A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example

BICEP: Bayesian inference for rare genomic variant causality evaluation in pedigrees

Next-generation sequencing is widely applied to the investigation of pedigree data for gene discovery. However, identifying plausible disease-causing variants within a robust statistical framework is challenging. Here, we introduce BICEP: a Bayesian inference tool for rare variant causality evaluation in pedigree-based cohorts. BICEP calculates the posterior odds that a genomic variant is causal for a phenotype based on the variant cosegregation as well as a priori evidence such as deleteriousness and functional consequence. BICEP can correctly identify causal variants for phenotypes with both Mendelian and complex genetic architectures, outperforming existing methodologies. Additionally, BICEP can correctly down-weight common variants that are unlikely to be involved in phenotypic liability in the context of a pedigree, even if they have reasonable cosegregation patterns. The output metrics from BICEP allow for the quantitative comparison of variant causality within and across pedigrees, which is not possible with existing approaches.

Germline DNA Damage Repair Gene Alterations in Patients with Metachronous Breast and Colorectal Cancer

A hereditary component of breast (BC) and colorectal cancer (CRC) has been described in approximately one-third of these tumor types. BC patients have an increased risk of developing CRC as a second primary tumor and vice versa. Germline genomic variants (NextSeq550, Illumina) were investigated in 24 unrelated BC and/or CRC patients and 7 relatives from 3 index patients. Fifty-six pathogenic or likely pathogenic variants were identified in 19 of 24 patients. We detected single-nucleotide variants (SNVs) in CRC predisposition genes (MLH1 and MUTYH) and other promising candidates (CDK5RAP3, MAD1L1, NOS3, and POLM). Eighteen patients presented SNVs or copy number variants (CNVs) in DNA damage repair genes. We also identified SNVs recently associated with BC or CRC predisposition (PABPC1, TYRO3, MAP3K1, SLC15A4, and LAMA1). The PABPC1c.1255C>T variant was detected in nine unrelated patients. Each patient presented at least one SNV/CNV in a candidate gene, and most had alterations in more than one gene, reinforcing a polygenic model for BC/CRC predisposition. A significant fraction of BC/CRC patients with a family history of these tumors harbored deleterious germline variants in DNA repair genes. Our findings can lead to strategies to improve the diagnosis, genetic counseling, and treatment of patients and their relatives.

shinyseg: a web application for flexible cosegregation and sensitivity analysis

MOTIVATION

Cosegregation analysis is a powerful tool for identifying pathogenic genetic variants, but its implementation remains challenging. Existing software is either limited in scope or too demanding for many end users. Moreover, current solutions lack methods for assessing the robustness of cosegregation evidence, which is important due to its reliance on uncertain estimates.

RESULTS

We present shinyseg, a comprehensive web application for clinical cosegregation analysis. Our app streamlines penetrance specification based on either liability classes or epidemiological data such as risks, hazard ratios, and age of onset distribution. In addition, it incorporates sensitivity analyses to assess the robustness of cosegregation evidence, and offers support in clinical interpretation.

AVAILABILITY AND IMPLEMENTATION

The shinyseg app is freely available at https://chrcarrizosa.shinyapps.io/shinyseg, with documentation and complete R source code on https://chrcarrizosa.github.io/shinyseg and https://github.com/chrcarrizosa/shinyseg.

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.

ClinGen guidance for use of the PP1/BS4 co-segregation and PP4 phenotype specificity criteria for sequence variant pathogenicity classification

The 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant classification publication established a standard employed internationally to guide laboratories in variant assessment. Those recommendations included both pathogenic (PP1) and benign (BS4) criteria for evaluating the inheritance patterns of variants, but details of how to apply those criteria at appropriate evidence levels were sparse. Several publications have since attempted to provide additional guidance, but anecdotally, this issue is still challenging. Additionally, it is not clear that those prior efforts fully distinguished disease-gene identification considerations from variant pathogenicity considerations nor did they address autosomal-recessive and X-linked inheritance. Here, we have taken a mixed inductive and deductive approach to this problem using real diseases as examples. We have developed a practical heuristic for genetic co-segregation evidence and have also determined that the specific phenotype criterion (PP4) is inseparably coupled to the co-segregation criterion. We have also determined that negative evidence at one locus constitutes positive evidence for other loci for disorders with locus heterogeneity. Finally, we provide a points-based system for evaluating phenotype and co-segregation as evidence types to support or refute a locus and show how that can be integrated into the Bayesian framework now used for variant classification and consistent with the 2015 guidelines.

Characterization of BRCA2 R3052Q variant in mice supports its functional impact as a low-risk variant

Pathogenic variants in BRCA2 are known to significantly increase the lifetime risk of developing breast and ovarian cancers. Sequencing-based genetic testing has resulted in the identification of thousands of BRCA2 variants that are considered to be variants of uncertain significance (VUS) because the disease risk associated with them is unknown. One such variant is p.Arg3052Gln, which has conflicting interpretations of pathogenicity in the ClinVar variant database. Arginine at position 3052 in BRCA2 plays an important role in stabilizing its C-terminal DNA binding domain. We have generated a knock-in mouse model expressing this variant to examine its role on growth and survival in vivo. Homozygous as well as hemizygous mutant mice are viable, fertile and exhibit no overt phenotype. While we did not observe any hematopoietic defects in adults, we did observe a marked reduction in the in vitro proliferative ability of fetal liver cells that were also hypersensitive to PARP inhibitor, olaparib. In vitro studies performed on embryonic and adult fibroblasts derived from the mutant mice showed significant reduction in radiation induced RAD51 foci formation as well as increased genomic instability after mitomycin C treatment. We observed mis-localization of a fraction of R3052Q BRCA2 protein to the cytoplasm which may explain the observed in vitro phenotypes. Our findings suggest that BRCA2 R3052Q should be considered as a hypomorphic variant.

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification

Functional classification of genetic variants is a key for their clinical applications in patient care. However, abundant variant data generated by the next-generation DNA sequencing technologies limit the use of experimental methods for their classification. Here, we developed a protein structure and deep learning (DL)-based system for genetic variant classification, DL-RP-MDS, which comprises two principles: 1) Extracting protein structural and thermodynamics information using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, 2) combining those data with an unsupervised learning model of auto-encoder and a neural network classifier to identify the statistical significance patterns of the structural changes. We observed that DL-RP-MDS provided higher specificity than over 20 widely used in silico methods in classifying the variants of three DNA damage repair genes: TP53, MLH1, and MSH2. DL-RP-MDS offers a powerful platform for high-throughput genetic variant classification. The software and online application are available at https://genemutation.fhs.um.edu.mo/DL-RP-MDS/.

