47 research outputs found
Performance of BRCA1/2 mutation prediction models in male breast cancer patients
To establish whether existing mutation prediction models can identify which male breast cancer (MBC) patients should be offered BRCA1 and BRCA2 diagnostic DNA screening, we compared the performance of BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm), BRCAPRO (BRCA probability) and the Myriad prevalence table ("Myriad"). These models were evaluated using the family data of 307 Dutch MBC probands tested for BRCA1/2, 58 (19%) of whom were carriers. We compared the numbers of observed vs predicted carriers and assessed the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) for each model. BOADICEA predicted the total number of BRCA1/2 mutation carriers quite accurately (observed/predicted ratio: 0.94). When a cut-off of 10% and 20% prior probability was used, BRCAPRO showed a non-significant better performance (observed/predicted ratio BOADICEA: 0.81, 95% confidence interval [CI]: [0.60-1.09] and 0.79, 95% CI: [0.57-1.09], vs. BRCAPRO: 1.02, 95% CI: [0.75-1.38] and 0.94, 95% CI: [0.68-1.31], respectively). Myriad underestimated the number of carriers in up to 69% of the cases. BRCAPRO showed a non-significant, higher AUC than BOADICEA (0.798 vs 0.776). Myriad showed a significantly lower AUC (0.671). BRCAPRO and BOADICEA can efficiently identify MBC patients as BRCA1/2 mutation carriers. Besides their general applicability, these tools will be of particular value in countries with limited healthcare resources
A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example
BACKGROUND: Assessment of the clinical significance of unclassified variants (UVs) identified in BRCA1 and BRCA2 is very important for genetic counselling. The analysis of co-segregation of the variant with the disease in families is a powerful tool for the classification of these variants. Statistical methods have been described in literature but these methods are not always easy to apply in a diagnostic setting. METHODS: We have developed an easy to use method which calculates the likelihood ratio (LR) of an UV being deleterious, with penetrance as a function of age of onset, thereby avoiding the use of liability classes. The application of this algorithm is publicly available http://www.msbi.nl/cosegregation. It can easily be used in a diagnostic setting since it requires only information on gender, genotype, present age and/or age of onset for breast and/or ovarian cancer. RESULTS: We have used the algorithm to calculate the likelihood ratio in favour of causality for 3 UVs in BRCA1 (p.M18T, p.S1655F and p.R1699Q) and 5 in BRCA2 (p.E462G p.Y2660D, p.R2784Q, p.R3052W and p.R3052Q). Likelihood ratios varied from 0.097 (BRCA2, p.E462G) to 230.69 (BRCA2, p.Y2660D). Typing distantly related individuals with extreme phenotypes (i.e. very early onset cancer or old healthy individuals) are most informative and give the strongest likelihood ratios for or against causality. CONCLUSION: Although co-segregation analysis on itself is in most cases insufficient to prove pathogenicity of an UV, this method simplifies the use of co-segregation as one of the key features in a multifactorial approach considerably
Comprehensive Functional Characterization and Clinical Interpretation of 20 Splice-Site Variants of the RAD51C Gene
Hereditary breast and/or ovarian cancer is a highly heterogeneous disease with more than 10 known disease-associated genes. In the framework of the BRIDGES project (Breast Cancer Risk after Diagnostic Gene Sequencing), the RAD51C gene has been sequenced in 60,466 breast cancer patients and 53,461 controls. We aimed at functionally characterizing all the identified genetic variants that are predicted to disrupt the splicing process. Forty RAD51C variants of the intron-exon boundaries were bioinformatically analyzed, 20 of which were selected for splicing functional assays. To test them, a splicing reporter minigene with exons 2 to 8 was designed and constructed. This minigene generated a full-length transcript of the expected size (1062 nucleotides), sequence, and structure (Vector exon V1- RAD51C exons_2-8- Vector exon V2). The 20 candidate variants were genetically engineered into the wild type minigene and functionally assayed in MCF-7 cells. Nineteen variants (95%) impaired splicing, while 18 of them produced severe splicing anomalies. At least 35 transcripts were generated by the mutant minigenes: 16 protein-truncating, 6 in-frame, and 13 minor uncharacterized isoforms. According to ACMG/AMP-based standards, 15 variants could be classified as pathogenic or likely pathogenic variants: c.404G > A, c.405-6T > A, c.571 + 4A > G, c.571 + 5G > A, c.572-1G > T, c.705G > T, c.706-2A > C, c.706-2A > G, c.837 + 2T > C, c.905-3C > G, c.905-2A > C, c.905-2_905-1del, c.965 + 5G > A, c.1026 + 5_1026 + 7del, and c.1026 + 5G > T
Clinical correlates of low-risk variants in FGFR2, TNRC9, MAP3K1, LSP1 and 8q24 in a Dutch cohort of incident breast cancer cases
Exploring the link between MORF4L1 and risk of breast cancer.
