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Abstract 


Missense substitutions in high-risk cancer susceptibility genes create clinical uncertainty in the genetic counseling process. Multifactorial likelihood classification approaches and in vitro assays are useful for the classification of exonic sequence variants in BRCA1 and BRCA2, but these currently rely on the assumption that changes in protein function are the major biological mechanism of pathogenicity. This study investigates the potentially pathogenic role of aberrant splicing for exonic variants predicted to encode missense substitutions using patient-derived RNA. No splicing aberrations were identified for BRCA1c.5054C>T and BRCA2c.7336A>G, c.8839G>A, and c.9154C>T. However, RT-PCR analysis identified a major splicing aberration for BRCA1c.4868C>G(p.Ala1623Gly), a variant encoding a missense substitution considered likely to be neutral. Splicing aberrations were also observed for BRCA2c.7988A>T(p.Glu2663Val) and c.8168A>G(p.Asp2723Gly), but both variant and wildtype alleles were shown to be present in full-length mRNA transcripts, suggesting that variant protein may be translated. BRCA2 protein function assays indicated that BRCA2p.Glu2663Val, p.Asp2723Gly and p.Arg3052Trp missense proteins have abrogated function consistent with pathogenicity. Multifactorial likelihood analysis provided evidence for pathogenicity for BRCA1 c.5054C>T(p.Thr1685Ile) and BRCA2c.7988A>T(p.Glu2663Val), c.8168A>G(p.Asp2723Gly) and c.9154C>T(p.Arg3052Trp), supporting experimentally derived evidence. These findings highlight the need for improved bioinformatic prediction of splicing aberrations and to refine multifactorial likelihood models used to assess clinical significance.

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Hum Mutat. Author manuscript; available in PMC 2011 Jan 17.
Published in final edited form as:
PMCID: PMC3021973
NIHMSID: NIHMS225236
PMID: 20513136

Detection of Splicing Aberrations Caused by BRCA1 and BRCA2 Sequence Variants Encoding Missense Substitutions: Implications for Prediction of Pathogenicity

Abstract

Missense substitutions in high-risk cancer susceptibility genes create clinical uncertainty in the genetic counseling process. Multifactorial likelihood classification approaches and in vitro assays are useful for the classification of exonic sequence variants in BRCA1 and BRCA2, but these currently rely on the assumption that changes in protein function are the major biological mechanism of pathogenicity. This study investigates the potentially pathogenic role of aberrant splicing for exonic variants predicted to encode missense substitutions using patient-derived RNA. No splicing aberrations were identified for BRCA1c.5054C>T and BRCA2c.7336A>G, c.8839G>A, and c.9154C>T. However, RT-PCR analysis identified a major splicing aberration for BRCA1c.4868C>G(p.Ala1623Gly), a variant encoding a missense substitution considered likely to be neutral. Splicing aberrations were also observed for BRCA2c.7988A>T(p.Glu2663Val) and c.8168A>G(p.Asp2723Gly), but both variant and wildtype alleles were shown to be present in full-length mRNA transcripts, suggesting that variant protein may be translated. BRCA2 protein function assays indicated that BRCA2p.Glu2663Val, p.Asp2723Gly and p.Arg3052Trp missense proteins have abrogated function consistent with pathogenicity. Multifactorial likelihood analysis provided evidence for pathogenicity for BRCA1 c.5054C>T(p.Thr1685Ile) and BRCA2c.7988A>T(p.Glu2663Val), c.8168A>G(p.Asp2723Gly) and c.9154C>T(p.Arg3052Trp), supporting experimentally derived evidence. These findings highlight the need for improved bioinformatic prediction of splicing aberrations and to refine multifactorial likelihood models used to assess clinical significance.

Keywords: BRCA1, BRCA2, clinical significance, variants, splicing

INTRODUCTION

The breast cancer predisposition genes, BRCA1 (MIM# 113705) and BRCA2 (MIM# 600185) are often sequenced in probands from families presenting with multiple cases of breast cancer. Clearly pathogenic changes such as nonsense or frameshift mutations are identified in some probands, however many rare sequence variants of unknown clinical significance are also reported. Approximately 1,500 distinct sequence variants in BRCA1/2 are reported on the Breast Cancer Information Core (BIC) database as having unknown clinical significance (Easton, et al., 2007). Such unclassified variants include missense changes, small in-frame insertions or deletions or potential splice site alterations, and are problematic for cancer risk estimation and clinical management (Schwartz, et al., 2008).

Unclassified variants of BRCA1 and BRCA2 may be evaluated using a multifactorial likelihood model (Goldgar, et al., 2004), which integrates data from several approaches targeting independent characteristics associated with known pathogenic sequence variants. The model can include data from segregation analysis of variants with disease, amino acid evolutionary conservation and physico-chemical properties, morphological and molecular phenotypes of tumour and family history (Abkevich, et al., 2004; Chenevix-Trench, et al., 2006; Easton, et al., 2007; Farrugia, et al., 2008; Goldgar, et al., 2008; Goldgar, et al., 2004; Gomez Garcia, et al., 2009; Lakhani, et al., 2002; Osorio, et al., 2007; Spurdle, et al., 2008b). In vitro assays assessing the effect of a sequence variant on splicing or protein activity can also contribute to classification by offering molecular evidence for the effect of a variant, especially where data for multifactorial modelling is limited. Such assays, along with in silico assessment of the effect of the variant on mRNA splicing or protein structure/function may help define the molecular role of an unclassified variant (Couch, et al., 2008; Lovelock, et al., 2007; Phelan, et al., 2005). Assays to assess aberrant splicing may identify BRCA1 or BRCA2 variants that result in the production of a transcript that is susceptible to nonsense-mediated decay or the production of a splice product that will be translated into a truncated protein, both of which are generally considered to be clinically pathogenic (Xu, et al., 1997).

Although web-based programs have a role in the prediction of splicing aberrations and may become stand-alone diagnostic tools, it is currently important for in vitro splicing assays to be conducted alongside the bioinformatic predictions to calibrate and estimate the sensitivity and specificity of the predictions made. This is largely because bioinformatic tools currently perform relatively poorly with respect to the recognition of cryptic splice site use or identification of sequence variants that may alter splicing enhancer or silencer sites. In addition, these tools provide no information on the potential extent of aberrant splicing from a quantitative perspective, including the impact of a variant on the production of naturally occurring alternative transcripts. The latter is of considerable importance, given that 14 naturally occurring splice isoforms exist for BRCA1 and seven for BRCA2, and variants within splicing enhancer/silencer sequences or in regions proximal to the splice junctions have the potential to affect the regulation of natural isoform expression. An example is the increased expression of the BRCA2 ΔExon 18 isoform created by the variant BRCA2 c.7977-1G>C (Tesoriero, et al., 2005).

Classifying variants that cause dysregulated expression of natural isoforms is particularly challenging since the minimum alteration in transcript expression that predisposes to cancer development has not been established. Moreover, for cases where an exonic DNA variant causes increased isoform expression by disrupting an exonic splice enhancer (ESE), but also encodes a missense change, the basis for pathogenicity may be additionally unclear. In these cases, a dual basis for pathogenicity is plausible.