Assessing the pathogenicity of BRCA1/2 variants of unknown significance: Relevance and challenges for breast cancer precision medicine

Introduction

Breast cancer (BC) is the leading cause of cancer-related death in women worldwide. Pathogenic variants in BRCA1 and BRCA2 genes account for approximately 50% of all hereditary BC, with 60-80% of patients characterized by Triple Negative Breast Cancer (TNBC) at an early stage phenotype. The identification of a pathogenic BRCA1/2 variant has important and expanding roles in risk-reducing surgeries, treatment planning, and familial surveillance. Otherwise, finding unclassified Variants of Unknown Significance (VUS) limits the clinical utility of the molecular test, leading to an "imprecise medicine".

Methods

We reported the explanatory example of the BRCA1 c.5057A>C, p.(His1686Pro) VUS identified in a patient with TNBC. We integrated data from family history and clinic-pathological evaluations, genetic analyses, and bioinformatics in silico investigations to evaluate the VUS classification.

Results

Our evaluation posed evidences for the pathogenicity significance of the investigated VUS: 1) association of the BRCA1 variant to cancer-affected members of the family; 2) absence of another high-risk mutation; 3) multiple indirect evidences derived from gene and protein structural analysis.

Discussion

In line with the ongoing efforts to uncertain variants classification, we speculated about the relevance of an in-depth assessment of pathogenicity of BRCA1/2 VUS for a personalized management of patients with BC. We underlined that the efficient integration of clinical data with the widest number of supporting molecular evidences should be adopted for the proper management of patients, with the final aim of effectively guide the best prognostic and therapeutic paths.

In Silico and Structure-Based Assessment of Similar Variants Discovered in Tandem Repeats of BRCT Domains of BRCA1 and BARD1 To Characterize the Folding Pattern

BRCA1 and BARD1 are important proteins in the homologous DNA damage repair pathways. Different genetic variants identified in these proteins have been clinically correlated with the occurrence of hereditary breast and ovarian cancer (HBOC). Variants of unknown significance (VUS) reported in the BRCT domains of BRCA1 and BARD1 substantiate the importance of BRCT domain-containing proteins for genomic integrity. To classify the pathogenicity of variants, in silico, structural and molecular dynamics (MD)-based approaches were explored. Different variants reported in the BRCT region were retrieved from cBioPortal, LOVD3, BRCA Exchange, and COSMIC databases to evaluate the pathogenicity. Multiple sequence alignment and superimposition of the structures of BRCA1 BRCT and BARD1 BRCT domains were performed to compare alterations in folding patterns. From 11 in silico predictions servers, variants reported to be pathogenic by 70% of the servers were considered for structural analysis. To our observations, four residue pairs of both the proteins were reported, harboring 11 variants, H1686Y, W1718L, P1749L, P1749S, and W1837L variants for BRCA1 BRCT and H606D, H606N, W635L, P657L, P657S, and W762F for BARD1 BRCT. MD simulations of the BRCT repeat regions of these variants and wild-type proteins were performed to evaluate the differences of folding patterns. Root mean square deviation (RMSD), R _g, solvent-accessible surface area (SASA), and root mean square fluctuation (RMSF) of variants showed slight differences in the folding patterns from the wild-type proteins. Furthermore, principal components analysis of H1686Y, P1749S, and W1718L variants of BRCA1 showed less flexibility than the wild type, whereas that of H606D, W635L, and W762F of BARD1 showed more flexibility than the wild type. Normal mode analysis of the energy minima from the simulation trajectories revealed that most of the variants do not show much differences in the flexibility compared to the wild-type proteins, except for the discrete regions in the BRCT repeats, most prominently in the 1798-1801 amino acid region of BRCA1 and at the residue 744 in BARD1.

Clinical, splicing, and functional analysis to classify BRCA2 exon 3 variants: Application of a points-based ACMG/AMP approach

Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.

The Pathogenic R3052W BRCA2 Variant Disrupts Homology-Directed Repair by Failing to Localize to the Nucleus

The BRCA2 germline missense variant, R3052W, resides in the DNA binding domain and has been previously classified as a pathogenic allele. In this study, we sought to determine how R3052W alters the cellular functions of BRCA2 in the DNA damage response. The BRCA2 R3052W mutated protein exacerbates genome instability, is unable to rescue homology-directed repair, and fails to complement cell survival following exposure to PARP inhibitors and crosslinking drugs. Surprisingly, despite anticipated defects in DNA binding or RAD51-mediated DNA strand exchange, the BRCA2 R3052W protein mislocalizes to the cytoplasm precluding its ability to perform any DNA repair functions. Rather than acting as a simple loss-of-function mutation, R3052W behaves as a dominant negative allele, likely by sequestering RAD51 in the cytoplasm.

An Algorithm for Optimal Testing in Co‐segregation Analysis

Clinical genetic sequencing tests often identify variants of uncertain significance. One source of data that can help classify the pathogenicity of variants is familial cosegregation analysis. Identifying and genotyping relatives for cosegregation analysis can be time consuming and costly. We propose an algorithm that describes a single measure of expected variant information gain from genotyping a single additional relative in a family. Then we explore the performance of this algorithm by comparing actual recruitment strategies used in 35 families who had pursued cosegregation analysis with synthetic pedigrees of possible testing outcomes if the families had pursued an optimized testing strategy instead. For each actual and synthetic pedigree, we calculated the likelihood ratio of pathogenicity as each successive test was added to the pedigree. We analyzed the differences in cosegregation likelihood ratio over time resulting from actual versus optimized testing approaches. Employing the testing strategy indicated by the algorithm would have led to maximal information more rapidly in 30 of the 35 pedigrees (86%). Many clinical and research laboratories are involved in targeted cosegregation analysis. The algorithm we present can facilitate a data driven approach to optimal relative recruitment and genotyping for cosegregation analysis and more efficient variant classification.

Comprehensive Identification of Deleterious TP53 Missense VUS Variants Based on Their Impact on TP53 Structural Stability

TP53 plays critical roles in maintaining genome stability. Deleterious genetic variants damage the function of TP53, causing genome instability and increased cancer risk. Of the large quantity of genetic variants identified in TP53, however, many remain functionally unclassified as variants of unknown significance (VUS) due to the lack of evidence. This is reflected by the presence of 749 (42%) VUS of the 1785 germline variants collected in the ClinVar database. In this study, we addressed the deleteriousness of TP53 missense VUS. Utilizing the protein structure-based Ramachandran Plot-Molecular Dynamics Simulation (RPMDS) method that we developed, we measured the effects of missense VUS on TP53 structural stability. Of the 340 missense VUS tested, we observed deleterious evidence for 193 VUS, as reflected by the TP53 structural changes caused by the VUS-substituted residues. We compared the results from RPMDS with those from other in silico methods and observed higher specificity of RPMDS in classification of TP53 missense VUS than these methods. Data from our current study address a long-standing challenge in classifying the missense VUS in TP53, one of the most important tumor suppressor genes.

