE interactions on both multiplicative and additive scales in a sample of women drawn from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium and the UK Biobank, comprising of 28,745 breast cancer cases and 102,997 controls. Subsequently, we developed a breast cancer risk prediction model that integrated breast cancer predisposition genes, a PRS, an epidemiologic risk score (ERS) for non-modifiable risk factors, and another ERS for modifiable risk factors, to examine the joint effects of these factors on breast cancer risk. Our findings demonstrated that an ERS, when combined with the PRS, could contribute to risk stratification for women who have a rare PV in a high-penetrance breast cancer susceptibility gene. The integration of rare high-penetrant and common low-penetrant genetic variation with epidemiologic risk factors into breast cancer risk prediction models has the potential to inform personalized screening and prevention strategies. Next, we assessed the utilization of recommended risk management options following genetic testing for hereditary cancer syndromes based on data from 680 patients who were part of the Cancer Health Assessments Reaching Many (CHARM) study, a multimodal cancer genetics services delivery program. We identified post-testing screening and surgical procedures using electronic health records, and examined utilization in participants who did and did not receive actionable risk management recommendations from study genetic counselors following national guidelines. Our results indicate that implementing CHARM’s risk assessment and testing model increased access to evidence-based genetic services and provided opportunities for patients to engage in recommended preventive care, without encouraging excessive use of risk management strategies. The findings of this dissertation could be useful to identify population subgroups who are especially susceptible to developing breast cancer and help establish personalized risk prevention recommendations for high-risk women.