Sensitivity of BRCA1/2 mutation testing in 466 breast/ovarian cancer families

Analysis of 30 putative BRCA1 splicing mutations in hereditary breast and ovarian cancer families identifies exonic splice site mutations that escape in silico prediction

Screening for pathogenic mutations in breast and ovarian cancer genes such as BRCA1/2, CHEK2 and RAD51C is common practice for individuals from high-risk families. However, test results may be ambiguous due to the presence of unclassified variants (UCV) in the concurrent absence of clearly cancer-predisposing mutations. Especially the presence of intronic or exonic variants within these genes that possibly affect proper pre-mRNA processing poses a challenge as their functional implications are not immediately apparent. Therefore, it appears necessary to characterize potential splicing UCV and to develop appropriate classification tools. We investigated 30 distinct BRCA1 variants, both intronic and exonic, regarding their spliceogenic potential by commonly used in silico prediction algorithms (HSF, MaxEntScan) along with in vitro transcript analyses. A total of 25 variants were identified spliceogenic, either causing/enhancing exon skipping or activation of cryptic splice sites, or both. Except from a single intronic variant causing minor effects on BRCA1 pre-mRNA processing in our analyses, 23 out of 24 intronic variants were correctly predicted by MaxEntScan, while HSF was less accurate in this cohort. Among the 6 exonic variants analyzed, 4 severely impair correct pre-mRNA processing, while the remaining two have partial effects. In contrast to the intronic alterations investigated, only half of the spliceogenic exonic variants were correctly predicted by HSF and/or MaxEntScan. These data support the idea that exonic splicing mutations are commonly disease-causing and concurrently prone to escape in silico prediction, hence necessitating experimental in vitro splicing analysis.

Pitfalls and Caveats in BRCA Sequencing

Between 5 and 10% of breast cancer cases are considered to result from hereditary predisposition. Germ-line mutations in BRCA1 and BRCA2 are responsible for an inherited predisposition of breast and ovarian cancer. Direct nucleotide sequencing is considered the gold standard technique for mutation detection for genes such as BRCA1 and BRCA2. In many laboratories that analyze BRCA1 and BRCA2, previous to direct sequencing, screening techniques to identify sequence variants in the PCR amplicons are performed. The mutations detected in these genes may be frameshift mutations (insertions or deletions), nonsense mutations, or missense mutations. The clinical interpretation of the mutation as the cause of the disease may be difficult to establish in the case of missense mutations. Only in 30-70% of the families in which a hereditary component is suspected, a mutation in BRCA1 and/or BRCA2 is detected. Negative results may be due to: wrong selection of the proband; mutations in the regulatory portion of the genes; gene silencing due to epigenetic phenomena; or large genomic rearrangements that produce deletions of whole exons. Another possibility that explains the lack of detection of alterations in BRCA1 or BRCA2 is the presence of mutations in undiscovered genes or in genes that interact with BRCA1 and/or BRCA2, which may be low-penetrance genes, like CHEK2.

BRCA1/2 mutation analysis in male breast cancer families from North West England

64 families with a history of male breast cancer aged 60 or less or with a family history of male and female breast cancer were screened for the presence of BRCA1 and BRCA2 mutations. Seventeen pathogenic BRCA2 and four BRCA1 mutations were identified (34%) in samples from an affected family member. All but one of the mutations segregated with disease where samples were available and pedigree structure permitted. Despite high sensitivity of mutation testing only 64% of families fulfilling BCLC criteria had an identifiable pathogenic mutation. It is possible that at least some of these families may have mutations in other genes, although we found no involvement of CHEK2 1100delC.

Phenocopies in BRCA1 and BRCA2 families: evidence for modifier genes and implications for screening

BACKGROUND

The identification of BRCA1 and BRCA2 mutations in familial breast cancer kindreds allows genetic testing of at-risk relatives. Those who test negative are usually reassured and additional breast cancer surveillance is discontinued. However, we postulated that in high-risk families, such as those seen in clinical genetics centres, the risk of breast cancer might be influenced not only by the BRCA1/BRCA2 mutation but also by modifier genes. One manifestation of this would be the presence of phenocopies in BRCA1/BRCA2 kindreds.