Cohort profile and heritability assessment of familial pancreatic cancer: a nation-wide study

BACKGROUND

Familial Pancreatic Cancer (FPC) is responsible for up to 10% of all cases of pancreatic ductal adenocarcinoma (PDAC). Individuals predisposed for FPC have an estimated lifetime risk of 16-39% of developing PDAC. While heritability of PDAC has been estimated to be 36% in a Nordic twin study, no heritability estimate specific on FPC has been reported.

METHODS

A national cohort of Danish families with predisposition for FPC is currently included in a screening program for PDAC at Odense University Hospital. Family members included in the screening program were interviewed for pedigree data including: cases of PDAC among first-degree relatives (FDRs) and number of affected/unaffected siblings. Heritability for FPC in the predisposed families was assessed by doubling the estimated intra-class correlation coefficient (ICC) from a random intercept logistic model fitted to data on FDRs.

RESULTS

Among families with predisposition for FPC, 83 cases of PDAC were identified. The median age at diagnosis of PDAC was 66 years, and median time from diagnosis to death was 7.6 months. A total of 359 individuals were found as unaffected FDRs of the 83 PDAC cases. The retrieved FDRs included a total of 247 individuals in sibship and 317 individuals in parent-offspring relatedness. We estimated an ICC of 0.25, corresponding to a narrow sense additive heritability estimate of 0.51 in the FPC family cohort.

CONCLUSION

We have established a nation-wide cohort of FPC families to facilitate clinical and genetic studies on FPC. The estimated heritability of 51% prominently underlines a strong genetic background of FPC.

Utilization of breast cancer risk prediction models by cancer genetic counselors in clinical practice predominantly in the United States

Risk assessment in cancer genetic counseling is essential in identifying individuals at high risk for developing breast cancer to recommend appropriate screening and management options. Historically, many breast cancer risk prediction models were developed to calculate an individual's risk to develop breast cancer or to carry a pathogenic variant in the BRCA1 or BRCA2 genes. However, how or when genetic counselors use these models in clinical settings is currently unknown. We explored genetic counselors' breast cancer risk model usage patterns including frequency of use, reasons for using or not using models, and change in usage since the adoption of multi-gene panel testing. An online survey was developed and sent to members of the National Society of Genetic Counselors; board-certified genetic counselors whose practice included cancer genetic counseling were eligible to participate in the study. The response rate was estimated at 23% (243/1,058), and respondents were predominantly working in the United States. The results showed that 93% of all respondents use at least one breast cancer risk prediction model in their clinical practice. Among the six risk models selected for the study, the Tyrer-Cuzick (IBIS) model was used most frequently (95%), and the BOADICEA model was used least (40%). Determining increased or decreased surveillance and breast MRI eligibility were the two most common reasons for most model usage, while time consumption and difficulty in navigation were the two most common reasons for not using models. This study provides insight into perceived benefits and limitations of risk models in clinical use in the United States, which may be useful information for software developers, genetic counseling program curriculum developers, and currently practicing cancer genetic counselors.

Imprecise Medicine: BRCA2 Variants of Uncertain Significance (VUS), the Challenges and Benefits to Integrate a Functional Assay Workflow with Clinical Decision Rules

Pathological mutations in homology-directed repair (HDR) genes impact both future cancer risk and therapeutic options for patients. HDR is a high-fidelity DNA repair pathway for resolving DNA double-strand breaks throughout the genome. BRCA2 is an essential protein that mediates the loading of RAD51 onto resected DNA breaks, a key step in HDR. Germline mutations in BRCA2 are associated with an increased risk for breast, ovarian, prostate, and pancreatic cancer. Clinical findings of germline or somatic BRCA2 mutations in tumors suggest treatment with platinum agents or PARP inhibitors. However, when genetic analysis reveals a variant of uncertain significance (VUS) in the BRCA2 gene, precision medicine-based decisions become complex. VUS are genetic changes with unknown pathological impact. Current statistics indicate that between 10–20% of BRCA sequencing results are VUS, and of these, more than 50% are missense mutations. Functional assays to determine the pathological outcome of VUS are urgently needed to provide clinical guidance regarding cancer risk and treatment options. In this review, we provide a brief overview of BRCA2 functions in HDR, describe how BRCA2 VUS are currently assessed in the clinic, and how genetic and biochemical functional assays could be integrated into the clinical decision process. We suggest a multi-step workflow composed of robust and accurate functional assays to correctly evaluate the potential pathogenic or benign nature of BRCA2 VUS. Success in this precision medicine endeavor will offer actionable information to patients and their physicians.

Segregation analysis of the BRCA2 c.9227G>T variant in multiple families suggests a pathogenic role in breast and ovarian cancer predisposition

Classification of variants in the BRCA1 and BRCA2 genes has a major impact on the clinical management of subjects at high risk for breast and ovarian cancer. The identification of a pathogenic variant allows for early detection/prevention strategies in healthy carriers as well as targeted treatments in patients affected by BRCA-associated tumors. The BRCA2 c.9227G>T p.(Gly3076Val) variant recurs in families from Northeast Italy and is rarely reported in international databases. This variant substitutes the evolutionary invariant glycine 3076 with a valine in the DNA binding domain of the BRCA2 protein, thus suggesting a high probability of pathogenicity. We analysed clinical and genealogic data of carriers from 15 breast/ovarian cancer families in whom no other pathogenic variants were detected. The variant was shown to co-segregate with breast and ovarian cancer in the most informative families. Combined segregation data led to a likelihood ratio of 81,527:1 of pathogenicity vs. neutrality. We conclude that c.9227G>T is a BRCA2 pathogenic variant that recurs in Northeast Italy. It can now be safely used for the predictive testing of healthy family members to guide preventive surgery and/or early tumor detection strategies, as well as for PARP inhibitors treatments in patients with BRCA2-associated tumors.

Considerations in assessing germline variant pathogenicity using cosegregation analysis

PURPOSE

The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have developed guidelines for classifying germline variants as pathogenic or benign to interpret genetic testing results. Cosegregation analysis is an important component of the guidelines. There are two main approaches for cosegregation analysis: meiosis counting and Bayes factor-based quantitative methods. Of these, the ACMG/AMP guidelines employ only meiosis counting. The accuracy of either approach has not been sufficiently addressed in previous works.