We undertook a study to assess the clinical significance of a panel of exonic BRCA1 and BRCA2 variants predicted to encode missense substitutions, including extensive splicing assays to investigate if variants were associated with splicing aberrations. In addition, for a subset of variants that transcribed full-length transcript encoding the missense substitution, commonly used BRCA2 functional assays were employed to measure the influence of the amino acid substitution on homologous recombination repair activity of BRCA2 and the ability of BRCA2 to regulate cell division via control of centrosome duplication.

METHODS

Subjects

Five Australian families were ascertained as eligible for research by kConFab (http://www.kconfab.org/Index.shtml) (Mann, et al., 2006), two from Mayo Clinic in the United States, and one jointly from St Georges University of London and The University of Southampton in the United Kingdom. All families were initially identified via family cancer clinics, and all participants provided written informed consent. Families included in this study were selected because of the presence of an unclassified sequence variant in the proband. Variants studied are shown in Table 1. Nucleotide numbering reflects cDNA numbering with +1 corresponding to the A of the ATG translation initiation codon in the reference sequence of BRCA1 (GenBank accession #NM_007294.3) and BRCA2 (GenBank accession #NM_000059.3), according to journal guidelines (www.hgvs.org/mutnomen). The initiation codon is codon 1. The site of recruitment was as follows: Mayo Clinic, I family each with BRCA1 c.4868C>G (p.Ala1623Gly) and c.5054C>T (p.Thr1685Ile); UK clinics, BRCA1 c.4868C>G (p.Ala1623Gly); kConFab, all remaining BRCA2 variants. Splicing assays were conducted on mRNA from Epstein Barr Virus transformed lymphoblastoid cell lines (LCLs) from the variant carrier proband from each family, and the analysis was repeated on a second carrier for BRCA2 c.7988A>T p.Glu2663Val. In addition, for the additional family with BRCA1 c.4868C>G (p.Ala1623Gly) recruited in the UK, clinical splicing assays were conducted on lymphocyte mRNA from three variant carriers.

Table 1

Comparison of bioinformatic splice prediction consensus values with in vitro analysis

VARIANTHuman Splicing
Findera
MaxEntbESE FinderESE
Rescue
In vitro
analysis

VariantProximal
consensus
site
VariantProximal
consensus
site
BRCA1

c.4868C>G
(p.Ala1623Gly)
85.75
(46%)
81.246.29
(420%)
5.91Multiple
sites broken
No
change
119bp
deletion of
exon 16
c.5054C>T
(p.Thr1685Ile)
NSCNSCNSCNSCMultiple
sites broken
No
change
No aberrant
splicing
BRCA2

c.7336A>G
(p.Lys2446Glu)
NSCNSCNSCNSCNo change2× new
sites
No aberrant
splicing
c.7988A>T
(p.Glu2663Val)
86.88
(49%)
81.987.31
(950%)
8.881 site brokenNo
change
Up-
regulation of
isoforms
c.8168A>G
(p.Asp2723Gly)
86.88
(42%)
90.58.56
(2153%)
8.881 site
broken
Site
broken
163 bp
deletion of
exon 18
c.8839G>A
(p.Glu2947Lys)
NSCNSCNSCNSCNSF3× sites
broken,
1× new
site
No aberrant
splicing
c.9154C>T
(p.Arg3052Trp)
NSCNSCNSCNSC2× sites
broken
No
change
No aberrant
splicing
aPercent difference between wildtype and variant values <5% were excluded from study.
bPercent difference between wildtype and variant values <25% were excluded from study.

Abbreviations: NSC, no sites created; NSF, no sites found.

Nucleotide numbering reflects cDNA numbering with +1 corresponding to the A of the ATG translation initiation codon in the reference sequence of BRCA1 (GenBank accession #NM_007294.3) and BRCA2 (GenBank accession #NM_000059.3), according to journal guidelines (www.hgvs.org/mutnomen). The initiation codon is codon 1.

Bioinformatic analysis of variant sequences

To predict the effect of each variant on mRNA splicing we utilized Human Splicing Finder version 2.4 (www.umd.be/HSF) (Desmet, et al., 2009) which calculates consensus values of potential variant affected mRNA splice sites and splice regulatory sites using different algorithms, including Human Splicing Finder, MaxEnt (Yeo and Burge, 2004), ESE Rescue (Fairbrother, et al., 2002) and ESE Finder (Cartegni, et al., 2003).

Identification of splicing aberrations

For assays conducted in Brisbane, culture of LCLs were conducted with and without cycloheximide. Treated LCLs were grown in the presence of cycloheximide (100 mg/ml) for 4 hours in order to stabilise mutant mRNA (Bateman, et al., 1999). RNA was extracted from cycloheximide treated and untreated cell lines using the RNeasy Mini Kit (Qiagen, Doncaster, Victoria, Australia), according to the manufacturer’s instructions. Each RNA sample was treated with DNase to reduce DNA contamination using DNA-free Kit (Ambion, Austin, TX, USA). cDNA was synthesised using Superscript III First Strand Synthesis System (Invitrogen, Carlsbad, CA, USA). PCR was performed using Amplitaq Gold (Applied Biosystems, Scoresby, Victoria, Australia) under the following conditions: 95°C for 7 minutes followed by 35 cycles of 94°C for 30 seconds, 55°C for 30 seconds and 72°C for 1 minute and a final extension step at 72°C for 7 minutes using primers listed in Supp. Table S1. The location of primers used are illustrated in Supp. Figure S1. PCR products were purified using QIAquick PCR Purification Kit (Qiagen), and sequenced using Big-Dye Terminator version 3.1 sequencing chemistry and the ABI 377 sequencer (Applied Biosystems, Australia). Aberrant splice products from BRCA2 c.8168A>G (p.Asp2723Gly) were cloned using pGEM®-T Easy Vector (Promega Corporation, Madison, WI, USA) according to the manufacturers instructions. Recombinant clones were PCR amplified from a single colony and sequenced as above. Aberrant splice products from BRCA1 c.4868C>G p.Ala1623Gly and BRCA2 c.7988A>T (p.Glu2663Val) were excised using QIAquick Gel Extraction Kit (Qiagen) and re-amplified using PCR under the conditions outlined above and sequenced. Fourteen non-variant carrying control LCLs were used for each RT-PCR. Reactions were performed in duplicate from two separate LCL cultures.

For the UK carriers of BRCA1 c.4868C>G p.Ala1623Gly, RNA was extracted from untransformed lymphocytes by the TRIzol method (Invitrogen) and cDNA was reverse transcribed by using random primers. RT-PCR was performed on the cDNA using PCR primers located in BRCA1 exon 15 and exon 17 (Supp. Table S1). Banding patterns were compared to that of 30 normal controls by agarose gel electrophoresis, and RT-PCR products of the two bands detected in the variant carrier were extracted, purified (Qiagen), and sequenced.

Quantitation of natural splice isoforms

Real-time PCR reactions were carried out in a Lightcycler 480 (Roche, Castle Hill, NSW, Australia) using Platinum SYBR Green qPCR SuperMix-UDG (Invitrogen). Isoform specific primer sequences are listed in Supp. Table S1 and primer design is illustrated in Supp. Figure S1. The house keeping genes GAPDH and EEF1A1 were used as internal references for normalization. Each sample was run in quadruplicate. Normalized expression values were obtained using the Lightcycler 480 Gene Scanning software. Seven to nine non-variant carrying controls were used for cycloheximide treated and untreated samples respectively.

