Risks and Function of Breast Cancer Susceptibility Alleles

SIMPLE SUMMARY: Population-based genetic risk stratification and detection of early-stage breast cancers will improve approaches to prevent and reduce disease-associated mortalities. In this review, we summarize the latest discoveries in breast cancer susceptibility genetics and propose how these findings can be applied in the clinical arena to improve risk prediction and prevention of breast cancer. We also review the latest approaches and progress aimed at elucidating the functional consequences of both high and moderate penetrance genetic variation, which tend to lie in the protein coding regions of breast cancer susceptibility genes, and common low penetrance breast cancer risk alleles which tend to lie in non-protein coding DNA regions and affect gene regulation. For non-coding risk variation, there is no genetic code to interpret the function of common risk allele; and so, we provide the reader with an illustration of the step-by-step methods to understand their functional impact on breast cancer disease biology. ABSTRACT: Family history remains one of the strongest risk factors for breast cancer. It is well established that women with a first-degree relative affected by breast cancer are twice as likely to develop the disease themselves. Twins studies indicate that this is most likely due to shared genetics rather than shared epidemiological/lifestyle risk factors. Linkage and targeted sequencing studies have shown that rare high- and moderate-penetrance germline variants in genes involved in the DNA damage response (DDR) including BRCA1, BRCA2, PALB2, ATM, and TP53 are responsible for a proportion of breast cancer cases. However, breast cancer is a heterogeneous disease, and there is now strong evidence that different risk alleles can predispose to different subtypes of breast cancer. Here, we review the associations between the different genes and subtype-specificity of breast cancer based on the most comprehensive genetic studies published. Genome-wide association studies (GWAS) have also been used to identify an additional hereditary component of breast cancer, and have identified hundreds of common, low-penetrance susceptibility alleles. The combination of these low penetrance risk variants, summed as a polygenic risk score (PRS), can identify individuals across the spectrum of disease risk. However, there remains a substantial bottleneck between the discovery of GWAS-risk variants and their contribution to tumorigenesis mainly because the majority of these variants map to the non-protein coding genome. A range of functional genomic approaches are needed to identify the causal risk variants and target susceptibility genes and establish their underlying role in disease biology. We discuss how the application of these multidisciplinary approaches to understand genetic risk for breast cancer can be used to identify individuals in the population that may benefit from clinical interventions including screening for early detection and prevention, and treatment strategies to reduce breast cancer-related mortalities.