METHODS

We analyzed hypothetical, simulated, and real-life data to evaluate the accuracy of each approach for cancer-associated genes.

RESULTS

We demonstrate that meiosis counting can provide incorrect classifications when the underlying genetic basis of the disease departs from simple Mendelian situations. Some Bayes factor approaches are currently implemented with inappropriate penetrance. We propose an improved penetrance model and describe several critical considerations, including the accuracy of cosegregation for moderate-risk genes and the impact of pleiotropy, population, and birth year. We highlight a webserver, COOL (Co-segregation Online, http://BJFengLab.org/ ), that implements an accurate Bayes factor cosegregation analysis.

CONCLUSION

An appropriate penetrance model improves the accuracy of Bayes factor cosegregation analysis for high-penetrant variants, and is a better choice than meiosis counting whenever feasible.

Functional Categorization of BRCA1 Variants of Uncertain Clinical Significance in Homologous Recombination Repair Complementation Assays

PURPOSE

Because BRCA1 is a high-risk breast/ovarian cancer susceptibility gene, BRCA1 sequence variants of uncertain clinical significance (VUS) complicate genetic counseling. As most VUS are rare, reliable classification based on clinical and genetic data is often impossible. However, all pathogenic BRCA1 variants analyzed result in defective homologous recombination DNA repair (HRR). Thus, BRCA1 VUS may be categorized based on their functional impact on this pathway.

EXPERIMENTAL DESIGN

Two hundred thirty-eight BRCA1 VUS-comprising most BRCA1 VUS known in the Netherlands and Belgium-were tested for their ability to complement Brca1-deficient mouse embryonic stem cells in HRR, using cisplatin and olaparib sensitivity assays and a direct repeat GFP (DR-GFP) HRR assay. Assays were validated using 25 known benign and 25 known pathogenic BRCA1 variants. For assessment of pathogenicity by a multifactorial likelihood analysis method, we collected clinical and genetic data for functionally deleterious VUS and VUS occurring in three or more families.

RESULTS

All three assays showed 100% sensitivity and specificity (95% confidence interval, 83%-100%). Out of 238 VUS, 45 showed functional defects, 26 of which were deleterious in all three assays. For 13 of these 26 variants, we could calculate the probability of pathogenicity using clinical and genetic data, resulting in the identification of 7 (likely) pathogenic variants.

CONCLUSIONS

We have functionally categorized 238 BRCA1 VUS using three different HRR-related assays. Classification based on clinical and genetic data alone for a subset of these variants confirmed the high sensitivity and specificity of our functional assays.

Prevalence and founder effect of the BRCA1 p.(Val1833Met) variant in the Greek population, with further evidence for pathogenicity and risk modification

PURPOSE

Multiple lines of evidence have suggested a likely causative role in breast/ovarian cancer (BrCa/OvCa) predisposition for the BRCA1 p.(Val1833Met) variant, predominantly found among Greek patients. Our aim was to study the variant's prevalence and founder effect on the Greek population, while providing additional data for its pathogenicity.

METHODS

We genotyped 3531 BrCa/OvCa patients using Sanger and next generation sequencing, as well as 1558 healthy, age-matched females with real-time PCR. Carriers underwent haplotype analysis to determine a founder effect. A co-segregation analysis was applied to estimate the likelihood ratio for pathogenicity.

RESULTS

In total, 27 BrCa/OvCa patients (0.77%; 27/3531) were found to carry the p.(Val1833Met) variant. No carriers were identified in the control group diagnosis. A common shared haplotype, spanning 2.76 Mb on chromosome 17 was demonstrated among carriers, establishing the founder effect. BRCA1, p.(Val1833Met) is possibly a disease-associated variant, supported by a likelihood ratio of 1.88, while a correlation to ovarian cancer is suspected.

CONCLUSIONS

Altogether, BRCA1, p.(Val1833Met) variant is a Greek founder and is very likely to predispose for BrCa/OvCa. Therefore, such carriers should be counselled accordingly, with clinical recommendations supporting surveillance and risk-reduction strategies, while providing the option for targeted therapeutic interventions.

A comparison of cosegregation analysis methods for the clinical setting

Quantitative cosegregation analysis can help evaluate the pathogenicity of genetic variants. However, genetics professionals without statistical training often use simple methods, reporting only qualitative findings. We evaluate the potential utility of quantitative cosegregation in the clinical setting by comparing three methods. One thousand pedigrees each were simulated for benign and pathogenic variants in BRCA1 and MLH1 using United States historical demographic data to produce pedigrees similar to those seen in the clinic. These pedigrees were analyzed using two robust methods, full likelihood Bayes factors (FLB) and cosegregation likelihood ratios (CSLR), and a simpler method, counting meioses. Both FLB and CSLR outperform counting meioses when dealing with pathogenic variants, though counting meioses is not far behind. For benign variants, FLB and CSLR greatly outperform as counting meioses is unable to generate evidence for benign variants. Comparing FLB and CSLR, we find that the two methods perform similarly, indicating that quantitative results from either of these methods could be combined in multifactorial calculations. Combining quantitative information will be important as isolated use of cosegregation in single families will yield classification for less than 1% of variants. To encourage wider use of robust cosegregation analysis, we present a website ( http://www.analyze.myvariant.org ) which implements the CSLR, FLB, and Counting Meioses methods for ATM, BRCA1, BRCA2, CHEK2, MEN1, MLH1, MSH2, MSH6, and PMS2. We also present an R package, CoSeg, which performs the CSLR analysis on any gene with user supplied parameters. Future variant classification guidelines should allow nuanced inclusion of cosegregation evidence against pathogenicity.

Unclassified Variants of BRCA1 and BRCA2 in Korean Patients With Ovarian Cancer

OBJECTIVE

The aim of the present study was to investigate unclassified variants (UVs) in BRCA1 and 2 of Korean patients with ovarian cancer.

METHODS

We retrospectively analyzed 138 patients diagnosed with ovarian/fallopian tubal/peritoneal cancer between January 2013 and January 2016, whose BRCA genetic test results and clinical characteristics were available for review. Patient peripheral blood lymphocyte specimens were assessed for BRCA mutations and variations by direct sequencing. Identified UVs were classified according to several algorithms.

RESULTS

The results of genetic testing revealed 31 (22.5%, 31/138) pathogenic BRCA mutations (24 BRCA1, 7 BRCA2 mutations). The BRCA1 c.390C>A mutation was observed in 4 patients (12.9%, 4/31). Thirty-four (24.6%, 34/138) BRCA UVs were identified in 33 patients. Of these, the BRCA1 c.4883T>C and BRCA2 c.8187G>T variants were each detected in 4 patients (4/34, 11.8%). According to the used algorithms and cosegregation test, the BRCA1 c.5339T>C and BRCA2 c.8437_8439delGGA variants were both predicted to be likely pathogenic.

