Exceptions to the rule: Case studies in the prediction of pathogenicity for genetic variants in hereditary cancer genes

Based on current consensus guidelines and standard practice, many genetic variants detected in clinical testing are classified as disease causing based on their predicted impact on the normal expression or function of the gene in the absence of additional data. However, our laboratory has identified a subset of such variants in hereditary cancer genes for which compelling contradictory evidence emerged after the initial evaluation following the first observation of the variant. Three representative examples of variants in BRCA1, BRCA2 and MSH2 that are predicted to disrupt splicing, prematurely truncate the protein, or remove the start codon were evaluated for pathogenicity by analyzing clinical data with multiple classification algorithms. Available clinical data for all three variants contradicts the expected pathogenic classification. These variants illustrate potential pitfalls associated with standard approaches to variant classification as well as the challenges associated with monitoring data, updating classifications, and reporting potentially contradictory interpretations to the clinicians responsible for translating test outcomes to appropriate clinical action. It is important to address these challenges now as the model for clinical testing moves toward the use of large multi‐gene panels and whole exome/genome analysis, which will dramatically increase the number of genetic variants identified.     

Comprehensive profiling of BRCA1 and BRCA2 variants in breast and ovarian cancer in Chinese patients

The identification and interpretation of germline BRCA1/2 variants become increasingly important in breast and ovarian cancer (OC) treatment. However, there is no comprehensive analysis of the germline BRCA1/2 variants in a Chinese population. Here we performed a systematic review and meta‐analysis on such variants from 94 publications. A total of 2,128 BRCA1/2 variant records were extracted, including 601 from BRCA1 and 632 from BRCA2. In addition, 414, 734, 449, and 307 variants were also recorded in the BIC, ClinVar, ENIGMA, and UMD databases, respectively, and 579 variants were newly reported. Subsequent analysis showed that the overall germline BRCA1/2 pathogenic variant frequency was 5.7% and 21.8% in Chinese breast and OC, respectively. Populations with high‐risk factors exhibited a higher pathogenic variant percentage. Furthermore, the variant profile in Chinese is distinct from that in other ethnic groups with no distinct founder pathogenic variants. We also tested our in‐house American College of Medical Genetics‐guided pathogenicity interpretation procedure for Chinese BRCA1/2 variants. Our results achieved a consistency of 91.2–97.6% (5‐grade classification) or 98.4–100% (2‐grade classification) with public databases. In conclusion, this study represents the first comprehensive meta‐analysis of Chinese BRCA1/2 variants and validates our in‐house pathogenicity interpretation procedure, thereby providing guidance for further PARP inhibitor development and companion diagnostics in the Chinese population.     

Cholesterol metabolism is a potential therapeutic target for Rett syndrome

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.     

A guide for functional analysis of BRCA1 variants of uncertain significance

Germline mutations in the tumor suppressor gene BRCA1 confer an estimated lifetime risk of 56–80% for breast cancer and 15–60% for ovarian cancer. Since the mid 1990s when BRCA1 was identified, genetic testing has revealed over 1,500 unique germline variants. However, for a significant number of these variants, the effect on protein function is unknown making it difficult to infer the consequences on risks of breast and ovarian cancers. Thus, many individuals undergoing genetic testing for BRCA1 mutations receive test results reporting a variant of uncertain clinical significance (VUS), leading to issues in risk assessment, counseling, and preventive care. Here, we describe functional assays for BRCA1 to directly or indirectly assess the impact of a variant on protein conformation or function and how these results can be used to complement genetic data to classify a VUS as to its clinical significance. Importantly, these methods may provide a framework for genome‐wide pathogenicity assignment. Hum Mutat 33:1526–1537, 2012. © 2012 Wiley Periodicals, Inc.     

Analysis of BRCA1 Variants in Double‐Strand Break Repair by Homologous Recombination and Single‐Strand Annealing

Missense substitutions of uncertain clinical significance in the BRCA1 gene are a vexing problem in genetic counseling for women who have a family history of breast cancer. In this study, we evaluated the functions of 29 missense substitutions of BRCA1 in two DNA repair pathways. Repair of double‐strand breaks by homology‐directed recombination (HDR) had been previously analyzed for 16 of these BRCA1 variants, and 13 more variants were analyzed in this study. All 29 variants were also analyzed for function in double‐strand break repair by the single‐strand annealing (SSA) pathway. We found that among the pathogenic mutations in BRCA1, all were defective for DNA repair by either pathway. The HDR assay was accurate because all pathogenic mutants were defective for HDR, and all nonpathogenic variants were fully functional for HDR. Repair by SSA accurately identified pathogenic mutants, but several nonpathogenic variants were scored as defective or partially defective. These results indicated that specific amino acid residues of the BRCA1 protein have different effects in the two related DNA repair pathways, and these results validate the HDR assay as highly correlative with BRCA1‐associated breast cancer.     

Splicing and multifactorial analysis of intronic BRCA1 and BRCA2 sequence variants identifies clinically significant splicing aberrations up to 12 nucleotides from the intron/exon boundary

Clinical management of breast cancer families is complicated by identification of BRCA1 and BRCA2 sequence alterations of unknown significance. Molecular assays evaluating the effect of intronic variants on native splicing can help determine their clinical relevance. Twenty-six intronic BRCA1/2 variants ranging from the consensus dinucleotides in the splice acceptor or donor to 53 nucleotides into the intron were identified in multiple-case families. The effect of the variants on splicing was assessed using HSF matrices, MaxEntScan and NNsplice, followed by analysis of mRNA from lymphoblastoid cell lines. A total of 12 variants were associated with splicing aberrations predicted to result in production of truncated proteins, including a variant located 12 nucleotides into the intron. The posterior probability of pathogenicity was estimated using a multifactorial likelihood approach, and provided a pathogenic or likely pathogenic classification for seven of the 12 spliceogenic variants. The apparent disparity between experimental evidence and the multifactorial predictions is likely due to several factors, including a paucity of likelihood information and a nonspecific prior probability applied for intronic variants outside the consensus dinucleotides. Development of prior probabilities of pathogenicity incorporating bioinformatic prediction of splicing aberrations should improve identification of functionally relevant variants and enhance multifactorial likelihood analysis of intronic variants.     