Quantitation of the variant and wildtype allele in c.7988A>T (p.Glu2663Val) full-length transcripts

Double stranded cDNA was synthesised for the restriction enzyme digestion assay of c.7988A>T (p.Glu2663Val) using the Illumina TotalPrep RNA amplification kit (Ambion), modified by omitting the final in vitro transcription step. cDNA was digested for 2 hours using 450 ng of cDNA at 65°C and 2 units of TaaI (New England Biolabs, Ipswich, UK) per 20 ul reaction. Digestion products were used as template cDNA for real-time PCR using conditions mentioned above and primers detailed in Supp. Table S1. Data were normalized to the housekeeping gene EEF1A1. To account for the possible amplification of background single stranded (ss)-cDNA, primers were designed to target a GAPDH sequence that is digested by TaaI in the ds-cDNA. Approximately 100-fold reduction in GAPDH levels was observed after TaaI digestion indicating that most of the ss-cDNA was converted to ds-cDNA, and thus ss-cDNA was unlikely to have contributed significantly to the level of full length BRCA2 isoform measured after TaaI digestion.

Identification of the variant and wildtype allele in BRCA1 c.4868C>G p.Ala1623Gly in full-length transcripts

The full-length band of the RT-PCR product was gel purified and the DNA was cloned into the TOPO vector (Invitrogen). After transformation and growing on a LB-amp plate, sixteen colonies were picked. Miniprep DNAs were amplified and sequenced.

Functional assays of missense substitutions

Assays of protein function were carried out using methods described previously (Farrugia et al., 2008). These are summarized in brief below.

In vitro homologous recombination assay

V-C8-DR-GFP cells were transfected with either pcDNA3.1 vector, pcBASce1 vector containing the I-SceI restriction endonuclease gene, or pcBAsce1 plus various FLAG tagged BRCA2-pcDNA3.1 constructs. After 72 h, cells were harvested and the number of green fluorescent protein (GFP)–expressing cells was assessed by flow cytometry. In parallel, we determined transfection/expression efficiency for BRCA2 by fluorescently labeling cells from these transfection experiments with an anti-FLAG antibody and counting the number of FLAG-BRCA2–expressing cells per 1,000 cells using a fluorescence microscope. The ratio of GFP-expressing cells induced by wildtype or mutant BRCA2 compared with vector control in the homologous recombination assay was then plotted after adjustment for transfection efficiency.

Centrosome amplification assays

293T cells were cultured on glass cover slips and transfected with FLAG-tagged BRCA2-pcDNA3.1 wildtype and mutant constructs using Fugene 6 according to manufacturer’s instructions. For indirect immunofluorescence, cells were fixed with cold methanol, permeabilized, and stained with primary anti-centrin-2 (1:800) polyclonal (MC1, kindly provided by Dr. Jeffrey Salisbury) and anti-FLAG monoclonal (Santa Cruz Biotechnologies, Santa Cruz, CA, USA) antibodies 72 hr after transfection. Alexa 568 goat anti-mouse and 488 goat anti-rabbit secondary antibodies were subsequently added, along with 1mg/ml Hoechst (Molecular Probes). Centriole numbers were counted in a minimum of 100 BRCA2 expressing cells from each of two independent experiments using a Zeiss LSM510 confocal microscope.

Multifactorial likelihood classification

Amino acid sequence conservation and physico-chemical properties, and prior probability of pathogenicity

The prior probability of pathogenicity was derived for each missense substitution, by using A-GVGD classification (agvgd.iarc.fr/index.php) which is based on the severity of alteration in physical and chemical properties and sequence conservation through to the sea urchin, Strongylocentrotus (Tavtigian, et al., 2008).

Segregation

To determine the likelihood of variant causality of disease compared to neutrality, Bayes factor analysis was carried out as described previously (Spurdle, et al., 2008b; Thompson, et al., 2003). Bayes factor scores calculated in an identical manner were available for additional families, as reported previously (Farrugia, et al., 2008).

Tumour histopathology and pathology review

Pathology review was performed as part of kConFab core activities for a subset of tumours. Additional pathology review was performed by two pathologists (SL or L DaS). Estimates of the likelihood of BRCA1 or BRCA2 mutation status were derived for variant carriers using histopathologic features based on the methods described in Spurdle et al. (2008). Briefly, likelihoods are based on the association of histopathologic features reported to be associated with mutation status (Lakhani, et al., 2005; Lakhani, et al., 2002) (Supp. Table S2). In cases where multiple tumours were reviewed for a given individual, only information from the tumour diagnosed at the youngest age was used in the calculation.

Family History

Likelihood ratios were based on the statistical model developed by Easton et al. (2007)(Easton, et al., 2007). The rationale behind the model is that certain key characteristics can be used to predict the presence of a pathogenic mutation within a family, including the disease status of the proband, the age at diagnosis and the number and age of relatives with breast cancer.

Co-occurrence with a pathogenic mutation

Co-occurrence likelihood scores were derived as previously described (Spurdle, et al., 2008b), from a Myriad Genetics Laboratories dataset of 70,000 BRCA1 and BRCA2 tests (Goldgar, et al., 2004).

Calculation of Posterior Probability

Probabilities were derived for each component under the assumption that each factor was statistically independent. The individual likelihood ratios were multiplied to calculate an overall multifactorial likelihood ratio. Bayes factor analysis was then used to calculate a posterior probability that the variant was pathogenic from the multifactorial likelihood ratio and the prior probability. Variants were classified according to the criteria set by Plon et al (Plon, et al., 2008).

RESULTS

The seven exonic variants (Figure 1) were identified by BRCA1/2 mutation screening of familial breast cancer cases recruited into family cancer clinics. All BRCA2 variants create missense changes within the DNA-binding domain and were considered unclassified variants according to the Kathleen Cuningham Foundation Consortium for research into Familial Breast Cancer (KConFab) classification at the time of selection for this study. An additional two BRCA1 unclassified variants were selected for study because they were predicted bioinformatically to increase the likelihood of aberrant splicing, and an LCL from a variant carrier was readily available for splicing assays.

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BRCA1 and BRCA2 exons showing the position of variants studied. BRCA2 variants occur within the DNA-binding domain and BRCA1 variants occur within the transactivation domain.