CONCLUSIONS

The 2 identified likely pathogenic UVs require further verification with clinical evidence. Clarifying the clinical significance of UVs is an increasingly important step for cancer treatment in the current era of precision medicine.

Outcomes of 92 patient-driven family studies for reclassification of variants of uncertain significance

PURPOSE

Family studies are an important but underreported source of information for reclassification of variants of uncertain significance (VUS). We evaluated outcomes of a patient-driven framework that offered familial VUS reclassification analysis to any adult with any clinically ascertained VUS from any laboratory in the United States.

METHODS

With guidance from FindMyVariant.org, participants recruited their own relatives for study participation. We genotyped relatives, calculated quantitative cosegregation likelihood ratios, and evaluated variant classifications using Tavtigian's unified framework for Bayesian analysis with American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria. We report participation and VUS reclassification rates from the 50 families enrolled for at least one year and reclassification results for 112 variants from the larger 92-family cohort.

RESULTS

For the 50-family cohort, 6.7 relatives per family were invited to participate and 67% of relatives returned samples for genotyping. Sixty-one percent of VUS were reclassified, 84% of which were classified as benign or likely benign. Genotyping relatives identified a de novo variant, phase variants, and relatives with phenotypes highly specific for or incompatible with specific classifications.

CONCLUSIONS

Motivated families can contribute to successful VUS reclassification at substantially higher rates than those previously published. Clinical laboratories could consider offering family studies to all patients with VUS.

Dealing With BRCA1/2 Unclassified Variants in a Cancer Genetics Clinic: Does Cosegregation Analysis Help?

Background: Detection of variants of uncertain significance (VUSs) in BRCA1 and BRCA2 genes poses relevant challenges for counseling and managing patients. VUS carriers should be managed similarly to probands with no BRCA1/2 variants detected, and predictive genetic testing in relatives is discouraged. However, miscomprehension of VUSs is common and can lead to inaccurate risk perception and biased decisions about prophylactic surgery. Therefore, efforts are needed to improve VUS evaluation and communication at an individual level.

Aims: We aimed at investigating whether cosegregation analysis, integrated with a careful review of available functional data and in silico predictions, may improve VUSs interpretation and counseling in individual families.

Methods: Patients with Breast Cancer (BC) and/or Ovarian Cancer (OC) fulfilling established criteria were offered genetic counseling and BRCA1/2 testing; VUSs identified in index cases were checked in other relatives affected by BC/OC whenever possible. As an alternative, if BC/OC clustered only in one branch of the family, the parental origin of the VUS was investigated. Public prediction tools and databases were used to collect additional information on the variants analyzed.

Results: Out of 1045 patients undergoing BRCA1/2 testing in the period October 2011–April 2018, 66 (6.3%) carried class 3 VUSs. Cosegregation analysis was performed for 13 VUSs in 11 kindreds. Seven VUSs (53.8%) did not cosegregate with breast/ovarian cancer in the family, which provided evidence against their role in cancer clustering in those families. Among the 6 cosegregating VUSs, for two (BRCA1 c.5152+2T>G and BRCA2 c.7975A>G) additional evidence exists from databases and in silico tools supporting their pathogenicity, which reinforces the hypothesis they may have had a predisposing effect in respective families. For the remaining four VUSs (31%), cosegregation analysis failed to provide relevant information.

Conclusion: Our findings suggest that cosegregation analysis in a clinical context may be helpful to improve test result interpretation in the specific family and, therefore, should be offered whenever possible. Besides, obtaining and sharing cosegregation data helps gathering evidence that may eventually contribute to VUS classification.

Power of pedigree likelihood analysis in extended pedigrees to classify rare variants of uncertain significance in cancer risk genes

Rare and private variants of uncertain significance (VUS) are routinely identified in clinical panel, exome, and genome sequencing. We investigated the power of single family co-segregation analysis to aid classification of VUS. We simulated thousands of pedigrees using demographics in China and the United States, segregating benign and pathogenic variants. Genotypes and phenotypes were simulated using penetrance models for Lynch syndrome and breast/ovarian cancer. We calculated LOD scores adjusted for proband ascertainment (LODadj), to determine power to yield quantitative evidence for, or against, pathogenicity of the VUS. Power to classify VUS was higher for Chinese than United States pedigrees. The number of affected individuals explained the most variation in LODadj (21-38%). The distance to the furthest affected relative (FAR) from the proband explained 1-7% of the variation for the benign VUS and Lynch associated cancers. Minimum age of onset (MAO) explained 5-13% of the variation in families with pathogenic breast/ovarian cancer variants. Random removal of 50% of the phenotype/genotype data reduced power and the variation in LODadj was best explained by FAR followed by the number of affected individuals and MAO when the founder was only two generations from the proband. Power to classify benign variants was ~2x power to classify pathogenic variants. Affecteds-only analysis resulted in virtually no power to correctly classify benign variants and reduced power to classify pathogenic variants. These results can be used to guide recruitment efforts to classify rare and private VUS.

The BRCA2 variant c.68-7 T>A is associated with breast cancer

Background

BRCA2 c.68-7T>A has been demonstrated to cause aberrant splicing and is possibly pathogenic. The population prevalence of the variant is 0.2%, which higher than usual for pathogenic BRCA2 variants. The pathogenicity of the variant is discussed.

Methods

The outpatient genetic clinic at The Norwegian Radium Hospital, part of Oslo University Hospital, has invited breast cancer kindreds for genetic examinations and prospective follow-up of high risk patients since 1988. We have complete files of all activities and results, and we examined the files for association between BRCA2 c.68-7T>A and breast cancer.

Results

Seventeen out of 714 (2.4%) breast cancer kindreds sequenced for BRCA2 carried the variant BRCA2 c.68-7T>A (p < 0.0001 compared to population controls). Segregation analysis was inconclusive (likelihood ratio 0.36) for pathogenicity. Two breast cancers were prospectively observed during 134 observation years (annual incidence rate 1.5% (95% CI 0.15% to 5.4%) and one additional breast cancer was diagnosed at first (prevalence) round.

Conclusion

BRCA2 c.68-7T>A is associated with breast cancer. In the families selected due to aggregation of breast cancer, carriers of the BRCA2 c.68-7T>A variant have increased risk for breast cancer. It is, however, possible that the variant has lower penetrance than the average pathogenic BRCA2 variants, and that in the families selected for having known aggregation of breast cancer other (modifying) factors contributed to the observed results.

