bioRxivGenomicsPreprint
Saturation genome editing-based functional evaluation and clinical classification of BRCA2 single nucleotide variants
Huaizhi HuangiD, Chunling HuiD, Jie NaiD, Steven N. HartiD, Rohan David GnanaolivuiD, Mohamed Abozaid, Tara Rao, Yohannes A. Tecleab, Tina F. PesaraniD, Paulo Cilas Morais Lyra JunioriD, Rachid KaramiD, Siddhartha YadaviD, Susan M. DomchekiD, Miguel de la HoyaiD, Mark E. RobsoniD, Miika M. MehineiD, Chaitanya BandlamudiiD, Diana L. MandelkeriD, Álvaro N.A. MonteiroiD, Nicholas James BoddickeriD, Wenan CheniD, Marcy E. RichardsoniD, Fergus J. CouchiD
Abstract
Germline BRCA2 loss-of function (LOF) variants identified by clinical genetic testing predispose to breast, ovarian, prostate and pancreatic cancer. However, variants of uncertain significance (VUS) (n>4000) limit the clinical use of testing results. Thus, there is an urgent need for functional characterization and clinical classification of all BRCA2 variants. Here we report on comprehensive saturation genome editing-based functional characterization of 97% of all possible single nucleotide variants (SNVs) in the BRCA2 DNA Binding Domain hotspot for pathogenic missense variants that is encoded by exons 15 to 26. The assay was based on deep sequence analysis of surviving endogenously targeted haploid cells. A total of 7013 SNVs were characterized as functionally abnormal (n=955), intermediate/uncertain, or functionally normal (n=5224) based on 95% agreement with ClinVar known pathogenic and benign standards. Results were validated relative to batches of nonsense and synonymous variants and variants evaluated using a homology directed repair (HDR) functional assay. Breast cancer case-control association studies showed that pooled SNVs encoding functionally abnormal missense variants were associated with increased risk of breast cancer (odds ratio (OR) 3.89, 95%CI: 2.77-5.51). In addition, 86% of tumors associated with abnormal missense SNVs displayed loss of heterozygosity (LOH), whereas 26% of tumors with normal variants had LOH. The functional data were added to other sources of information in a ClinGen/ACMG/AMP-like model and 700 functionally abnormal SNVs, including 220 missense SNVs, were classified as pathogenic or likely pathogenic, while 4862 functionally normal SNVs, including 3084 missense SNVs, were classified as benign or likely benign. These classified variants can now be used for risk assessment and clinical care of variant carriers and the remaining functional scores can be used directly for clinical classification and interpretation of many additional variants. SummaryGermline BRCA2 loss-of function (LOF) variants identified by clinical genetic testing predispose to several types of cancer. However, variants of uncertain significance (VUS) limit the clinical use of testing results. Thus, there is an urgent need for functional characterization and clinical classification of all BRCA2 variants to facilitate current and future clinical management of individuals with these variants. Here we show the results from a saturation genome editing (SGE) and functional analysis of all possible single nucleotide variants (SNVs) from exons 15 to 26 that encode the BRCA2 DNA Binding Domain hotspot for pathogenic missense variants. The assay was based on deep sequence analysis of surviving endogenously targeted human haploid HAP1 cells. The assay was calibrated relative to ClinVar known pathogenic and benign missense standards and 95% prevalence thresholds for functionally abnormal and normal variants were identified. Thresholds were validated based on nonsense and synonymous variants. SNVs encoding functionally abnormal missense variants were associated with increased risks of breast and ovarian cancer. The functional assay results were integrated into a ClinGen/ACMG/AMP-like model for clinical classification of the majority of BRCA2 SNVs as pathogenic/likely pathogenic or benign/likely benign. The classified variants can be used for improved clinical management of variant carriers.
- organism: human
- assay: whole-exome sequencing
- research focus: variant effect prediction
- approach: experimental assay
- Citations
- 5
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