Bioinformatic predictions and in vitro analysis of splicing aberrations

All variants were screened for potential splicing aberrations using Human Splicing Finder version 2.4 (www.umd.be/HSF, summarised in Table 1), and also assessed using in vitro splicing assays shown in Figure 2. Two of three variants predicted to create a de novo splice donor showed aberrant splicing consistent with bioinformatic predictions. BRCA1 c.4868C>G (p.Ala1623Gly) with MaxEnt scores of 6.29 for the variant splice site ctgGTGGGT, compared with 5.91 for the nearest donor consensus sequence, tttGTGAGT, resulted in a 119bp deletion from exon 16 (Figure 2A). The same findings were observed for BRCA1 c.4868C>G (p.Ala1623Gly) from the UK variant carriers (data not shown). BRCA2 c.8168A>G (p.Asp2723Gly) with MaxEnt scores of 8.56 for the variant site acaGTTGGG and 8.88 for the nearest donor consensus sequence, aagGTAAAT, and resulted in a deletion of 163 bp from exon 18 (Figure 2D). Both variants represent instances where splice sites otherwise unrecognizable by the splice machinery were elevated to a comparable or more likely splice point relative to the nearest site. Both deletions result in loss of the open-reading frame and creation of a stop codon, and were not seen in controls. Each of the seven variants was predicted to create or disrupt an ESE by one or more bioinformatic splice prediction tools, but a role for ESEs was indicated for only BRCA2 c.7988A>T (p.Glu2663Val). This substitution within exon 18 is predicted to disrupt an SRp55 site, and was associated with an elevated level of the two naturally occurring splice isoforms predicted to create a loss of the open reading frame; Δexon 18 (as previously reported by (Farrugia, et al., 2008)), and Δexon 17&18 (Figure 2E).

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RT-PCR analysis of mRNA isolated from cycloheximide treated and untreated LCLs. In all figures, cyclohexamide treated samples are denoted ‘+’ and untreated samples are denoted ‘−’. Lanes showing variant carriers are underlined and all non-variant carrying controls are not underlined (A). Lanes 1&2 represent the BRCA1 c.4868C>G (p.Ala1623Gly) carrier and lanes 3&4 represent the c.5054C>T (p.Thr1685Ile) carrier. (B) Lanes 3&4 represent the BRCA2 c.8839G>A (p.Glu2947Lys) carrier and lanes 5&6 represent the BRCA2 c.9154C>T (p.Arg3052Trp) carrier. (C) Lanes 5–6 represent the BRCA2 c.7336A>G (p.Lys2446Glu) carrier (D) Lanes 3 and 4 represent the BRCA2 c.8168A>G (p.Asp2723Gly) carrier. (E) BRCA2 c.7988A>T (p.Glu2663Val). Lanes 1 and 2 represent the variant carrier. Alternative isoforms representing ΔExon 17&18 and ΔExon 18 are indicated in (D) and (E).

Stability and quantitation analysis of mRNA isoforms for BRCA2 c.7988A>T (p.Glu2663Val)

Cycloheximide was utilized to inhibit translation in vivo to ensure that the mRNA transcripts identified by the nonsense mediated RNA decay (NMD) pathway as truncating would be stabilized for detection by semi-quantitative RT-PCR. Comparison of cycloheximide and non-cycloheximide assays for this variant suggests that the alternative transcripts undergo minimal NMD (Figure 2E), and thus could encode truncated proteins. Real-time PCR was carried out to quantify the levels of Δexon 18 and Δexon 17&18 mRNA isoforms, relative to the full-length native transcript in the c.7988A>T (p.Glu2663Val) variant and controls. Cycloheximide treated cell lines were initially used to assess the relative contribution of each isoform to overall BRCA2 expression (Figure 3A–B). The c.7988A>T (p.Glu2663Val) carriers produced at least a 3–10 fold greater proportion of the Δexon 18 product relative to the full-length isoform when compared to controls not carrying this variant (Figure 3A). A higher level of the ΔExon 17&18 isoform relative to the full-length isoform was also observed in the c.7988A>T (p.Glu2663Val) carriers compared to all but one control (Figure 3B). These results raised the possibility that a higher quantity of the truncated forms of the protein would be produced by the variant carrier compared to individuals without the variant.

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Quantitative real-time PCR of BRCA2 full-length, Δ18 and Δ17&18 splice isoforms. (A–B) Elevated transcript production of Δexon 18 and Δexon 17&18 relative to the full-length isoform seen in BRCA2 c.7988A>T (p.Glu2663Val) compared with controls not carrying the variant. In each case RNA was analysed from cycloheximide treated samples. (C) Total full-length isoform production for BRCA2 c.7988A>T (p.Glu2663Val) carriers and controls not carrying the variant in cycloheximide treated samples showing that the variant carrier produces the full-length isoform within a normal range. (D) The BRCA2 c.7988A>T (p.Glu2663Val) carrier produces a markedly elevated level of the Δ18 isoform when compared to controls. (E) One carrier produces an elevated level of Δexon 17&18 isoform when compared to most of the controls. Error bars represent standard error of the mean.

The expression of the three isoforms (Δexon 18, Δexon 17&18 and full-length) were then normalized to expression of the reference gene GAPDH, to assess relative levels of each the three transcripts (Figure 3C–E). Figure 3(D) shows that the relative level of the Δexon 18 alternative isoform is increased in both of the variant carriers when compared to controls. The relative level of the Δexon 17&18 isoform is also increased in the variant carriers compared to some of the controls assayed (Fig 3E). However, full-length expression by the carrier was within the normal range of that expressed in the controls (Fig 3C). This suggests that, despite the increase in alternative isoform expression, the full-length isoform is expressed at levels similar to those observed in individuals who do not carry the c.7988A>T (p.Glu2663Val) variant. This is consistent with the fact that the full-length transcript predominates in the absence of NMD, comprising greater than 90% of total transcript in the c.7988A>T (p.Glu2663Val) carriers, and greater than 95% in controls (data not shown).

Results were similar for untreated cell lines when real-time PCR data was normalized to GAPDH and an alternative reference gene, EEF1A1 (Supp. Figure S2).

Variant and wildtype full-length transcript expression in BRCA1 c.4868C>G, BRCA2 c.7988A>T, and BRCA2 c.8168A>G carriers

Based on the splicing aberrations observed, these three variants might be interpreted to be pathogenic: BRCA1 c.4868C>G (p.Ala1623Gly) and BRCA2 c.8168A>G (p.Asp2723Gly) create an aberrant splice product encoding a truncated protein, and BRCA2 c.7988A>T (p.Glu2663Val) results in elevated levels of an alternative mRNA isoform encoding a truncated protein. However, we further investigated if both variant and wildtype alleles were expressed in the full-length isoform, to determine if a full-length missense protein could be encoded by variant carriers. Sequencing of the full-length band revealed the presence of both wild-type and variant allele for BRCA1 c.4868C>G (p.Ala1623Gly). Similarly, sequencing of the upper band in Figure 2D identified both alleles for c.8168A>G (p.Asp2723Gly) in the full-length transcript. Sequencing of the 895bp full-length band in Figure 2E also showed evidence that both alleles for c.7988A>T (p.Glu2663Val) were present in the full-length transcript, indicating that both variant and wildtype alleles are expressed and suggesting that both missense and normal BRCA2 protein are likely to be translated in vivo. This is consistent with the fact that full-length transcript was within the normal range in LCLs for carriers of BRCA2 c.7988A>T (p.Glu2663Val).