Family-Specific Variants and the Limits of Human Genetics

Every single-nucleotide change compatible with life is present in the human population today. Understanding these rare human variants defines an extraordinary challenge for genetics and medicine. The new clinical practice of sequencing many genes for hereditary cancer risk has illustrated the utility of clinical next-generation sequencing in adults, identifying more medically actionable variants than single-gene testing. However, it has also revealed a linear relationship between the length of DNA evaluated and the number of rare 'variants of uncertain significance' reported. We propose that careful approaches to phenotype-genotype inference, distinguishing between diagnostic and screening intent, in conjunction with expanded use of family-scale genetics studies as a source of information on family-specific variants, will reduce variants of uncertain significance reported to patients.

Family Studies for Classification of Variants of Uncertain Classification: Current Laboratory Clinical Practice and a New Web-Based Educational Tool

Multi-gene cancer panels often identify variants of uncertain clinical significance (VUS) that pose a challenge to health care providers in managing a patient's cancer risk. Family segregation analysis can yield powerful data to re-classify a VUS (as either benign or pathogenic). However, financial and personnel resources to coordinate these studies are limited. In an informal assessment we found that family studies for variant classification are done by most clinical genetics laboratories that offer hereditary cancer panel testing. The process for family studies differs substantially across laboratories. One near universal limitation is that families usually have too few individuals for an informative co-segregation analysis. A unique and potential resource-saving approach is to engage patients and their families in expanding their own pedigrees for segregation analysis of their VUS. We describe a novel public educational tool ( FindMyVariant.org ) designed to inform patients and genetic counselors about strategies to improve the probability of variant classification using familial segregation. While the web tool is designed to be useful for any gene, the project was primarily focused on VUS's returned in cancer risk genes. FindMyVariant.org is a resource for genetic providers to offer motivated families who are willing to gather information about their family relationships and history. Working alongside clinical or research genetic laboratories, the information they collect may help reclassify their VUS using segregation analysis.

Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making

Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening.

Human genetics has entered a new age with the advent of next generation sequencing. However, this great advance also comes with new concerns. Currently, the extensive use of multi-gene panels, whole exome and whole genome sequencing, is generating an ever-growing number of new DNA sequence variations detected in the disease-predisposing genes of human patients. The pathogenic or neutral status of these variants needs to be known before planning any medical act or follow-up. We show here that the status of the variants identified in the BRCA1 breast/ovarian cancer susceptibility gene can be estimated thanks to experimental systems using yeast cells and a novel computational model. Importantly, this model provides a probabilistic classification of variants, opening the possibility to integrate results from functional assays into clinical decision-making. Moreover, our computational model is directly compatible with all kinds of experimental system without any requirement for skills in statistics thanks to ready-to-use online tools. We believe that this work is a step forward in the clinical interpretation of human genetic variants.

Prioritizing Variants in Complete Hereditary Breast and Ovarian Cancer Genes in Patients Lacking Known BRCA Mutations

BRCA1 and BRCA2 testing for hereditary breast and ovarian cancer (HBOC) does not identify all pathogenic variants. Sequencing of 20 complete genes in HBOC patients with uninformative test results (N = 287), including noncoding and flanking sequences of ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, EPCAM, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD51B, STK11, TP53, and XRCC2, identified 38,372 unique variants. We apply information theory (IT) to predict and prioritize noncoding variants of uncertain significance in regulatory, coding, and intronic regions based on changes in binding sites in these genes. Besides mRNA splicing, IT provides a common framework to evaluate potential affinity changes in transcription factor (TFBSs), splicing regulatory (SRBSs), and RNA-binding protein (RBBSs) binding sites following mutation. We prioritized variants affecting the strengths of 10 splice sites (four natural, six cryptic), 148 SRBS, 36 TFBS, and 31 RBBS. Three variants were also prioritized based on their predicted effects on mRNA secondary (2°) structure and 17 for pseudoexon activation. Additionally, four frameshift, two in-frame deletions, and five stop-gain mutations were identified. When combined with pedigree information, complete gene sequence analysis can focus attention on a limited set of variants in a wide spectrum of functional mutation types for downstream functional and co-segregation analysis.

Novel germline mutations and unclassified variants of BRCA1 and BRCA2 genes in Chinese women with familial breast/ovarian cancer

BACKGROUND

Germline mutations in the BRCA1 and BRCA2 genes greatly increase a woman's risk of developing breast and/or ovarian cancer. The prevalence and distribution of such mutations differ across races/ethnicities. Several studies have investigated Chinese women with high-risk breast cancer, but the full spectrum of the mutations in these two genes remains unclear.

METHODS

In this study, 133 unrelated Chinese women with familial breast/ovarian cancer living in Zhejiang, eastern China, were enrolled between the years 2008 and 2014. The complete coding regions and exon-intron boundaries of BRCA1 and BRCA2 were screened by PCR-sequencing assay. Haplotype analysis was performed to confirm BRCA1 and BRCA2 founder mutations. In silico predictions were performed to identify the non-synonymous amino acid changes that were likely to disrupt the functions of BRCA1 and BRCA2.

RESULTS

A total of 23 deleterious mutations were detected in the two genes in 31 familial breast/ovarian cancer patients with a total mutation frequency of 23.3% (31/133). The highest frequency of 50.0% (8/16) was found in breast cancer patients with a history of ovarian cancer. The frequencies of BRCA1 and BRCA2 mutations were 13.5 % (18/133) and 9.8% (13/133), respectively. We identified five novel deleterious mutations (c.3295delC, c.3780_3781delAG, c.4063_4066delAATC, c.5161 > T and c.5173insA) in BRCA1 and seven (c.1-40delGA, c.4487delC, c.469_473delAAGTC, c.5495delC, c.6141T > A, c.6359C > G and c.7588C > T) in BRCA2, which accounted for 52.2% (12/23) of the total mutations. Six recurrent mutations were found, including four (c.3780_3781delAG, c.5154G > A, c.5468-1del8 and c.5470_5477del8) in BRCA1 and two (c.3109C > T and c.5682C > G) in BRCA2. Two recurrent BRCA1 mutations (c.5154G > A and c.5468-1del8) were identified as putative founder mutations. We also found 11 unclassified variants, and nine of these are novel. The possibility was that each of the non-synonymous amino acid changes would disrupt the function of BRCA1 and BRCA2 varied according to the different algorithms used.

CONCLUSIONS

BRCA1 and BRCA2 mutations accounted for a considerable proportion of hereditary breast/ovarian cancer patients from eastern China and the spectrum of the mutations of these two genes exhibited some unique features. The two BRCA1 putative founder mutations may provide a cost-effective option to screen Chinese population, while founder effects of the two mutations should be investigated in a lager sample size of patients.

