An integrative model for the comprehensive classification of BRCA1 and BRCA2 variants of uncertain clinical significance

Proline variants in the BRCA1 coiled-coil domain disrupt folding and binding to PALB2

Inherited mutations in the genes coding for the tumor suppressor proteins BRCA1 and PALB2 can lead to increased risk of breast and ovarian cancer. Upon DNA damage, these two proteins form a complex to promote double-stranded break repair via homologous recombination. Missense mutations in either BRCA1 or PALB2 that disrupt this important interaction result in loss of effective DNA damage repair and are associated with breast tumorigenesis. However, the overwhelming majority of missense mutations found in the binding domains of these two genes remain classified as variants of unknown significance. Here we report an in vitro assay for assessing the effect of variants of unknown significance on the heterodimerization of PALB2 and BRCA1 that recapitulates the effect of the known deleterious mutations. We apply the assay to several variants of unknown significance in BRCA1 which reveals other mutations in this region that also disrupt binding, including a mutation of a residue not predicted to directly interact with PALB2. Structural analysis indicates that all BRCA1 mutations to proline tested disrupt α-helix formation and therefore are not well tolerated even when located at positions outside of the PALB2-binding interface. This assay and the structural hypothesis described will be helpful for assessing risk for variants identified in the future in the BRCA1/PALB2 interaction domains.

Functional evaluation of BRCA1/2 variants of unknown significance with homologous recombination assay and integrative in silico prediction model

Numerous variants of unknown significance (VUSs) exist in hereditary breast and ovarian cancers. Although multiple methods have been developed to assess the significance of BRCA1/2 variants, functional discrepancies among these approaches remain. Therefore, a comprehensive functional evaluation system for these variants should be established. We performed conventional homologous recombination (HR) assays for 50 BRCA1 and 108 BRCA2 VUSs and complementarily predicted VUSs using a statistical logistic regression prediction model that integrated six in silico functional prediction tools. BRCA1/2 VUSs were classified according to the results of the integrative in vitro and in silico analyses. Using HR assays, we identified 10 BRCA1 and 4 BRCA2 VUSs as low-functional pathogenic variants. For in silico prediction, the statistical prediction model showed high accuracy for both BRCA1 and BRCA2 compared with each in silico prediction tool individually and predicted nine BRCA1 and seven BRCA2 variants to be pathogenic. Integrative functional evaluation in this study and the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines strongly suggested that seven BRCA1 variants (p.Glu272Gly, p.Lys1095Glu, p.Val1653Leu, p.Thr1681Pro, p.Phe1761Val, p.Thr1773Ile, and p.Gly1803Ser) and four BRCA2 variants (p.Trp31Gly, p.Ser2616Phe, p.Tyr2660Cys, and p.Leu2792Arg) were pathogenic. This study demonstrates that integrative evaluation using conventional HR assays and optimized in silico prediction comprehensively classified the significance of BRCA VUSs for future clinical applications.

Saturation genome editing of 11 codons and exon 13 of BRCA2 coupled with chemotherapeutic drug response accurately determines pathogenicity of variants

The unknown pathogenicity of a significant number of variants found in cancer-related genes is attributed to limited epidemiological data, resulting in their classification as variant of uncertain significance (VUS). To date, Breast Cancer gene-2 (BRCA2) has the highest number of VUSs, which has necessitated the development of several robust functional assays to determine their functional significance. Here we report the use of a humanized-mouse embryonic stem cell (mESC) line expressing a single copy of the human BRCA2 for a CRISPR-Cas9-based high-throughput functional assay. As a proof-of-principle, we have saturated 11 codons encoded by BRCA2 exons 3, 18, 19 and all possible single-nucleotide variants in exon 13 and multiplexed these variants for their functional categorization. Specifically, we used a pool of 180-mer single-stranded donor DNA to generate all possible combination of variants. Using a high throughput sequencing-based approach, we show a significant drop in the frequency of non-functional variants, whereas functional variants are enriched in the pool of the cells. We further demonstrate the response of these variants to the DNA-damaging agents, cisplatin and olaparib, allowing us to use cellular survival and drug response as parameters for variant classification. Using this approach, we have categorized 599 BRCA2 variants including 93-single nucleotide variants (SNVs) across the 11 codons, of which 28 are reported in ClinVar. We also functionally categorized 252 SNVs from exon 13 into 188 functional and 60 non-functional variants, demonstrating that saturation genome editing (SGE) coupled with drug sensitivity assays can enhance functional annotation of BRCA2 VUS.

MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model

Implementation of next-generation sequencing (NGS) for the genetic analysis of hereditary diseases has resulted in a vast number of genetic variants identified daily, leading to inadequate variant interpretation and, consequently, a lack of useful clinical information for treatment decisions. Herein, we present MARGINAL 1.0.0, a machine learning (ML)-based software for the interpretation of rare BRCA1 and BRCA2 germline variants. MARGINAL software classifies variants into three categories, namely, (likely) pathogenic, of uncertain significance and (likely) benign, implementing the criteria established by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP). We first annotated BRCA1 and BRCA2 variants using various sources. Then, we automatically implemented the ACMG-AMP criteria, and we finally constructed the ML model for variant classification. To maximize accuracy, we compared the performance of eight different ML algorithms in a classification scheme based on a serial combination of two classifiers. The model showed high predictive abilities with maximum accuracy of 92% and 98%, recall of 92% and 98% and specificity of 90% and 98% for the first and second classifiers, respectively. Our results indicate that using a gene and disease-specific ML automated software for clinical variant evaluation can minimize conflicting interpretations.

Increased Risk of Hereditary Prostate Cancer in Italian Families with Hereditary Breast and Ovarian Cancer Syndrome Harboring Mutations in BRCA and in Other Susceptibility Genes

Hereditary prostate cancer (HPCa) has the highest heritability of any cancer in men. Interestingly, it occurs in several hereditary syndromes, including breast and ovarian cancer (HBOC) and Lynch syndrome (LS). Several gene mutations related to these syndromes have been identified as biomarkers in HPCa. The goal of this study was to screen for germline mutations in susceptibility genes by using a multigene panel, and to subsequently correlate the results with clinical and laboratory parameters. This was undertaken in 180 HBOC families, which included 217 males with prostate cancer (PCa). Mutational analysis was further extended to 104 family members of mutated patients. Screening of HBOC families revealed that 30.5% harbored germline mutations in susceptibility genes, with 21.6% harboring pathogenic variants (PVs) and 8.9% having variants of uncertain significance (VUS). We found PVs at similar frequency in BRCA1 and BRCA2 genes (8.8% and 9.4%, respectively), while 0.56% of PVs were present in well-established susceptibility genes PALB2, TP53 and RAD51C. Moreover, 0.56% of monoallelic PVs were present in MUTYH, a gene whose function in tumorigenesis in the context of PCa is still unclear. Finally, we reported double heterozygosity (DH) in BRCA1/2 genes in a single family, and found double mutation (DM) present in BRCA2 in a separate family. There was no significant difference between the mean age of onset of PCa in HBOC families with or without germline mutations in susceptibility genes, while the mean survival was highest in mutated patients compared to wild type. Furthermore, PCa is the second most recurrent cancer in our cohort, resulting in 18% of cases in both mutated and non-mutated families. Our investigation shows that PVs were located mostly in the 3′ of BRCA1 and BRCA2 genes, and in BRCA2, most PVs fell in exon 11, suggesting a mutation cluster region relating to risk of HPCa. A total of 65 family members inherited the proband’s mutation; of these, 24 developed cancer, with 41 remaining unaffected.