Functional evaluation and clinical classification of BRCA2 variants

Abstract

Germline BRCA2 loss-of function variants, which can be identified through clinical genetic testing, predispose to several cancers^1-5. However, variants of uncertain significance limit the clinical utility of test results. Thus, there is a need for functional characterization and clinical classification of all BRCA2 variants to facilitate the clinical management of individuals with these variants. Here we analysed all possible single-nucleotide variants from exons 15 to 26 that encode the BRCA2 DNA-binding domain hotspot for pathogenic missense variants. To enable this, we used saturation genome editing CRISPR-Cas9-based knock-in endogenous targeting of human haploid HAP1 cells⁶. The assay was calibrated relative to nonsense and silent variants and was validated using pathogenic and benign standards from ClinVar and results from a homology-directed repair functional assay⁷. Variants (6,959 out of 6,960 evaluated) were assigned to seven categories of pathogenicity based on a VarCall Bayesian model⁸. Single-nucleotide variants that encode loss-of-function missense variants were associated with increased risks of breast cancer and ovarian cancer. The functional assay results were integrated into models from ClinGen, the American College of Medical Genetics and Genomics, and the Association for Molecular Pathology⁹ for clinical classification of BRCA2 variants. Using this approach, 91% were classified as pathogenic or likely pathogenic or as benign or likely benign. These classified variants can be used to improve clinical management of individuals with a BRCA2 variant.

Fig. 1. Schematic overview of the SGE MAVE of all SNVs in the BRCA2 DBD.

a, Design of the SGE experiment and the targeted regions. All possible SNVs were introduced and assessed in exon 15 (E15) to E26 encoding the BRCA2 DBD domain, along with 10 bp of adjacent intronic nucleotides for each exon. E18 and E25 were divided into 2 regions, which resulted in a total of 14 target regions. b, Schematic of the SGE workflow. In each target region, a SNV library that contained all possible SNVs was transfected with a corresponding Cas9–sgRNA construct into HAP1 haploid cells. gDNA was extracted at D5 and D14 after transfection, and the target region was amplified and barcoded for targeted gDNA sequencing. SNV abundance was evaluated and normalized to generate functional scores for all SNVs. An ACMG–AMP classification model was applied to formally classify SNVs based on the results of the MAVE functional assays and other evidence. The schematics in this figure were created using BioRender (credit: C.H., https://BioRender.com/u10b291; 2024).

Fig. 2. Functional annotation of BRCA2 SNVs.

a, Distribution of raw functional scores of 6,959 SNVs coloured by variant type. b, Distribution of adjusted functional scores for all variants from the VarCall model. c, Model-based functional score distribution by variant type in each exon. Colour indicates variant type. d, Bar chart illustrating the percentage of each variant type in each of the seven functional categories. Colour indicates functional categories. e, Bar chart illustrating the percentage of SNVs by functional category in 14 target regions. Colour indicates functional categories.

Fig. 3. Comparison of BRCA2 MAVE data with data from functional assays and in silico predictors.

a–d, Boxplots showing functional scores of SNVs encoding missense variants compared with a BRCA2^–/– V-C8 HDR assay (a), a DLD1 BRCA2^–/– olaparib sensitivity assay (b), a prime-editing-based haploid cell-survival assay (c) and a mouse Brca2^–/– embryonic stem cell complementation assay (d). The numbers of variants of each type resulting from the individual assays are shown. Functionally abnormal variants have significantly lower functional scores than functionally normal variants in a (P = 1.6 × 10⁻⁵²), b (P = 2.0 × 10⁻¹¹), c (P = 3.4 × 10⁻⁸) and d (P = 1.1 × 10⁻⁴), using two-sided Mann–Whitney–Wilcoxon tests. P values for all comparisons are shown. Boxes represent the interquartile range, the horizontal line is the median functional score, and whiskers show maximum and minimum values. Variants are shown as points and coloured by the functional strength of the evidence category. e, Comparison of the AUC values between MAVE and two in silico predictors (AlphaMissense and BayesDel) using ClinVar-classified missense standards (n = 70). f, Comparison of the AUC values between MAVE and two in silico predictors (AlphaMissense and BayesDel) using missense variants characterized using a well-calibrated HDR assay (n = 417).

Fig. 4. Clinical classification of BRCA2 SNVs.

a, Sankey plot illustrating the clinical classification of SNVs after integration of BRCA2 MAVE functional data into the ClinGen BRCA1/2 VCEP ACMG–AMP classification framework. The numbers of SNVs for functional categories in each variant type are shown in the left-hand MAVE column. The numbers of variants in the classification category are shown in the right-hand ACMG column. b, Sankey plot illustrating the changes in variant classification status in ClinVar before (left) and after (right) incorporating BRCA2 MAVE functional results into the BRCA1/2 VCEP ACMG–AMP classification framework.

Extended Data Fig. 1. Functional effects of SNVs on the BRCA2 protein.

A, Heatmap of functional categories (colour) for all possible amino acid substitutions encoded by SNVs. B, Cross-species sequence conservation from pufferfish to Homo sapiens (n = 10) relative to frequency of P_Strong missense variants (perfectly conserved: 100% identity across 10 species; highly conserved: 80% or 90% identity; poorly conserved: ≤70% identity). C–G, BRCA2 3-dimensional protein ribbon diagrams showing the frequency of P_Strong missense variants encoded by SNVs at each amino acid in the Helical (C), OB1 (D), OB2 (E), OB3 (F) domains, and the BRCA2-DSS1-ssDNA complex (PBD 1MJE) (G). Colour denotes the frequency of P_Strong missense alterations (green: 0%; yellow: <25%; orange: 25-49.9%; red: ≥50%). The subdomains were oriented to maximize views of the functionally pathogenic missense alterations. The BRCA2-DSS1-ssDNA complex is shown from N-terminus (left) to C-terminus (right).

Extended Data Fig. 2. Lifetime risks of breast and ovarian cancer associated with categories of pathogenic and benign variants.

A,B, Lifetime risk estimates for breast cancer (A) and ovarian cancer (B) associated with categories (P_Strong, P_Strong/Moderate/Supporting, B_Strong, B_Strong/Moderate/Supporting) of BRCA2 DNA binding domain SNVs from the BRCA2 MAVE study. Standards included known pathogenic (all protein truncating alterations), known benign (benign variants established by the ClinGen BRCA1/2 VCEP), general population breast/ovarian (age related risks of these cancers from the general SEER registry).

Extended Data Fig. 3. Comparisons of variant classifications from two MAVE studies.

Sankey plot of ClinGen/ACMG/AMP BRCA1/2 VCEP-based classification of commonly evaluated BRCA2 DBD SNVs from two independent MAVE studies (our study of HAP1 cells (Huang et al.), and Sahu et al.’s study of ES cells).