Classification and Clinical Management of Variants of Uncertain Significance in High Penetrance Cancer Predisposition Genes

In 2008, the International Agency for Research on Cancer (IARC) proposed a system for classifying sequence variants in highly penetrant breast and colon cancer susceptibility genes, linked to clinical actions. This system uses a multifactorial likelihood model to calculate the posterior probability that an altered DNA sequence is pathogenic. Variants between 5%-94.9% (class 3) are categorized as variants of uncertain significance (VUS). This interval is wide and might include variants with a substantial difference in pathogenicity at either end of the spectrum. We think that carriers of class 3 variants would benefit from a fine-tuning of this classification. Classification of VUS to a category with a defined clinical significance is very important because for carriers of a pathogenic mutation full surveillance and risk-reducing surgery can reduce cancer incidence. Counselees who are not carriers of a pathogenic mutation can be discharged from intensive follow-up and avoid unnecessary risk-reducing surgery. By means of examples, we show how, in selected cases, additional data can lead to reclassification of some variants to a different class with different recommendations for surveillance and therapy. To improve the clinical utility of this classification system, we suggest a pragmatic adaptation to clinical practice.

Identification of a Variety of Mutations in Cancer Predisposition Genes in Patients With Suspected Lynch Syndrome

BACKGROUND & AIMS

Multigene panels are commercially available tools for hereditary cancer risk assessment that allow for next-generation sequencing of numerous genes in parallel. However, it is not clear if these panels offer advantages over traditional genetic testing. We investigated the number of cancer predisposition gene mutations identified by parallel sequencing in individuals with suspected Lynch syndrome.

METHODS

We performed germline analysis with a 25-gene, next-generation sequencing panel using DNA from 1260 individuals who underwent clinical genetic testing for Lynch syndrome from 2012 through 2013. All patients had a history of Lynch syndrome-associated cancer and/or polyps. We classified all identified germline alterations for pathogenicity and calculated the frequencies of pathogenic mutations and variants of uncertain clinical significance (VUS). We also analyzed data on patients' personal and family history of cancer, including fulfillment of clinical guidelines for genetic testing.

RESULTS

Of the 1260 patients, 1112 met National Comprehensive Cancer Network (NCCN) criteria for Lynch syndrome testing (88%; 95% confidence interval [CI], 86%-90%). Multigene panel testing identified 114 probands with Lynch syndrome mutations (9.0%; 95% CI, 7.6%-10.8%) and 71 with mutations in other cancer predisposition genes (5.6%; 95% CI, 4.4%-7.1%). Fifteen individuals had mutations in BRCA1 or BRCA2; 93% of these met the NCCN criteria for Lynch syndrome testing and 33% met NCCN criteria for BRCA1 and BRCA2 analysis (P = .0017). An additional 9 individuals carried mutations in other genes linked to high lifetime risks of cancer (5 had mutations in APC, 3 had bi-allelic mutations in MUTYH, and 1 had a mutation in STK11); all of these patients met NCCN criteria for Lynch syndrome testing. A total of 479 individuals had 1 or more VUS (38%; 95% CI, 35%-41%).

CONCLUSIONS

In individuals with suspected Lynch syndrome, multigene panel testing identified high-penetrance mutations in cancer predisposition genes, many of which were unexpected based on patients' histories. Parallel sequencing also detected a high number of potentially uninformative germline findings, including VUS.

New recurrent BRCA1/2 mutations in Polish patients with familial breast/ovarian cancer detected by next generation sequencing

Background

Targeted PCR-based genetic testing for BRCA1 and BRCA2 can be performed at a lower cost than full gene testing; however, it may overlook mutations responsible for familial breast and/or ovarian cancers. In the present study, we report the utility of next generation sequencing (NGS) to identify new pathogenic variants of BRCA1/2.

Methods

BRCA1 and BRCA2 exons were amplified using the Ion AmpliSeq BRCA1/2 Panel and sequenced on the Ion Torrent PGM sequencer in 512 women with familial and/or only early onset breast and/or ovarian cancers who were negative for selected BRCA1/2 mutations.

Results

146 single nucleotide variants (SNVs) and 32 indels were identified. Of them, 14 SNVs and 17 indels were considered as pathogenic or likely pathogenic. One and 18 pathogenic mutations had been detected previously in the Polish and other populations, respectively, and 12 deleterious mutations were previously unknown. Eight mutations were recurrent; Q563X (BRCA1), N3124I (BRCA2) and c.4516delG (BRCA1) were found in eight, six and four patients, respectively, and two other mutations (c.9118-2A > G and c.7249delCA in BRCA2) were detected in three patients each. Altogether, BRCA1/2 pathogenic mutations were identified in 52 out of 512 (10%) patients.

Conclusions

NGS substantially improved the detection rates of a wide spectrum of mutations in Polish patients with familial breast and/or ovarian cancer. Although targeted screening for specific BRCA1 mutations can be offered to all Polish breast or ovarian cancer patients, NGS-based testing is justified in patients with breast or ovarian cancer likely related to BRCA1/2 who test negative for the selected BRCA1/2 pathogenic mutations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0092-2) contains supplementary material, which is available to authorized users.

Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants

Next-generation sequencing technologies are making it possible to study the role of rare variants in human disease. Many studies balance statistical power with cost-effectiveness by (a) sampling from phenotypic extremes and (b) utilizing a two-stage design. Two-stage designs include a broad-based discovery phase and selection of a subset of potential causal genes/variants to be further examined in independent samples. We evaluate three parameters: first, the gain in statistical power due to extreme sampling to discover causal variants; second, the informativeness of initial (Phase I) association statistics to select genes/variants for follow-up; third, the impact of extreme and random sampling in (Phase 2) replication. We present a quantitative method to select individuals from the phenotypic extremes of a binary trait, and simulate disease association studies under a variety of sample sizes and sampling schemes. First, we find that while studies sampling from extremes have excellent power to discover rare variants, they have limited power to associate them to phenotype—suggesting high false-negative rates for upcoming studies. Second, consistent with previous studies, we find that the effect sizes estimated in these studies are expected to be systematically larger compared with the overall population effect size; in a well-cited lipids study, we estimate the reported effect to be twofold larger. Third, replication studies require large samples from the general population to have sufficient power; extreme sampling could reduce the required sample size as much as fourfold. Our observations offer practical guidance for the design and interpretation of studies that utilize extreme sampling.