Functional Analysis of a Large set of BRCA2 exon 7 Variants Highlights the Predictive Value of Hexamer Scores in Detecting Alterations of Exonic Splicing Regulatory Elements

Exonic variants can alter pre‐mRNA splicing either by changing splice sites or by modifying splicing regulatory elements. Often these effects are difficult to predict and are only detected by performing RNA analyses. Here, we analyzed, in a minigene assay, 26 variants identified in the exon 7 of BRCA2, a cancer predisposition gene. Our results revealed eight new exon skipping mutations in this exon: one directly altering the 5′ splice site and seven affecting potential regulatory elements. This brings the number of splicing regulatory mutations detected in BRCA2 exon 7 to a total of 11, a remarkably high number considering the total number of variants reported in this exon (n = 36), all tested in our minigene assay. We then exploited this large set of splicing data to test the predictive value of splicing regulator hexamers’ scores recently established by Ke et al. ( 2011 ). Comparisons of hexamer‐based predictions with our experimental data revealed high sensitivity in detecting variants that increased exon skipping, an important feature for prescreening variants before RNA analysis. In conclusion, hexamer scores represent a promising tool for predicting the biological consequences of exonic variants and may have important applications for the interpretation of variants detected by high‐throughput sequencing.     

Functional Assays for Analysis of Variants of Uncertain Significance in BRCA2

Missense variants in the BRCA2 gene are routinely detected during clinical screening for pathogenic mutations in patients with a family history of breast and ovarian cancer. These subtle changes frequently remain of unknown clinical significance because of the lack of genetic information that may help establish a direct correlation with cancer predisposition. Therefore, alternative ways of predicting the pathogenicity of these variants are urgently needed. Since BRCA2 is a protein involved in important cellular mechanisms such as DNA repair, replication, and cell cycle control, functional assays have been developed that exploit these cellular activities to explore the impact of the variants on protein function. In this review, we summarize assays developed and currently utilized for studying missense variants in BRCA2. We specifically depict details of each assay, including variants of uncertain significance analyzed, and describe a validation set of (genetically) proven pathogenic and neutral missense variants to serve as a golden standard for the validation of each assay. Guidelines are proposed to enable implementation of laboratory‐based methods to assess the impact of the variant on cancer risk.     

Future directions for high‐throughput splicing assays in precision medicine

Classification of variants of unknown significance is a challenging technical problem in clinical genetics. As up to one‐third of disease‐causing mutations are thought to affect pre‐mRNA splicing, it is important to accurately classify splicing mutations in patient sequencing data. Several consortia and healthcare systems have conducted large‐scale patient sequencing studies, which discover novel variants faster than they can be classified. Here, we compare the advantages and limitations of several high‐throughput splicing assays aimed at mitigating this bottleneck, and describe a data set of ~5,000 variants that we analyzed using our Massively Parallel Splicing Assay (MaPSy). The Critical Assessment of Genome Interpretation group (CAGI) organized a challenge, in which participants submitted machine learning models to predict the splicing effects of variants in this data set. We discuss the winning submission of the challenge (MMSplice) which outperformed existing software. Finally, we highlight methods to overcome the limitations of MaPSy and similar assays, such as tissue‐specific splicing, the effect of surrounding sequence context, classifying intronic variants, synthesizing large exons, and amplifying complex libraries of minigene species. Further development of these assays will greatly benefit the field of clinical genetics, which lack high‐throughput methods for variant interpretation.     

Contribution of bioinformatics predictions and functional splicing assays to the interpretation of unclassified variants of the BRCA genes

A large fraction of sequence variants of unknown significance (VUS) of the breast and ovarian cancer susceptibility genes BRCA1 and BRCA2 may induce splicing defects. We analyzed 53 VUSs of BRCA1 or BRCA2, detected in consecutive molecular screenings, by using five splicing prediction programs, and we classified them into two groups according to the strength of the predictions. In parallel, we tested them by using functional splicing assays. A total of 10 VUSs were predicted by two or more programs to induce a significant reduction of splice site strength or activation of cryptic splice sites or generation of new splice sites. Minigene-based splicing assays confirmed four of these predictions. Five additional VUSs, all at internal exon positions, were not predicted to induce alterations of splice sites, but revealed variable levels of exon skipping, most likely induced by the modification of exonic splicing regulatory elements. We provide new data in favor of the pathogenic nature of the variants BRCA1 c.212+3A>G and BRCA1 c.5194−12G>A, which induced aberrant out-of-frame mRNA forms. Moreover, the novel variant BRCA2 c.7977−7C>G induced in frame inclusion of 6 nt from the 3′ end of intron 17. The novel variants BRCA2 c.520C>T and BRCA2 c.7992T>A induced incomplete skipping of exons 7 and 18, respectively. This work highlights the contribution of splicing minigene assays to the assessment of pathogenicity, not only when patient RNA is not available, but also as a tool to improve the accuracy of bioinformatics predictions.     

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly‐interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.     

BRCA1‐ and BRCA2‐specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge

BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene‐specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.