In silico analysis of BRCA1 and BRCA2 missense variants and the relevance in molecular genetic testing.
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ABSTRACT:
SUBMITTER: Poon KS
PROVIDER: S-EPMC8160182 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeGuidelines for variant interpretation incorporate variant hotspots in critical functional domains as evidence for pathogenicity (e.g., PM1 and PP2), but do not use "coldspots," that is, regions without essential functions that tolerate variation, as evidence a variant is benign. To improve variant classification we evaluated BRCA1 and BRCA2 missense variants reported in ClinVar to identify regions where pathogenic missenses are extremely infrequent, defined as coldspots.MethodsWe used Bayesian approaches to model variant classification in these regions.ResultsBRCA1 exon 11 (~60% of the coding sequence), and BRCA2 exons 10 and 11 (~65% of the coding sequence), are coldspots. Of 89 pathogenic (P) or likely pathogenic (LP) missense variants in BRCA1, none are in exon 11 (odds <0.01, 95% confidence interval [CI] 0.0-0.01). Of 34?P or LP missense variants in BRCA2, none are in exons 10-11 (odds <0.01, 95% CI 0.0-0.01). More than half of reported missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 are in coldspots (3115/5301?=?58.8%). Reclassifying these 3115 VUS as likely benign would substantially improve variant classification.ConclusionIn BRCA1 and BRCA2 coldspots, missense variants are very unlikely to be pathogenic. Classification schemes that incorporate coldspots can reduce the number of VUS and mitigate risks from reporting benign variation as VUS.
| S-EPMC7200594 | biostudies-literature
Project description:BACKGROUND: BRCA1 and BRCA2 germline mutations predispose heterozygous carriers to hereditary breast/ovarian cancer. However, unclassified variants (UVs) (variants with unknown clinical significance) and missense polymorphisms in BRCA1 and BRCA2 genes pose a problem in genetic counseling, as their impact on risk of breast and ovarian cancer is still unclear. The objective of our study was to identify UVs and missense polymorphisms in Algerian breast/ovarian cancer patients and relatives tested previously for BRCA1 and BRCA2 genes germline mutations analysis. METHODS: We analyzed 101 DNA samples from 79 breast/ovarian cancer families. The approach used is based on BRCA1 and BRCA2 sequence variants screening by SSCP or High-Resolution Melting (HRM) curve analysis followed by direct sequencing. In silico analyses have been performed using different bioinformatics programs to individualize genetics variations that can disrupt the BRCA1 and BRCA2 genes function. RESULTS: Among 80 UVs and polymorphisms detected in BRCA1/2 genes (33 BRCA1 and 47 BRCA2), 31 were new UVs (10 BRCA1 and 21 BRCA2), 7 were rare UVs (4 BRCA1 and 3 BRCA2) and 42 were polymorphic variants (19 BRCA1 and 23 BRCA2). Moreover, 8 new missense UVs identified in this study: two BRCA1 (c.4066C>A/p.Gln1356Lys, c.4901G>T/p.Arg1634Met) located respectively in exons 11 and 16, and six BRCA2 (c.1099G>A/p.Asp367Asn, c.2636C>A/p.Ser879Tyr, c.3868T>A/p.Cys1290Ser, c.5428G>T/p.Val1810Phe, c.6346C>G/p.His2116Asp and c.9256G>A/p.Gly3086Arg) located respectively in exons 10, 11 and 24, show a damaging PSIC score yielded by PolyPhen2 program and could be pathogenic. In addition, 5 new BRCA} missense UVs out of six that were found to be damaging by PolyPhen2 program, also were deleterious according to SIFT program. The rare BRCA1 UV c.5332G>A/p.Asp1778Asn was found here for the first time in co-occurrence in trans with the deleterious BRCA1 mutation c.798_799delTT/p.Ser267LysfsX19 in young breast cancer patient. Moreover, 10 new identified intronic variants with unknown clinical significance (3 BRCA1 and 7 BRCA2) in the present study, could be considered as benign, because GeneSplicer, SpliceSiteFinder and MaxEntScan prediction programs show no splice site alteration for these variants. Several missense polymorphisms of BRCA1 c.2612C>T/p.Pro871Leu, c.3548A>G/p.Lys1183Arg, c.4837A>G/p.Ser1613Gly and BRCA2 c.865A>C/p.Asn289His, c.1114A>C/p.Asn372His, c.2971A>G/p.Asn991Asp, c.7150C>A/p.Gly2384Lys have been identified with high frequency in patients who were tested negative for BRCA1 and BRCA2 mutations. These missense polymorphisms could have a role as susceptibility breast cancer markers in Algerian breast/ovarian cancer families where pathological BRCA1 and BRCA2 mutations were not present. CONCLUSIONS: For the first time, UVs and missense polymorphisms in BRCA1 and BRCA2 genes have been identified in Algerian breast/ovarian cancer families. Evaluation of breast/ovarian cancer risk induced by the eight new missense UVs and common polymorphisms detected in our present work is on going in a larger study.
