Understanding Germ-Line Mutations in<i>BRCA1</i>

Szabo, Csilla I.; Worley, Terri; Monteiro, Alvaro N.A.

doi:10.4161/cbt.3.6.841

Cited by 34 publications

(27 citation statements)

References 84 publications

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“…2). This region displays relatively low conservation across other BRCA1 orthologues with no recognizable structural motif and was therefore expected to be more tolerant to changes (32). Variants R1443G, P1614S, and E1644G showed transcription activation levels equal or higher than wt BRCA1 whereas V1534M, D1546N, and L1564P had lower activity (between 60% and 80% of the wt activity) in yeast ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Determination of Cancer Risk Associated with Germ Line BRCA1 Missense Variants by Functional Analysis

et al. 2007

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Germ line inactivating mutations in BRCA1 confer susceptibility for breast and ovarian cancer. However, the relevance of the many missense changes in the gene for which the effect on protein function is unknown remains unclear. Determination of which variants are causally associated with cancer is important for assessment of individual risk. We used a functional assay that measures the transactivation activity of BRCA1 in combination with analysis of protein modeling based on the structure of BRCA1 BRCT domains. In addition, the information generated was interpreted in light of genetic data. We determined the predicted cancer association of 22 BRCA1 variants and verified that the common polymorphism S1613G has no effect on BRCA1 function, even when combined with other rare variants. We estimated the specificity and sensitivity of the assay, and by meta-analysis of 47 variants, we show that variants with <45% of wild-type activity can be classified as deleterious whereas variants with >50% can be classified as neutral. In conclusion, we did functional and structure-based analyses on a large series of BRCA1 missense variants and defined a tentative threshold activity for the classification missense variants. By interpreting the validated functional data in light of additional clinical and structural evidence, we conclude that it is possible to classify all missense variants in the BRCA1 COOH-terminal region. These results bring functional assays for BRCA1 closer to clinical applicability.

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Section: Resultsmentioning

confidence: 99%

Determination of Cancer Risk Associated with Germ Line BRCA1 Missense Variants by Functional Analysis

et al. 2007

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“…Inherited mutations in this gene have been associated with an increased lifetime risk of breast and ovarian cancer (6-8 times that of the general population) [4]. There are several thousand known deleterious BRCA1 mutations that result in frameshifts and/or premature stop codons, producing a truncated protein product [5]. In contrast, the functional impact of most missense variants that result in a single amino acid residue change in BRCA1 protein is not known.…”

Section: Introductionmentioning

confidence: 99%

Functional impact of missense variants in BRCA1 predicted by supervised learning

Karchin¹,

Monteiro²,

Tavtigian³

et al. 2005

PLoS Comput Biol

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Many individuals tested for inherited cancer susceptibility at the BRCA1 gene locus are discovered to have variants of unknown clinical significance (UCVs). Most UCVs cause a single amino acid residue (missense) change in the BRCA1 protein. They can be biochemically assayed, but such evaluations are time-consuming and labor-intensive. Computational methods that classify and suggest explanations for UCV impact on protein function can complement functional tests. Here we describe a supervised learning approach to classification of BRCA1 UCVs. Using a novel combination of 16 predictive features, the algorithms were applied to retrospectively classify the impact of 36 BRCA1 C-terminal (BRCT) domain UCVs biochemically assayed to measure transactivation function and to blindly classify 54 documented UCVs. Majority vote of three supervised learning algorithms is in agreement with the assay for more than 94% of the UCVs. Two UCVs found deleterious by both the assay and the classifiers reveal a previously uncharacterized putative binding site. Clinicians may soon be able to use computational classifiers such as those described here to better inform patients. These classifiers can be adapted to other cancer susceptibility genes and systematically applied to prioritize the growing number of potential causative loci and variants found by large-scale disease association studies.

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“…Screening is important for genetic counseling in affected families and for early diagnosis or disease prevention in carriers. Most deleterious mutations constitute either small frameshift insertions/deletions or nonsense mutations that give rise to premature stop codons, missense mutations in conserved and functionally important domains, or splice-site mutations resulting in aberrant transcript processing [Szabo et al, 2004;Wang et al, 2003]. Mutations may also comprise more complex rearrangements, including deletions and duplications of large genomic regions, that escape detection using traditional nonquantitative PCR-based mutation screening and sequencing of DNA templates, due to removal of primer sites [Mazoyer, 2005].…”

Section: Introductionmentioning

confidence: 99%

Detection and precise mapping of germline rearrangements inBRCA1, BRCA2, MSH2, andMLH1using zoom-in array comparative genomic hybridization (aCGH)

et al. 2008

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Disease-predisposing germline mutations in cancer susceptibility genes may consist of large genomic rearrangements that are challenging to detect and characterize using standard PCR-based mutation screening methods. Here, we describe a custom-made zoom-in microarray comparative genomic hybridization (CGH) platform of 60mer oligonucleotides. The 4 x 44 K array format provides high-resolution coverage (200-300 bp) of 400-700 kb genomic regions surrounding six cancer susceptibility genes. We evaluate its performance to accurately detect and precisely map earlier described or novel large germline deletions or duplications occurring in BRCA1 (n=11), BRCA2 (n=2), MSH2 (n=7), or MLH1 (n=9). Additionally, we demonstrate its applicability for uncovering complex somatic rearrangements, exemplified by zoom-in analysis of the PTEN and CDKN2A loci in breast cancer cells. The sizes of rearrangements ranged from several 100 kb, including large flanking regions, to <500-bp deletions, including parts of single exons that would be missed by standard multiplex ligation-dependent probe amplification (MLPA) methods. Zoom-in CGH arrays accurately defined the borders of rearrangements, allowing convenient design of primers for sequence determination of the breakpoints. The array platform can be streamlined for a particular application, e.g., focusing on breast cancer susceptibility genes, with increased capacity using multiformat design, and represents a valuable new tool and complement for genetic screening in clinical diagnostics.

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Understanding Germ-Line Mutations inBRCA1

Cited by 34 publications

References 84 publications

Determination of Cancer Risk Associated with Germ Line BRCA1 Missense Variants by Functional Analysis

Determination of Cancer Risk Associated with Germ Line BRCA1 Missense Variants by Functional Analysis

Functional impact of missense variants in BRCA1 predicted by supervised learning

Detection and precise mapping of germline rearrangements inBRCA1, BRCA2, MSH2, andMLH1using zoom-in array comparative genomic hybridization (aCGH)

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