Identifying Genetic Factors Associated with Breast or Ovarian Cancer Risk in BRCA1 Pathogenic Variant Carriers. Doctoral Thesis

Abstract

Breast cancer (BC) is a most prevalent cancer among women globally and ovarian cancer (OC) is also a significant healthcare burden, ranking eighth in terms of incidence and mortality in females. The aetiology of these malignancies involves a complex interplay between modifiable and non-modifiable risk factors. Among these, genetic predisposition, particularly pathogenic variants (PVs) in BRCA1 gene, significantly elevate a risk of BC or OC development. However, BC and OC risk for germline BRCA1 PV carriers differ by individual and are affected by genetic factors. The aim of this study is to explore genetic factors that might modulate BC and OC risk and to assess the effect of polygenic risk score (PRS) to estimate the overall genetic risk of a women carrying region-specific germline BRCA1 PVs to develop BC or OC due to additional genetic variations. We performed a genome-wide association study (GWAS) in 406 female BRCA1 PV (c.4035del or c.5266dup) carriers, affected with BC or OC vs. unaffected individuals, followed by functional annotations of the most significantly associated single nucleotide variants (SNVs). Next, we investigated recently developed novel genome-wise PRS association with BC and OC risk in BRCA1 PV carriers. A binomial logistic regression model was applied to assess the association of PRS with BC or OC development risk. In BC patients, the most significantly associated SNV was rs2609813 (p = 2.33 × 10−7, odds ratio (OR) = 0.28) in FAM107B gene (genomic position (GRCh37) 10:14800320). The variant is intronic in the protein coding gene and predicted to be a regulatory region variant. The second most significant BC-associated SNV was rs4688094 (p = 7.76 × 10−7, OR = 0.38) in long non-coding RNA (lncRNA) gene (genomic position (GRCh37) 3:118003477) and the most significant OC-associated SNV was rs79732499 (p = 1.38 × 10−7, OR = 0.00031) located in genomic position (GRCh37) 20:3404208 and is predicted to be a regulatory region variant located in enhancer. Both variants are in the non-coding genome. This suggests that they may influence gene expression or other regulatory processes rather than directly altering protein structure or function. Due to the small sample size, our results did not reach a genome-wide significance of p = 5 × 10−8. Regarding PRS calculations, best-fitting BayesW PRS model could effectively predict the individual’s BC risk (OR = 1.37; 95 % confidence interval (CI) = 1.03–1.81, p = 0.029 with area under receiver-operator curve (AUC) = 0.76). At the same time, none of the applied PRS was a good predictor of OC development risk, suggesting the need for further investigation in larger OC cohort. The results of this study can be used as preliminary data for a more comprehensive study and might contribute to customised PRS development for BRCA1 PV carriers. Previously developed BayesW PRS model contributed to assessing the risk of developing BC for germline 4 BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timelier patient stratification and decision-making to improve the current BC treatment or even prevention strategies.