Assays were then carried out to quantitate the proportion of variant allele expressed as full-length transcript. A double stranded (ds) cDNA-based assay was performed for the c.7988A>T (p.Glu2663Val) variant using TaaI restriction digest of the variant allele followed by real-time PCR. Quantitation of the undigested cDNA was used to represent total full-length transcript and quantitation from the digested cDNA represented wildtype transcript only. As shown in Figure 4, the contribution of the variant allele was reduced compared to the wildtype allele, constituting 39% and 41% of the overall full-length transcript for two related carriers. Furthermore, the relative levels of full length, Δexon 18, and Δexon 17&18 isoforms shown in Figure 3(A–B) were replicated using ds-cDNA as a template, suggesting that cDNA levels were similarly represented in both the ss-cDNA and ds-cDNA (data not shown). Due to the paucity of restriction enzyme sites, it was not possible to design a quantitative variant-specific digestion assay for other variants in the study. However, results from a semi-quantitative cloning-based methodology carried out by the Wessex clinical testing laboratory indicated that the BRCA1 c.4868C>G (p.Ala1623Gly) variant had an incomplete effect on splicing, with 10/15 clones shown to have the wildtype C allele.

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Quantitation of wildtype and variant alleles in BRCA2 c.7988A>T (p.Glu2663Val) following digestion of the variant allele in ds-cDNA by TaaI. The experiment was carried out using ds-cDNA synthesized from two related carriers of the variant.

Functional evaluation of BRCA2 missense substitutions displaying splicing aberrations

The functional consequences of the BRCA2 missense substitutions p.Glu2663Val and p.Asp2723Gly were assessed using results from homologous recombination and centrosome amplification assays, to evaluate whether the missense substitution was likely to be pathogenic. These commonly used assays of BRCA2 protein function were selected since they are considered key indicators of abrogated BRCA2 function. BRCA2 is implicated in homologous repair at sites of double stranded DNA breaks through the interaction with RAD51 (which possesses several activities required for homologous recombination) and single-stranded DNA (Davies, et al., 2001; Wu, et al., 2005), and a lack of functional BRCA2 is shown to lead to gross chromosomal rearrangements indicative of compromised homologous recombination (Patel, et al., 1998). Defective BRCA2 also leads to increased centrosome amplification (Tutt, et al., 1999) recognized as an indicator of micronucleus development resulting from genome instability (Chester, et al., 1998). Abrogation of function observed for either or both of these assays has been observed for known pathogenic variants, such as p.Asp2723His, indicating that these assays are probably independent predictors of BRCA2 protein function (Farrugia, et al., 2008; Wu, et al., 2005).

Results are summarized in Supp. Table S3, and include results from assays conducted as part of this study (for p.Glu2663Val), and assay results previously reported by some of the authors (Farrugia, et al., 2008). Full-length p.Asp2723Gly showed increased centrosome amplification (29% vs 10% for wildtype) and reduced homologous recombination (HR) activity (1.6% vs 6.1% for widltype). These results were similar to those obtained using the known pathogenic p.Asp2723His variant shown in Supp. Table S3 (Farrugia, et al., 2008; Wu, et al., 2005). Full-length p.Arg3052Trp showed reduced HR activity (1.6%) but did not induce significant centrosome amplification (13%). The p.Glu2663Val substitution showed increased centrosome amplification (29%) and reduced homologous repair (HR) activity (1.8%) relative to wildtype BRCA2. The results indicate that these missense substitutions both have the capacity to inactivate BRCA2 and predispose to cancer in the absence of dysregulated splicing.

Posterior probability of pathogenicity

The results from multifactorial likelihood analysis of the variants under study are shown in Table 2. It should be noted that the prior probability of pathogenicity chosen for multifactorial analysis of all these variants was based on the A-GVGD class, which currently does not incorporate the potential for exonic variants to cause splicing aberrations. BRCA1 c.5054C>T (p.Thr1685Ile) and BRCA2 c.7988A>T (p.Glu2663Val), c.8168A>G (p.Asp2723Gly) and c.9154C>T (p.Arg3052Trp) reached a posterior probability of pathogenicity greater than 0.99 and would thus be considered Class 5 pathogenic according to the classification system for sequence variants proposed by the 2008 IARC working group on unclassified genetic variants (Plon, et al., 2008). The pathogenic BRCA2 variants arise within the DNA-binding domain, occur at highly conserved amino acid residues and/or are predicted to create severe physico-chemical changes in this position. The low prior probability (0.01) for BRCA1 c.4868C>G (p.Ala1623Gly) reflects that this variant results in a minor physico-chemical change to the protein. The posterior probability for this variant reached 0.80 considered Class 3, (uncertain clinical significance). It is of interest to note that this variant would almost certainly be considered a Class 5 variant, on the basis of the observed splicing aberration (Spurdle, et al., 2008a) : it produces a major transcript carrying a premature stop codon. BRCA2 c.7336A>G (p.Lys2446Glu) and c.8839G>A (p.Glu2947Lys) were classified as Class 2 (likely not pathogenic), with a posterior probability between 0.001–0.049.

Table 2

Clinical Classification from Multifactorial Likelihood Analysis

VariantExonA-
GVGD
Score
Prior
probability
of the
variant
being
deleterious
*
Likelihood Ratios derived from each componentCombined
odds for
causality
Posterior
probability
of the
variant
being
deleterious
Evidence from
multifactorial
likelihood
analysis**
SegregationTumour
histopath
-ology
Family
history
Co-
occurrence
with a
deleterious
mutation
Farrugia et
al.(Farrugia, et al., 2008)
Easton et
al.
(Easton, et al., 2007)
This
study
BRCA1
c.4868C>G
p.Ala1623Gly
16C00.01--27.721.2310.471.09392.460.80Class 3 -
Uncertain
c.5054C>T
p.Thr1685Ile
17C650.81---2.95125.891.09407.210.99Class 5 -
Pathogenic
BRCA2
c.7336A>G
p.Lys2446Glu
14C00.01--1.061.20N/AN/A1.270.013Class 2 - Likely
not pathogenic
c.7988A>T
p.Glu2663Val
18C650.81363.07138.040.99N/A1.121.51609.600.99Class 5 -
Pathogenic
c.8168A>G
p.Asp2723Gly
18C650.81--0.26N/A75.861.5931.310.99Class 5 -
Pathogenic
c.8839G>A
p.Glu2947Lys
22C00.01--1.21N/AN/AN/A1.210.012Class 2 - Likely
not pathogenic
c.9154C>T
p.Arg3052Trp
24C650.813981.07-0.211.191.621.482447.700.99Class 5 -
Pathogenic
*Prior probability based on A-GVGD score (Tavtigian, et al., 2008).
**Classifications as described in Plon et al (Plon, et al., 2008).

N/A – not available.

The segregation likelihood ratio from Farrugia et al. rather than Easton et al. was utilised when both were available. Tumour histopathology likelihood ratios are based on histopathologic features of reported mutation carrying BRCA1 or BRCA2 tumours (Spurdle, et al., 2008b). Family history scores reflect the presence of key characteristics identified within families carrying a variant used to assess pathogenicity (Easton, et al., 2007). Sequence variants found to co-occur with known pathogenic mutations have a diminished likelihood of pathogenicity as two pathogenic variants in trans is embryonically lethal or in the case of BRCA2 leads to Fanconi Anaemia (Goldgar, et al., 2004). An example calculation of the posterior probability, for variant BRCA1 c.4868C>G, is as follows: Posterior Probability 0.80 = Prior Probability 0.01 × Odds for causality 392.6 ([LR Segregation (27.72) × LR Pathology (1.23) × LR Family History (10.47) × LR Co-occurrence (1.09)]/(1-Prior Probability 0.01)).