INTRODUCTION: Proteins encoded by Fanconi anemia (FA) and/or breast cancer (BrCa) susceptibility genes cooperate in a common DNA damage repair signaling pathway. To gain deeper insight into this pathway and its influence on cancer risk, we searched for novel components through protein physical interaction screens. METHODS: Protein physical interactions were screened using the yeast two-hybrid system. Co-affinity purifications and endogenous co-immunoprecipitation assays were performed to corroborate interactions. Biochemical and functional assays in human, mouse and Caenorhabditis elegans models were carried out to characterize pathway components. Thirteen FANCD2-monoubiquitinylation-positive FA cell lines excluded for genetic defects in the downstream pathway components and 300 familial BrCa patients negative for BRCA1/2 mutations were analyzed for genetic mutations. Common genetic variants were genotyped in 9,573 BRCA1/2 mutation carriers for associations with BrCa risk. RESULTS: A previously identified co-purifying protein with PALB2 was identified, MRG15 (MORF4L1 gene). Results in human, mouse and C. elegans models delineate molecular and functional relationships with BRCA2, PALB2, RAD51 and RPA1 that suggest a role for MRG15 in the repair of DNA double-strand breaks. Mrg15-deficient murine embryonic fibroblasts showed moderate sensitivity to Îł-irradiation relative to controls and reduced formation of Rad51 nuclear foci. Examination of mutants of MRG15 and BRCA2 C. elegans orthologs revealed phenocopy by accumulation of RPA-1 (human RPA1) nuclear foci and aberrant chromosomal compactions in meiotic cells. However, no alterations or mutations were identified for MRG15/MORF4L1 in unclassified FA patients and BrCa familial cases. Finally, no significant associations between common MORF4L1 variants and BrCa risk for BRCA1 or BRCA2 mutation carriers were identified: rs7164529, Ptrend = 0.45 and 0.05, P2df = 0.51 and 0.14, respectively; and rs10519219, Ptrend = 0.92 and 0.72, P2df = 0.76 and 0.07, respectively. CONCLUSIONS: While the present study expands on the role of MRG15 in the control of genomic stability, weak associations cannot be ruled out for potential low-penetrance variants at MORF4L1 and BrCa risk among BRCA2 mutation carriers.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are
A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants:Application to BRCA1 and BRCA2
A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.</p
Mutations in SLC29A3, Encoding an Equilibrative Nucleoside Transporter ENT3, Cause a Familial Histiocytosis Syndrome (Faisalabad Histiocytosis) and Familial Rosai-Dorfman Disease
The histiocytoses are a heterogeneous group of disorders characterised by an excessive number of histiocytes. In most cases the pathophysiology is unclear and treatment is nonspecific. Faisalabad histiocytosis (FHC) (MIM 602782) has been classed as an autosomal recessively inherited form of histiocytosis with similarities to Rosai-Dorfman disease (RDD) (also known as sinus histiocytosis with massive lymphadenopathy (SHML)). To elucidate the molecular basis of FHC, we performed autozygosity mapping studies in a large consanguineous family and identified a novel locus at chromosome 10q22.1. Mutation analysis of candidate genes within the target interval identified biallelic germline mutations in SLC29A3 in the FHC kindred and in two families reported to have familial RDD. Analysis of SLC29A3 expression during mouse embryogenesis revealed widespread expression by e14.5 with prominent expression in the central nervous system, eye, inner ear, and epithelial tissues including the gastrointestinal tract. SLC29A3 encodes an intracellular equilibrative nucleoside transporter (hENT3) with affinity for adenosine. Recently germline mutations in SLC29A3 were also described in two rare autosomal recessive disorders with overlapping phenotypes: (a) H syndrome (MIM 612391) that is characterised by cutaneous hyperpigmentation and hypertrichosis, hepatomegaly, heart anomalies, hearing loss, and hypogonadism; and (b) PHID (pigmented hypertrichosis with insulin-dependent diabetes mellitus) syndrome. Our findings suggest that a variety of clinical diagnoses (H and PHID syndromes, FHC, and familial RDD) can be included in a new diagnostic category of SLC29A3 spectrum disorder
Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification
The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification
AURKA F31I polymorphism and breast cancer risk in BRCA1 and BRCA2 mutation carriers: A consortium of investigators of modifiers of BRCA1/2 study
The AURKA oncogene is associated with abnormal chromosome segregation and aneuploidy and predisposition to cancer. Amplification of AURKA has been detected at higher frequency in tumors from BRCA1 and BRCA2 mutation carriers than in sporadic breast tumors, suggesting that overexpression of AURKA and inactivation of BRCA1 and BRCA2 cooperate during tumor development and progression. The F31I polymorphism in AURKA has been associated with breast cancer risk in the homozygous state in prior studies. We evaluated whether the AURKA F31I polymorphism modifies breast cancer risk in BRCA1 and BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2. Consortium of Investigators of Modifiers of BRCA1/2 was established to provide sufficient statistical power through increased numbers of mutation carriers to identify polymorphisms that act as modifiers of cancer risk and can refine breast cancer risk estimates in BRCA1 and BRCA2 mutation carriers. A total of 4,935 BRCA1 and 2,241 BRCA2 mutation carriers and 11 individuals carrying both BRCA1 and BRCA2 mutations was genotyped for F31I. Overall, homozygosity for the 311 allele was not significantly associated with breast cancer risk in BRCA1 and BRCA2 carriers combined [hazard ratio (HR), 0.91; 95% confidence interval (95% CI), 0.77-1.061. Similarly, no significant association was seen in BRCA1 (HR, 0.90; 95% Cl, 0.75-1.08) or BRCA2 carriers (HR, 0.93; 95% CI, 0.67-1.29) or when assessing the modifying effects of either bilateral prophylactic oophorectomy or menopausal status of BRCA1 and BRCA2 carriers. In summary, the F31I polymorphism in AURKA is not associated with a modified risk of breast cancer in BRCA1 and BRCA2 carriers
Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification
Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe