Purpose Familial Pancreatic Cancer (FPC) kindreds contain at least two affected first-degree relatives (FDR). Comprehensive data are needed to assist clinical risk assessment and genetic testing. Methods Germline DNA samples from 727 unrelated probands with positive family history (521 met criteria for FPC) were CLIA-tested for mutations in BRCA1 and BRCA2 (including analysis of deletions and rearrangements), PALB2, and CDKN2A. We compared prevalence of deleterious mutations between FPC probands and non-FPC probands (kindreds containing at least two affected biologic relatives, but not FDR). We also examined the impact of family history of breast and ovarian cancer and melanoma. Results Prevalence of deleterious mutations (excluding variants of unknown significance) among FPC probands was: BRCA1, 1.2%; BRCA2, 3.7%; PALB2, 0.6%; CDKN2A, 2.5%. Four novel deleterious mutations were detected. FPC probands carry more mutations in the four genes (8.0%) than non-FPC probands (3.5%) (odds ratio=2.40, 95% CI=(1.06, 5.44), p=0.03). The probability of testing positive for deleterious mutations in any of the four genes ranges up to 10.4%, depending upon family history of cancers. BRCA2 and CDKN2A account for the majority of mutations in FPC. Conclusion Genetic testing of multiple relevant genes in probands with a positive family history is warranted, particularly for FPC.

Genetic testing has the potential to guide the prevention and treatment of disease in a variety of settings, and recent technical advances have greatly increased our ability to acquire large amounts of genetic data. The interpretation of this data remains challenging, as the clinical significance of genetic variation detected in the laboratory is not always clear. Although regulatory agencies and professional societies provide some guidance regarding the classification, reporting, and long-term follow-up of variants, few protocols for the implementation of these guidelines have been described. Because the primary aim of clinical testing is to provide results to inform medical management, a variant classification program that offers timely, accurate, confident and cost-effective interpretation of variants should be an integral component of the laboratory process. Here we describe the components of our laboratory's current variant classification program (VCP), based on 20 years of experience and over one million samples tested, using the BRCA1/2 genes as a model. Our VCP has lowered the percentage of tests in which one or more BRCA1/2 variants of uncertain significance (VUSs) are detected to 2.1% in the absence of a pathogenic mutation, demonstrating how the coordinated application of resources toward classification and reclassification significantly impacts the clinical utility of testing.

Genetic variants of uncertain clinical significance (VUSs) are a common outcome of clinical genetic testing. Locus-specific variant databases (LSDBs) have been established for numerous disease-associated genes as a research tool for the interpretation of genetic sequence variants to facilitate variant interpretation via aggregated data. If LSDBs are to be used for clinical practice, consistent and transparent criteria regarding the deposition and interpretation of variants are vital, as variant classifications are often used to make important and irreversible clinical decisions. In this study, we performed a retrospective analysis of 2017 consecutive BRCA1 and BRCA2 genetic variants identified from 24,650 consecutive patient samples referred to our laboratory to establish an unbiased dataset representative of the types of variants seen in the US patient population, submitted by clinicians and researchers for BRCA1 and BRCA2 testing. We compared the clinical classifications of these variants among five publicly accessible BRCA1 and BRCA2 variant databases: BIC, ClinVar, HGMD (paid version), LOVD, and the UMD databases. Our results show substantial disparity of variant classifications among publicly accessible databases. Furthermore, it appears that discrepant classifications are not the result of a single outlier but widespread disagreement among databases. This study also shows that databases sometimes favor a clinical classification when current best practice guidelines (ACMG/AMP/CAP) would suggest an uncertain classification. Although LSDBs have been well established for research applications, our results suggest several challenges preclude their wider use in clinical practice.Electronic supplementary materialThe online version of this article (doi:10.1007/s12687-015-0220-x) contains supplementary material, which is available to authorized users.

An estimated 1:40 individuals of Ashkenazi Jewish (AJ) ancestry carry one of three common founder mutations in BRCA1 or BRCA2, resulting in the inherited cancer condition, Hereditary Breast and Ovarian Cancer (HBOC) syndrome. Targeted testing for these three mutations (BRCA1 187delAG, BRCA1 5385insC, and BRCA2 6174delT) is therefore recommended for all AJ breast and ovarian cancer patients, regardless of age of diagnosis or family history. Comprehensive analysis of both genes is recommended for a subset of AJ patients in whom founder mutations are not identified, but estimates of the yield from comprehensive analysis in this population vary widely. We sought to determine the proportion of non-founder mutations as a percentage of all mutations in BRCA1 and BRCA2 among AJ patients to inform decisions about HBOC testing strategies in this population. We analyzed the genetic testing results for 37,952 AJ patients for whom clinical testing of BRCA1 and BRCA2 was performed at Myriad Genetic Laboratories from January 2006 through August 2013. Analysis was limited to AJ-only patients for whom the initial test order was either (1) comprehensive testing, or (2) founder mutation testing with instructions to automatically "reflex" to comprehensive analysis if negative. Cases were excluded if a separate follow-up order was placed to reflex to comprehensive analysis only after the founder mutation testing was reported out as negative. Among all BRCA1 and BRCA2 mutations detected in these groups, the percentage of non-founder mutations was 13 % (104/802) and 7.2 % (198/2,769). One-hundred and eighty-nine unique non-founder mutations were detected, 76 in BRCA1 and 113 in BRCA2. Non-founder mutations make up between 7.2 and 13.0 % of all BRCA1 and BRCA2 mutations in Ashkenazi Jews. A wide range of mutations are present, most of which are also seen in non-AJ individuals.

Missense variants represent a significant proportion of variants identified in clinical genetic testing. In the absence of strong clinical or functional evidence, the American College of Medical Genetics recommends that these findings be classified as variants of uncertain significance (VUS). VUSs may be reclassified to better inform patient care when new evidence is available. It is critical that the methods used for reclassification are robust in order to prevent inappropriate medical management strategies and unnecessary, life-altering surgeries. In an effort to provide evidence for classification, several in silico algorithms have been developed that attempt to predict the functional impact of missense variants through amino acid sequence conservation analysis. We report an analysis comparing internally derived, evidence-based classifications with the results obtained from six commonly used algorithms. We compiled a dataset of 1118 variants in BRCA1, BRCA2, MLH1, and MSH2 previously classified by our laboratory's evidence-based variant classification program. We compared internally derived classifications with those obtained from the following in silico tools: Align-GVGD, CONDEL, Grantham Analysis, MAPP-MMR, PolyPhen-2, and SIFT. Despite being based on similar underlying principles, all algorithms displayed marked divergence in accuracy, specificity, and sensitivity. Overall, accuracy ranged from 58.7 to 90.8% while the Matthews Correlation Coefficient ranged from 0.26-0.65. CONDEL, a weighted average of multiple algorithms, did not perform significantly better than its individual components evaluated here. These results suggest that the in silico algorithms evaluated here do not provide reliable evidence regarding the clinical significance of missense variants in genes associated with hereditary cancer.