| S-EPMC3826381 | biostudies-other
Project description:BACKGROUND:Increasing use of BRCA1/2 testing for tailoring cancer treatment and extension of testing to tumour tissue for somatic mutation is moving BRCA1/2 mutation screening from a primarily prevention arena delivered by specialist genetic services into mainstream oncology practice. A considerable number of gene tests will identify rare variants where clinical significance cannot be inferred from sequence information alone. The proportion of variants of uncertain clinical significance (VUS) is likely to grow with lower thresholds for testing and laboratory providers with less experience of BRCA. Most VUS will not be associated with a high risk of cancer but a misinterpreted VUS has the potential to lead to mismanagement of both the patient and their relatives. DESIGN:Members of the Clinical Working Group of ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) global consortium (www.enigmaconsortium.org) observed wide variation in practices in reporting, disclosure and clinical management of patients with a VUS. Examples from current clinical practice are presented and discussed to illustrate potential pitfalls, explore factors contributing to misinterpretation, and propose approaches to improving clarity. RESULTS AND CONCLUSION:Clinicians, patients and their relatives would all benefit from an improved level of genetic literacy. Genetic laboratories working with clinical geneticists need to agree on a clinically clear and uniform format for reporting BRCA test results to non-geneticists. An international consortium of experts, collecting and integrating all available lines of evidence and classifying variants according to an internationally recognized system, will facilitate reclassification of variants for clinical use.
| S-EPMC5006185 | biostudies-literature
Project description:ObjectivesMissense variants are very commonly detected when screening for mutations in the BRCA1 and BRCA2 genes. Pathogenic mutations in the BRCA1 and BRCA2 genes lead to an increased risk of developing breast, ovarian, prostate and/or pancreatic cancer. This study aimed to assess the predictive capability of in silico programmes and mutation databases in assisting diagnostic laboratories to determine the pathogenicity of sequence-detectable mutations.MethodsBetween July 2011 and April 2013, an analysis was undertaken of 13 missense BRCA gene variants that had been detected in patients referred to the Genetic Health Services New Zealand (Northern Hub) for BRCA gene analysis. The analysis involved the use of 13 in silico protein prediction programmes, two in silico transcript analysis programmes and the examination of three BRCA gene databases.ResultsIn most of the variants, the analysis showed different in silico interpretations. This illustrates the interpretation challenges faced by diagnostic laboratories.ConclusionUnfortunately, when using online mutation databases and carrying out in silico analyses, there is significant discordance in the classification of some missense variants in the BRCA genes. This discordance leads to complexities in interpreting and reporting these variants in a clinical context. The authors have developed a simple procedure for analysing variants; however, those of unknown significance largely remain unknown. As a consequence, the clinical value of some reports may be negligible.
| S-EPMC4450785 | biostudies-literature
Project description:Mutations in BRCA1 and BRCA2 are responsible for a large proportion of breast-ovarian cancer families. Protein-truncating mutations have been effectively used in the clinical management of familial breast cancer due to their deleterious impact on protein function. However, the majority of missense variants identified throughout the genes continue to pose an obstacle for predictive informative testing due to low frequency and lack of information on how they affect BRCA1/2 function. Phosphorylation of BRCA1 and BRCA2 play an important role in their function as regulators of DNA repair, transcription and cell cycle in response to DNA damage but whether missense variants of uncertain significance (VUS) are able to disrupt this important process is not known. Here we employed a novel approach using NetworKIN which predicts in vivo kinase-substrate relationship, and evolutionary conservation algorithms SIFT, PolyPhen and Align-GVGD. We evaluated whether 191 BRCA1 and 43 BRCA2 VUS from the Breast Cancer Information Core (BIC) database can functionally alter the consensus phosphorylation motifs and abolish kinase recognition and binding to sites known to be phosphorylated in vivo. Our results show that 13.09% (25/191) BRCA1 and 13.95% (6/43) BRCA2 VUS altered the phosphorylation of BRCA1 and BRCA2. We highlight six BRCA1 (K309T, S632N, S1143F, Q1144H, Q1281P, S1542C) and three BRCA2 (S196I, T207A, P3292L) VUS as potentially clinically significant. These occurred rarely (n<2 in BIC), mutated evolutionarily conserved residues and abolished kinase binding to motifs established in the literature involved in DNA repair, cell cycle regulation, transcription or response to DNA damage. Additionally in vivo phosphorylation sites identified via through-put methods are also affected by VUS and are attractive targets for studying their biological and functional significance. We propose that rare VUS affecting phosphorylation may be a novel and important mechanism for which BRCA1 and BRCA2 functions are disrupted in breast cancer.