DISCUSSION

This detailed study of exonic BRCA1 and BRCA2 missense variants has demonstrated that thorough laboratory investigation is required to assess the mechanism of pathogenicity for the subset of evolutionarily conserved exonic variants observed to cause aberrant splicing. A combination of quantitative isoform-specific real-time PCR, cDNA sequencing, quantitative allele-specific PCR, and protein functional assays were required to show that the BRCA2 c.7988A>T (p.Glu2663Val) variant, predicted to disrupt an ESE, is associated with increased expression of at least one commonly occurring isoform but also expresses normal levels of full-length isoform encoding both wildtype and proven functionally abrogated variant protein. Similarly, RT- PCR, cDNA sequencing, and protein functional assays together allowed us to infer that the BRCA2 c.8168A>G (p.Asp2723Gly) variant is associated with minor levels of aberrantly spliced transcript encoding a truncated protein, with the majority of the variant allele transcribed as full length transcript encoding a missense protein previously reported to have reduced function (Farrugia, et al., 2008). Despite the complexity of functional aberrations associated with these two variants, all lines of evidence indicate that they are pathogenic. The aberrant splicing results in transcripts considered pathogenic, and the encoded missense alteration disrupts BRCA2 function. In addition, multifactorial likelihood analysis classifies both variants as class 5 pathogenic (posterior probability >0.99), even assuming a lower prior probability of 0.81 for a C65 missense substitution (Tavtigian, et al., 2008) rather than an assumed prior of 0.96 for variants likely to cause splicing defects, based on the midpoint of estimates (CI 91% to 100%) for +−1/2 variants highly likely to disrupt splicing (Easton, et al., 2007; Spurdle, et al., 2008a).

This study also demonstrates that splicing aberrations considered to be Class 5 (pathogenic) may be observed for exonic substitutions assumed to encode neutral/low clinical significance missense changes at the protein level. The BRCA1 c.4868C>G (p.Ala1623Gly) (Easton, et al., 2007) missense substitution creates minimal physico-chemical change and is not at a position of high evolutionary conservation, so assignment of a missense prior probability of 0.01 (0–0.06) (Tavtigian, et al., 2008) misinforms the multifactorial model; even a modestly elevated prior that takes into account the sequence analysis observation that c.4868C>G has a higher splice donor quality score than does exon 16’s wt splice donor would have raised the variant from the uncertain class into the pathogenic class. This finding demonstrates the need to incorporate splicing predictions in future developments of the multifactorial likelihood classification model, to prevent misclassification of spliceogenic variants that have no or negligible effect on protein function. It would be advisable, however, that considerable effort be made to improve bioinformatic prediction tools in parallel. The comparison of bioinformatic predictions to observed splicing aberrations in this study highlights the tendency for bioinformatic prediction tools to over predict possible splicing disruption of donor and acceptor sites, and the particular challenge for bioinformatic programs to accurately predict disruption of splicing enhancer or silencer sites that display large sequence diversity (Cartegni, et al., 2002).

The efficiency with which a variant promotes recognition of a de novo site in preference to the consensus splice site should be considered. In vitro information provided by this and other studies will hopefully support the ongoing development of bioinformatic tools to improve prediction, for prioritization of variants for splicing assays in the short-term, and later for improved assessment of the prior probability of pathogenicity in the multifactorial classification model. Indeed, to this end, one of our co-authors (SVT) has recently initiated a study assessing splicing scores from MaxEntScan and NNSplice for all possible single nucleotide substitutions to the coding exons and proximal splice junction regions of BRCA1 and BRCA2. Information from in vitro assays will be used to assess the specificity and sensitivity of the algorithm; in addition, a combination of summary family history data and segregation data will be used to convert algorithm output into probabilities in favor of pathogenicity in much the same way as these data were used to calibrate Align-GVGD analysis of missense substitutions (Tavtigian, et al., 2008a).

Although the in vitro results observed in this study are accompanied by the caveat that splicing assays conducted on LCLs or lymphocytes may not reflect splicing in breast tissue, we argue that the use of such data can provide valuable insight into disease mechanisms. It is reassuring to note that the same results were observed from assays conducted on LCLs or lymphocytes for BRCA1 4868C>G (p.Ala1623Gly). In addition, several studies have shown that RNA analysis using LCLs reveal predicted splicing aberrations in BRCA1 and BRCA2 (Campos, et al., 2003; Chen, et al., 2006; Claes, et al., 2003). Moreover, family segregation studies have provided direct evidence of the clinical relevance of variant specific splicing aberrations observed using in vitro studies of LCL RNA in additional studies of BRCA1/2 and other cancer predisposition genes (Arnold, et al., 2009; Bonatti, et al., 2006; Farrugia, et al., 2008; Spearman, et al., 2008). However, it is important to note that the level of BRCA2 mRNA relative to two different reference genes (GAPDH and EEF1A1) showed a marked range across LCLs from normal non-carrier controls. It is possible that methods to synchronize cells in culture may reduce the variation in expression across normal cells and allow estimation of the relevance of total wildtype BRCA2 mRNA expression to disease predisposition, but this has yet to be tested. Therefore, evidence for pathogenicity of a sequence variant is currently best assessed by the relative expression of wildtype full-length transcript to aberrant transcript (missense or splice-related) in cycloheximide-treated cells. Another important issue to be addressed in future large-scale studies is the relationship between risk and proportion of aberrant:wildtype transcript for spliceogenic variants, a research initiative that would require use of sensitive quantitative methods.

In summary, possible splicing aberrations should not be discounted when evaluating the clinical significance of exonic variants. Detailed functional studies are required in order to assess the relative contribution of splicing defects and missense alterations to abrogation of protein function at the molecular level but the accrual of such information will improve our understanding of the relationship between informatically-predicted splicing, in-vitro/vivo splicing aberrations and disease risk, and ultimately refine the multifactorial likelihood model recommended for clinical classification of rare sequence variants. In instances where multifactorial analysis is uninformative and it is uncertain whether the molecular mechanism of pathogenesis is due to aberrant splicing or a missense change, ex vivo techniques using antisense morpholino oligonucleotides (AMOs) may be employed to restore normal splicing and isolate the effect of the missense change, as has been demonstrated for other diseases (Du, et al., 2007; Skordis, et al., 2003; Villemaire, et al., 2003).

Supplementary Material

01

ACKNOWLEDGMENTS

We gratefully acknowledge the participation of the families concerned. We wish to thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (funded by NHMRC grants 145684, 288704 and 454508) for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by grants from the National Breast Cancer Foundation, the National Health and Medical Research Council (NHMRC) and by the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. We thank Myriad Genetic Laboratories for information used to derive family history scores and investigate co-occurrence of variants with pathogenic. We thank Bruce Castle for providing clinical samples, and Joanne Dunlop from the West Midlands Regional Genetics Laboratory and Diana Barelle from the Wessex Regional Genetics Laboratory, for access to results from RNA analysis of BRCA1 c.4868C>G (p.Ala1623Gly).