METHODS

277 families with pathogenic BRCA1/BRCA2 mutations were reviewed and 28 breast cancer phenocopies identified. The relative risk of breast cancer in those testing negative was assessed using incidence rates from our cancer registry based on local population.

RESULTS

Phenocopies constituted up to 24% of tests on women with breast cancer after the identification of the mutation in the proband. The standardised incidence ratio for women who tested negative for the BRCA1/BRCA2 family mutation was 5.3 for all relatives, 5.0 for all first-degree relatives (FDRs) and 3.2 (95% confidence interval 2.0 to 4.9) for FDRs in whose family all other cases of breast and ovarian cancer could be explained by the identified mutation. 13 of 107 (12.1%) FDRs with breast cancer and no unexplained family history tested negative.

CONCLUSION

In high-risk families, women who test negative for the familial BRCA1/BRCA2 mutation have an increased risk of breast cancer consistent with genetic modifiers. In light of this, such women should still be considered for continued surveillance.

Optimal Selection of Individuals for BRCA Mutation Testing: A Comparison of Available Methods

Purpose

Several methods have been described that estimate the likelihood that a family history of cancer is a result of a mutation in the BRCA1 or BRCA2 genes. We examined the performance of six different methods with the aim of identifying an optimal strategy for selecting individuals for mutation testing in clinical practice.

Patients and Methods

Two hundred fifty-seven families who had completed BRCA1 and BRCA2 mutation screening were assessed by six models representing the major methodologies used to assess the likelihood of a pathogenic mutation. The performance of each method as a selection criterion was compared with the result of mutation testing to produce sensitivity, specificity, and receiver operating curve data. The impact of incorporating breast cancer pathology data in the assessment was also analyzed.

Results

The highest accuracy was achieved by the Bayesian probabilistic model (BRCAPRO). The formal probabilistic methods were significantly more accurate than clinical scoring methods. The methods were further improved by the incorporation of information on breast cancer pathology (tumor grade and estrogen receptor/progesterone receptor status). The resulting combined probability figure was highly accurate when selecting individuals for BRCA1 testing. Some BRCA2 mutation carriers were missed by all of the models examined.

Conclusion

Formal probabilistic models provide significantly greater accuracy in the selection of families for gene testing than the use of clinical criteria or scoring methods. The accuracy is further enhanced by incorporating information on the pathology of breast cancers occurring in the families.

A new scoring system for the chances of identifying a BRCA1/2 mutation outperforms existing models including BRCAPRO

PURPOSE

To develop a simple scoring system for the likelihood of identifying a BRCA1 or BRCA2 mutation.

METHODS

DNA samples from affected subjects from 422 non-Jewish families with a history of breast and/or ovarian cancer were screened for BRCA1 mutations and a subset of 318 was screened for BRCA2 by whole gene screening techniques. Using a combination of results from screening and the family history of mutation negative and positive kindreds, a simple scoring system (Manchester scoring system) was devised to predict pathogenic mutations and particularly to discriminate at the 10% likelihood level. A second separate dataset of 192 samples was subsequently used to test the model's predictive value. This was further validated on a third set of 258 samples and compared against existing models.

RESULTS

The scoring system includes a cut-off at 10 points for each gene. This equates to >10% probability of a pathogenic mutation in BRCA1 and BRCA2 individually. The Manchester scoring system had the best trade-off between sensitivity and specificity at 10% prediction for the presence of mutations as shown by its highest C-statistic and was far superior to BRCAPRO.

CONCLUSION

The scoring system is useful in identifying mutations particularly in BRCA2. The algorithm may need modifying to include pathological data when calculating whether to screen for BRCA1 mutations. It is considerably less time-consuming for clinicians than using computer models and if implemented routinely in clinical practice will aid in selecting families most suitable for DNA sampling for diagnostic testing.