| S-EPMC3660339 | biostudies-literature
Project description:Machine learning-based pathogenicity prediction helps interpret rare missense variants of BRCA1 and BRCA2, which are associated with hereditary cancers. Recent studies have shown that classifiers trained using variants of a specific gene or a set of genes related to a particular disease perform better than those trained using all variants, due to their higher specificity, despite the smaller training dataset size. In this study, we further investigated the advantages of "gene-specific" machine learning compared to "disease-specific" machine learning. We used 1068 rare (gnomAD minor allele frequency (MAF) < 0.005) missense variants of 28 genes associated with hereditary cancers for our investigation. Popular machine learning classifiers were employed: regularized logistic regression, extreme gradient boosting, random forests, support vector machines, and deep neural networks. As features, we used MAFs from multiple populations, functional prediction and conservation scores, and positions of variants. The disease-specific training dataset included the gene-specific training dataset and was > 7 × larger. However, we observed that gene-specific training variants were sufficient to produce the optimal pathogenicity predictor if a suitable machine learning classifier was employed. Therefore, we recommend gene-specific over disease-specific machine learning as an efficient and effective method for predicting the pathogenicity of rare BRCA1 and BRCA2 missense variants.
| S-EPMC10307865 | biostudies-literature
Project description:Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ?99% probability of pathogenicity, and 73 had ?95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.
| S-EPMC5985401 | biostudies-literature
Project description:In silico predictions of missense variants is an important consideration when interpreting variants of uncertain significance (VUS) in the BRCA1 and BRCA2 genes. We trained and evaluated hundreds of machine learning algorithms based on results from validated functional assays to better predict missense variants in these genes as damaging or neutral. This new optimal "BRCA-ML" model yielded a substantially more accurate method than current algorithms for interpreting the functional impact of variants in these genes, making BRCA-ML a valuable addition to data sources for VUS classification.
| S-EPMC7190647 | biostudies-literature
Project description:Rare exonic, non-truncating variants in known cancer susceptibility genes such as BRCA1 and BRCA2 are problematic for genetic counseling and clinical management of relevant families. This study used multifactorial likelihood analysis and/or bioinformatically-directed mRNA assays to assess pathogenicity of 19 BRCA1 or BRCA2 variants identified following patient referral to clinical genetic services. Two variants were considered to be pathogenic (Class 5). BRCA1:c.4484G> C(p.Arg1495Thr) was shown to result in aberrant mRNA transcripts predicted to encode truncated proteins. The BRCA1:c.122A>G(p.His41Arg) RING-domain variant was found from multifactorial likelihood analysis to have a posterior probability of pathogenicity of 0.995, a result consistent with existing protein functional assay data indicating lost BARD1 binding and ubiquitin ligase activity. Of the remaining variants, seven were determined to be not clinically significant (Class 1), nine were likely not pathogenic (Class 2), and one was uncertain (Class 3).These results have implications for genetic counseling and medical management of families carrying these specific variants. They also provide additional multifactorial likelihood variant classifications as reference to evaluate the sensitivity and specificity of bioinformatic prediction tools and/or functional assay data in future studies.
| S-EPMC3904950 | biostudies-literature
Project description:PurposeTo improve methods for predicting the impact of missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 on protein function.MethodsFunctional data for 248 BRCA1 and 207 BRCA2 variants from assays with established high sensitivity and specificity for damaging variants were used to recalibrate 40 in silico algorithms predicting the impact of variants on protein activity. Additional random forest (RF) and naïve voting method (NVM) metapredictors for both BRCA1 and BRCA2 were developed to increase predictive accuracy.ResultsOptimized thresholds for in silico prediction models significantly improved the accuracy of predicted functional effects for BRCA1 and BRCA2 variants. In addition, new BRCA1-RF and BRCA2-RF metapredictors showed area under the curve (AUC) values of 0.92 (95% confidence interval [CI]: 0.88-0.96) and 0.90 (95% CI: 0.84-0.95), respectively. Similarly, the BRCA1-NVM and BRCA2-NVM models had AUCs of 0.93 and 0.90. The RF and NVM models were used to predict the pathogenicity of all possible missense variants in BRCA1 and BRCA2.ConclusionThe recalibrated algorithms and new metapredictors significantly improved upon current models for predicting the impact of variants in cancer risk-associated domains of BRCA1 and BRCA2. Prediction of the functional impact of all possible variants in BRCA1 and BRCA2 provides important information about the clinical relevance of variants in these genes.
| S-EPMC6287763 | biostudies-literature