Spectrum of genetic variants of BRCA1 and BRCA2 in a German single center study.

BACKGROUND: Determination of mutation status of BRCA1 and BRCA2 has become part of the clinical routine. However, the spectrum of genetic variants differs between populations. The aim of this study was to deliver a comprehensive description of all detected variants. METHODS: In families fulfilling one of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) criteria for genetic testing, one affected was chosen for analysis. DNA of blood lymphocytes was amplified by PCR and prescreened by DHPLC. Aberrant fragments were sequenced. All coding exons and splice sites of BRCA1 and BRCA2 were analyzed. Screening for large rearrangements in both genes was performed by MLPA. RESULTS: Of 523 index patients, 121 (23.1%) were found to carry a pathogenic or likely pathogenic (class 4/5) mutation. A variant of unknown significance (VUS) was detected in 73/523 patients (13.9%). Two mutations p.Gln1756Profs*74 and p.Cys61Gly comprised 42.3% (n = 33/78) of all detected pathogenic mutations in BRCA1. Most of the other mutations were unique mutations. The most frequently detected mutation in BRCA2 was p.Val1283Lys (13.9%; n = 6/43). Altogether, 101 different neutral genetic variants were counted in BRCA1 (n = 35) and in BRCA2 (n = 66). CONCLUSION: The two most frequently detected mutations are founder mutations in Poland and Czech Republic. More similarities seem to be shared with our direct neighbor countries compared to other European countries. For comparison of the extended genotype, a shared database is needed.

BRCA1/2 missense mutations and the value of in-silico analyses.

INTRODUCTION: The clinical implications of genetic variants in BRCA1/2 in healthy and affected individuals are considerable. Variant interpretation, however, is especially challenging for missense variants. The majority of them are classified as variants of unknown clinical significance (VUS). Computational (in-silico) predictive programs are easy to access, but represent only one tool out of a wide range of complemental approaches to classify VUS. With this single-center study, we aimed to evaluate the impact of in-silico analyses in a spectrum of different BRCA1/2 missense variants. METHODS: We conducted mutation analysis of BRCA1/2 in 523 index patients with suspected hereditary breast and ovarian cancer (HBOC). Classification of the genetic variants was performed according to the German Consortium (GC)-HBOC database. Additionally, all missense variants were classified by the following three in-silico prediction tools: SIFT, Mutation Taster (MT2) and PolyPhen2 (PPH2). RESULTS: Overall 201 different variants, 68 of which constituted missense variants were ranked as pathogenic, neutral, or unknown. The classification of missense variants by in-silico tools resulted in a higher amount of pathogenic mutations (25% vs. 13.2%) compared to the GC-HBOC-classification. Altogether, more than fifty percent (38/68, 55.9%) of missense variants were ranked differently. Sensitivity of in-silico-tools for mutation prediction was 88.9% (PPH2), 100% (SIFT) and 100% (MT2). CONCLUSION: We found a relevant discrepancy in variant classification by using in-silico prediction tools, resulting in potential overestimation and/or underestimation of cancer risk. More reliable, notably gene-specific, prediction tools and functional tests are needed to improve clinical counseling.