Funding: This work was supported by a grant from The National Health and Medical Research Council (NHMRC) [ID442970]. kConFab is supported by grants from the National Breast Cancer Foundation, the NHMRC and by the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. The kConFab Clinical Follow Up Study was funded by NHMRC grants [145684 and 288704]. PW was awarded a scholarship by the QIMR Higher Degrees Committee. ABS is an NHMRC Senior Research Fellow, LDaS was supported by a fellowship from the Ludwig Institute for Cancer Research. FC, SVT and DEG were supported in part by the INHERIT BRCAs programme from the Canadian Institute for Health Research. FJC was supported by NIH grants [CA116167] and a Breast Cancer specialized Program in research Excellence grant [P50 CA116201] and an American Cancer Society award [RSG-04-220-01-CCE].

REFERENCES

  • Abkevich V, Zharkikh A, Deffenbaugh AM, Frank D, Chen Y, Shattuck D, Skolnick MH, Gutin A, Tavtigian SV. Analysis of missense variation in human BRCA1 in the context of interspecific sequence variation. Journal Of Medical Genetics. 2004;41(7):492–507. [Europe PMC free article] [Abstract] [Google Scholar]
  • Arnold S, Buchanan DD, Barker M, Jaskowski L, Walsh MD, Birney G, Woods MO, Hopper JL, Jenkins MA, Brown MA, et al. Classifying MLH1 and MSH2 variants using bioinformatic prediction, splicing assays, segregation, and tumor characteristics. Hum Mutat. 2009;30(5):757–770. [Europe PMC free article] [Abstract] [Google Scholar]
  • Bateman JF, Freddi S, Lamande SR, Byers P, Nasioulas S, Douglas J, Otway R, Kohonen-Corish M, Edkins E, Forrest S. Reliable and sensitive detection of premature termination mutations using a protein truncation test designed to overcome problems of nonsense-mediated mRNA instability. Hum Mutat. 1999;13(4):311–317. [Abstract] [Google Scholar]
  • Bonatti F, Pepe C, Tancredi M, Lombardi G, Aretini P, Sensi E, Falaschi E, Cipollini G, Bevilacqua G, Caligo MA. RNA-based analysis of BRCA1 and BRCA2 gene alterations. Cancer Genetics And Cytogenetics. 2006;170(2):93–101. [Abstract] [Google Scholar]
  • Campos B, DÃ-ez O, Domènech M, Baena M, Balmaña J, Sanz J, RamÃ-rez A, Alonso C, Baiget M. RNA analysis of eight BRCA1 and BRCA2 unclassified variants identified in breast/ovarian cancer families from Spain. Human Mutation. 2003;22(4):337–337. [Abstract] [Google Scholar]
  • Cartegni L, Chew SL, Krainer AR. Listening to silence and understanding nonsense: exonic mutations that affect splicing. Nature Reviews. Genetics. 2002;3(4):285–298. [Abstract] [Google Scholar]
  • Cartegni L, Wang J, Zhu Z, Zhang MQ, Krainer AR. ESEfinder: A web resource to identify exonic splicing enhancers. Nucleic Acids Res. 2003;31(13):3568–3571. [Europe PMC free article] [Abstract] [Google Scholar]
  • Chen X, Truong T-TN, Weaver J, Bove BA, Cattie K, Armstrong BA, Daly MB, Godwin AK. Intronic alterations in BRCA1 and BRCA2: effect on mRNA splicing fidelity and expression. Human Mutation. 2006;27(5):427–435. [Abstract] [Google Scholar]
  • Chenevix-Trench G, Healey S, Lakhani S, Waring P, Cummings M, Brinkworth R, Deffenbaugh AM, Burbidge LA, Pruss D, Judkins T, et al. Genetic and histopathologic evaluation of BRCA1 and BRCA2 DNA sequence variants of unknown clinical significance. Cancer Res. 2006;66(4):2019–2027. [Abstract] [Google Scholar]
  • Chester N, Kuo F, Kozak C, O'Hara CD, Leder P. Stage-specific apoptosis, developmental delay, and embryonic lethality in mice homozygous for a targeted disruption in the murine Bloom's syndrome gene. Genes Dev. 1998;12(21):3382–3393. [Europe PMC free article] [Abstract] [Google Scholar]
  • Claes K, Poppe B, Machackova E, Coene I, Foretova L, De Paepe A, Messiaen L. Differentiating pathogenic mutations from polymorphic alterations in the splice sites of BRCA1 and BRCA2. Genes, Chromosomes & Cancer. 2003;37(3):314–320. [Abstract] [Google Scholar]
  • Couch FJ, Rasmussen LJ, Hofstra R, Monteiro AN, Greenblatt MS, de Wind N. Assessment of functional effects of unclassified genetic variants. Hum Mutat. 2008;29(11):1314–1326. [Europe PMC free article] [Abstract] [Google Scholar]
  • Davies AA, Masson JY, McIlwraith MJ, Stasiak AZ, Stasiak A, Venkitaraman AR, West SC. Role of BRCA2 in control of the RAD51 recombination and DNA repair protein. Mol Cell. 2001;7(2):273–282. [Abstract] [Google Scholar]
  • Desmet FO, Hamroun D, Lalande M, Collod-Beroud G, Claustres M, Beroud C. Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 2009;37(9):e67. [Europe PMC free article] [Abstract] [Google Scholar]
  • Du L, Pollard JM, Gatti RA. Correction of prototypic ATM splicing mutations and aberrant ATM function with antisense morpholino oligonucleotides. Proc Natl Acad Sci U S A. 2007;104(14):6007–6012. [Europe PMC free article] [Abstract] [Google Scholar]
  • Easton DF, Deffenbaugh AM, Pruss D, Frye C, Wenstrup RJ, Allen-Brady K, Tavtigian SV, Monteiro AN, Iversen ES, Couch FJ, et al. A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes. Am J Hum Genet. 2007;81(5):873–883. [Europe PMC free article] [Abstract] [Google Scholar]
  • Fairbrother WG, Yeh RF, Sharp PA, Burge CB. Predictive identification of exonic splicing enhancers in human genes. Science. 2002;297(5583):1007–1013. [Abstract] [Google Scholar]
  • Farrugia DJ, Agarwal MK, Pankratz VS, Deffenbaugh AM, Pruss D, Frye C, Wadum L, Johnson K, Mentlick J, Tavtigian SV, et al. Functional assays for classification of BRCA2 variants of uncertain significance. Cancer Res. 2008;68(9):3523–3531. [Europe PMC free article] [Abstract] [Google Scholar]
  • Goldgar DE, Easton DF, Byrnes GB, Spurdle AB, Iversen ES, Greenblatt MS. Genetic evidence and integration of various data sources for classifying uncertain variants into a single model. Hum Mutat. 2008;29(11):1265–1272. [Europe PMC free article] [Abstract] [Google Scholar]
  • Goldgar DE, Easton DF, Deffenbaugh AM, Monteiro ANA, Tavtigian SV, Couch FJ. Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2. American Journal Of Human Genetics. 2004;75(4):535–544. [Europe PMC free article] [Abstract] [Google Scholar]
  • Gomez Garcia EB, Oosterwijk JC, Timmermans M, van Asperen CJ, Hogervorst FB, Hoogerbrugge N, Oldenburg R, Verhoef S, Dommering CJ, Ausems MG, et al. A method to assess the clinical significance of unclassified variants in the BRCA1 and BRCA2 genes based on cancer family history. Breast Cancer Res. 2009;11(1):R8. [Europe PMC free article] [Abstract] [Google Scholar]
  • Lakhani SR, Reis-Filho JS, Fulford L, Penault-Llorca F, van der Vijver M, Parry S, Bishop T, Benitez J, Rivas C, Bignon YJ, et al. Prediction of BRCA1 status in patients with breast cancer using estrogen receptor and basal phenotype. Clin Cancer Res. 2005;11(14):5175–5180. [Abstract] [Google Scholar]
  • Lakhani SR, Van De Vijver MJ, Jacquemier J, Anderson TJ, Osin PP, McGuffog L, Easton DF. The pathology of familial breast cancer: predictive value of immunohistochemical markers estrogen receptor, progesterone receptor, HER-2, and p53 in patients with mutations in BRCA1 and BRCA2. J Clin Oncol. 2002;20(9):2310–2318. [Abstract] [Google Scholar]
  • Lovelock PK, Spurdle AB, Mok MT, Farrugia DJ, Lakhani SR, Healey S, Arnold S, Buchanan D, Couch FJ, Henderson BR, et al. Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants? Breast Cancer Res. 2007;9(6):R82. [Europe PMC free article] [Abstract] [Google Scholar]
  • Mann GJ, Thorne H, Balleine RL, Butow PN, Clarke CL, Edkins E, Evans GM, Fereday S, Haan E, Gattas M, et al. Analysis of cancer risk and BRCA1 and BRCA2 mutation prevalence in the kConFab familial breast cancer resource. Breast Cancer Res. 2006;8(1):R12. [Europe PMC free article] [Abstract] [Google Scholar]
  • Osorio A, Milne RL, Honrado E, Barroso A, Diez O, Salazar R, de la Hoya M, Vega A, BenÃ-tez J. Classification of missense variants of unknown significance in BRCA1 based on clinical and tumor information. Human Mutation. 2007;28(5):477–485. [Abstract] [Google Scholar]
  • Patel KJ, Yu VP, Lee H, Corcoran A, Thistlethwaite FC, Evans MJ, Colledge WH, Friedman LS, Ponder BA, Venkitaraman AR. Involvement of Brca2 in DNA repair. Mol Cell. 1998;1(3):347–357. [Abstract] [Google Scholar]
  • Phelan CM, Dapic V, Tice B, Favis R, Kwan E, Barany F, Manoukian S, Radice P, van der Luijt RB, van Nesselrooij BPM, et al. Classification of BRCA1 missense variants of unknown clinical significance. Journal Of Medical Genetics. 2005;42(2):138–146. [Europe PMC free article] [Abstract] [Google Scholar]
  • Plon SE, Eccles DM, Easton D, Foulkes WD, Genuardi M, Greenblatt MS, Hogervorst FB, Hoogerbrugge N, Spurdle AB, Tavtigian SV. Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat. 2008;29(11):1282–1291. [Europe PMC free article] [Abstract] [Google Scholar]
  • Schwartz GF, Hughes KS, Lynch HT, Fabian CJ, Fentiman IS, Robson ME, Domchek SM, Hartmann LC, Holland R, Winchester DJ. Proceedings of the international consensus conference on breast cancer risk, genetics, & risk management, April, 2007. Cancer. 2008;113(10):2627–2637. [Abstract] [Google Scholar]
  • Skordis LA, Dunckley MG, Yue B, Eperon IC, Muntoni F. Bifunctional antisense oligonucleotides provide a trans-acting splicing enhancer that stimulates SMN2 gene expression in patient fibroblasts. Proc Natl Acad Sci U S A. 2003;100(7):4114–4119. [Europe PMC free article] [Abstract] [Google Scholar]
  • Spearman AD, Sweet K, Zhou XP, McLennan J, Couch FJ, Toland AE. Clinically applicable models to characterize BRCA1 and BRCA2 variants of uncertain significance. J Clin Oncol. 2008;26(33):5393–5400. [Europe PMC free article] [Abstract] [Google Scholar]
  • Spurdle AB, Couch FJ, Hogervorst FB, Radice P, Sinilnikova OM. Prediction and assessment of splicing alterations: implications for clinical testing. Hum Mutat. 2008a;29(11):1304–1313. [Europe PMC free article] [Abstract] [Google Scholar]
  • Spurdle AB, Lakhani SR, Healey S, Parry S, Da Silva LM, Brinkworth R, Hopper JL, Brown MA, Babikyan D, Chenevix-Trench G, et al. Clinical classification of BRCA1 and BRCA2 DNA sequence variants: the value of cytokeratin profiles and evolutionary analysis--a report from the kConFab Investigators. J Clin Oncol. 2008b;26(10):1657–1663. [Abstract] [Google Scholar]
  • Tavtigian SV, Byrnes GB, Goldgar DE, Thomas A. Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications. Hum Mutat. 2008;29(11):1342–1354. [Europe PMC free article] [Abstract] [Google Scholar]
  • Tesoriero AA, Wong EM, Jenkins MA, Hopper JL, Brown MA, Chenevix-Trench G, Spurdle AB, Southey MC. Molecular characterization and cancer risk associated with BRCA1 and BRCA2 splice site variants identified in multiple-case breast cancer families. Human Mutation. 2005;26(5):495–495. [Abstract] [Google Scholar]
  • Thompson D, Easton DF, Goldgar DE. A full-likelihood method for the evaluation of causality of sequence variants from family data. Am J Hum Genet. 2003;73(3):652–655. [Europe PMC free article] [Abstract] [Google Scholar]
  • Tutt A, Gabriel A, Bertwistle D, Connor F, Paterson H, Peacock J, Ross G, Ashworth A. Absence of Brca2 causes genome instability by chromosome breakage and loss associated with centrosome amplification. Curr Biol. 1999;9(19):1107–1110. [Abstract] [Google Scholar]
  • Villemaire J, Dion I, Elela SA, Chabot B. Reprogramming alternative pre-messenger RNA splicing through the use of protein-binding antisense oligonucleotides. J Biol Chem. 2003;278(50):50031–50039. [Abstract] [Google Scholar]
  • Wu K, Hinson SR, Ohashi A, Farrugia D, Wendt P, Tavtigian SV, Deffenbaugh A, Goldgar D, Couch FJ. Functional evaluation and cancer risk assessment of BRCA2 unclassified variants. Cancer Research. 2005;65(2):417–426. [Abstract] [Google Scholar]
  • Xu CF, Chambers JA, Nicolai H, Brown MA, Hujeirat Y, Mohammed S, Hodgson S, Kelsell DP, Spurr NK, Bishop DT, et al. Mutations and alternative splicing of the BRCA1 gene in UK breast/ovarian cancer families. Genes, Chromosomes & Cancer. 1997;18(2):102–110. [Abstract] [Google Scholar]
  • Yeo G, Burge CB. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol. 2004;11(2–3):377–394. [Abstract] [Google Scholar]

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