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Updated: Jun 12, 2026

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors
Published on: February 28, 2021
Comprehensive analysis of missense variations in the BRCT domain of BRCA1 by structural and functional assays
Megan S Lee1, Ruth Green, Sylvia M Marsillac
1Department of Biochemistry, School of Systems Molecular Medicine, University of Alberta, Edmonton, Alberta, Canada.
Abstract:
Genetic screening of the breast and ovarian cancer susceptibility gene BRCA1 has uncovered a large number of variants of uncertain clinical significance. Here, we use biochemical and cell-based transcriptional assays to assess the structural and functional defects associated with a large set of 117 distinct BRCA1 missense variants within the essential BRCT domain of the BRCA1 protein that have been documented in individuals with a family history of breast or ovarian cancer. In the first method, we used limited proteolysis to assess the protein folding stability of each of the mutants compared with the wild-type. In the second method, we used a phosphopeptide pull-down assay to assess the ability of each of the variants to specifically interact with a peptide containing a pSer-X-X-Phe motif, a known functional target of the BRCA1 BRCT domain. Finally, we used transcriptional assays to assess the ability of each BRCT variant to act as a transcriptional activation domain in human cells. Through a correlation of the assay results with available family history and clinical data, we define limits to predict the disease risk associated with each variant. Forty-two of the variants show little effect on function and are likely to represent variants with little or no clinical significance; 50 display a clear functional effect and are likely to represent pathogenic variants; and the remaining 25 variants display intermediate activities. The excellent agreement between the structure/function effects of these mutations and available clinical data supports the notion that functional and structure information can be useful in the development of models to assess cancer risk.
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