In addition to several well-established breast cancer (BC) susceptibility genes, the contribution of other candidate genes to BC risk remains mostly undefined. BARD1 is a potentially predisposing BC gene, however, the rarity of its mutations and an insufficient family/study size have hampered corroboration and estimation of the associated cancer risks. To clarify the role of BARD1 mutations in BC predisposition, a comprehensive case-control association study of a recurring nonsense mutation c.1690C>T (p.Q564X) was performed, comprising ~14,000 unselected BC patients and ~5900 controls from Polish and Belarusian populations. For comparisons, two BARD1 variants of unknown significance were also genotyped. We detected the highest number of BARD1 variants in BC cases in any individual BARD1-specific study, including 38 p.Q564X mutations. The p.Q564X was associated with a moderately increased risk of BC (OR = 2.30, p = 0.04). The estimated risk was even higher for triple-negative BC and bilateral BC. As expected, the two tested variants of unknown significance did not show significant associations with BC risk. Our study provides substantial evidence for the association of a deleterious BARD1 mutation with BC as a low/moderate risk allele. The p.Q564X was shown to be a Central European recurrent mutation with potential relevance for future genetic testing.

Over the last two decades, numerous BARD1 mutations/pathogenic variants (PVs) have been found in patients with breast cancer (BC) and ovarian cancer (OC). However, their role in BC and OC susceptibility remains controversial, and strong evidence-based guidelines for carriers are not yet available. Herein, we present a comprehensive catalog of BARD1 PVs identified in large cumulative cohorts of ~48,700 BC and ~20,800 OC cases (retrieved from 123 studies examining the whole coding sequence of BARD1). Using these resources, we compared the frequency of BARD1 PVs in the cases and ~134,100 controls from the gnomAD database and estimated the effect of the BARD1 PVs on BC and OC risks. The analysis revealed that BARD1 is a BC moderate-risk gene (odds ratio (OR) = 2.90, 95% CIs:2.25–3.75, p < 0.0001) but not an OC risk gene (OR = 1.36, 95% CIs:0.87–2.11, p = 0.1733). In addition, the BARD1 mutational spectrum outlined in this study allowed us to determine recurrent PVs and evaluate the variant-specific risk for the most frequent PVs. In conclusion, these precise estimates improve the understanding of the role of BARD1 PVs in BC and OC predisposition and support the need for BARD1 diagnostic testing in BC patients.

The identification of germline copy number variants (CNVs) by targeted next-generation sequencing (NGS) frequently relies on in silico CNV prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools, including one commercial (Sophia Genetics DDM) and three non-commercial tools (ExomeDepth, GATK gCNV, panelcn.MOPS) in 17 cancer predisposition genes in 4208 female index patients with familial breast and/or ovarian cancer (BC/OC). CNV predictions were verified via multiplex ligation-dependent probe amplification. We identified 77 CNVs in 76 out of 4208 patients (1.81%); 33 CNVs were identified in genes other than BRCA1/2, mostly in ATM, CHEK2, and RAD51C and less frequently in BARD1, MLH1, MSH2, PALB2, PMS2, RAD51D, and TP53. The Sophia Genetics DDM software showed the highest sensitivity; six CNVs were missed by at least one of the non-commercial tools. The positive predictive values ranged from 5.9% (74/1249) for panelcn.MOPS to 79.1% (72/91) for ExomeDepth. Verification of in silico predicted CNVs is required due to high frequencies of false positive predictions, particularly affecting target regions at the extremes of the GC content or target length distributions. CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further BC/OC predisposition genes.