Development and validation of a new algorithm for the reclassification of genetic variants identified in the BRCA1 and BRCA2 genes

BRCA1 and BRCA2 sequencing analysis detects variants of uncertain clinical significance in approximately 2 % of patients undergoing clinical diagnostic testing in our laboratory. The reclassification of these variants into either a pathogenic or benign clinical interpretation is critical for improved patient management. We developed a statistical variant reclassification tool based on the premise that probands with disease-causing mutations are expected to have more severe personal and family histories than those having benign variants. The algorithm was validated using simulated variants based on approximately 145,000 probands, as well as 286 BRCA1 and 303 BRCA2 true variants. Positive and negative predictive values of ≥99 % were obtained for each gene. Although the history weighting algorithm was not designed to detect alleles of lower penetrance, analysis of the hypomorphic mutations c.5096G>A (p.Arg1699Gln; BRCA1) and c.7878G>C (p.Trp2626Cys; BRCA2) indicated that the history weighting algorithm is able to identify some lower penetrance alleles. The history weighting algorithm is a powerful tool that accurately assigns actionable clinical classifications to variants of uncertain clinical significance. While being developed for reclassification of BRCA1 and BRCA2 variants, the history weighting algorithm is expected to be applicable to other cancer- and non-cancer-related genes.

Genetic testing and familial implications in breast-ovarian cancer families

DNA-testing for BRCA1 and BRCA2 has become incorporated in the diagnostic procedure of patients with breast and/or ovarian cancer. Since 1994 an immense amount of information has been gathered on mutation spectra, mutation risk assessment, cancer risks for mutation carriers, factors that modify these risks, unclassified DNA variants, surveillance strategies and preventive options. For the patient and family the main determinator still is whether a mutation is found or not. When a pathogenic mutation is detected in an index case, relatives can opt for pre-symptomatic DNA testing. However in the vast majority no mutation, or only unclear mutations are detectable yet. This means that a hereditary cause cannot be excluded, but pre-symptomatic DNA-testing is still unavailable for relatives. Surveillance for both index cases and relatives is based of the family history of cancer. Next generation genetic testing may help to elucidate genetic causes in these families.

The implications of familial incidental findings from exome sequencing: the NIH Undiagnosed Diseases Program experience

PURPOSE

Using exome sequence data from 159 families participating in the National Institutes of Health Undiagnosed Diseases Program, we evaluated the number and inheritance mode of reportable incidental sequence variants.

METHODS

Following the American College of Medical Genetics and Genomics recommendations for reporting of incidental findings from next-generation sequencing, we extracted variants in 56 genes from the exome sequence data of 543 subjects and determined the reportable incidental findings for each participant. We also defined variant status as inherited or de novo for those with available parental sequence data.

RESULTS

We identified 14 independent reportable variants in 159 (8.8%) families. For nine families with parental sequence data in our cohort, a parent transmitted the variant to one or more children (nine minor children and four adult children). The remaining five variants occurred in adults for whom parental sequences were unavailable.

CONCLUSION

Our results are consistent with the expectation that a small percentage of exomes will result in identification of an incidental finding under the American College of Medical Genetics and Genomics recommendations. Additionally, our analysis of family sequence data highlights that genome and exome sequencing of families has unavoidable implications for immediate family members and therefore requires appropriate counseling for the family.

Pathogenicity evaluation of BRCA1 and BRCA2 unclassified variants identified in Portuguese breast/ovarian cancer families

Hereditary breast/ovarian cancer syndrome is caused by germline deleterious mutations in BRCA1 and BRCA2. A major problem of genetic testing and counseling is the finding of variants of uncertain significance (VUS). We sought to ascertain the pathogenicity of 25 BRCA1 and BRCA2 VUS identified in Portuguese families during genetic testing. We performed cosegregation analysis of VUS with cancer in families, evaluated their frequency in unaffected controls, and looked for loss of heterozygosity in tumors. In addition, three different bioinformatic algorithms were used (Interactive Biosoftware, ESEfinder, and PolyPhen). Finally, six VUS located in exon-intron boundaries were analyzed by RT-PCR. We found that seven variants segregated with the disease, six variants co-occurred with a pathogenic mutation in the same gene, and four variants co-occurred with a deleterious mutation in the other BRCA gene. By RT-PCR, we observed that four variants (BRCA1 c.4484G>T, BRCA2 c.682-2A>C, BRCA2 c.8488-1G>A, and BRCA2 c.8954-5A>G) disrupted splicing. After the combined analysis, we were able to classify 4 splicing variants as pathogenic mutations, 16 variants as neutral, and 3 variants as polymorphisms; only 2 variants remained classified as VUS. This work highlights the contribution of DNA, RNA, and in silico data to assess the pathogenicity of BRCA1/2 VUS, which, in turn, allows more accurate genetic counseling and clinical management of the families carrying them.

Large numbers of individuals are required to classify and define risk for rare variants in known cancer risk genes

PURPOSE

Up to half of unique genetic variants in genomic evaluations of familial cancer risk will be rare variants of uncertain significance. Classification of rare variants will be an ongoing issue as genomic testing becomes more common.

METHODS

We modified standard power calculations to explore sample sizes necessary to classify and estimate relative disease risk for rare variant frequencies (0.001-0.00001) and varying relative risk (20-1.5), using population-based and family-based designs focusing on breast and colon cancer. We required 80% power and tolerated a 10% false-positive rate because variants tested will be in known genes with high pretest probability.

RESULTS

Using population-based strategies, hundreds to millions of cases are necessary to classify rare cancer variants. Larger samples are necessary for less frequent and less penetrant variants. Family-based strategies are robust to changes in variant frequency and require between 8 and 1,175 individuals, depending on risk.

CONCLUSION

It is unlikely that most rare missense variants will be classifiable in the near future, and accurate relative risk estimates may never be available for very rare variants. This knowledge may alter strategies for communicating information about variants of uncertain significance to patients.

The impact of next generation sequencing on the analysis of breast cancer susceptibility: a role for extremely rare genetic variation?

Women with a family history of breast cancer have an approximately twofold elevated risk of the disease. Even though an array of genes has been associated with breast cancer risk the past two decades, variants within these genes jointly explain at most 40% of this familial risk. Many explanations for this 'missing heritability' have been proposed, including the existence of many very rare variants, interactions between genetic and environmental factors and structural genetic variation. In this review, we discuss how next generation sequencing will teach us more about the genetic architecture of breast cancer, with a specific focus on very rare genetic variants. While such variants potentially explain a substantial proportion of familial breast cancer, assessing the breast cancer risks conferred by them remains challenging, even if this risk is relatively high. To assess more moderate risks, epidemiological approaches will require very large patient cohorts to be genotyped for the variant, only achievable through international collaboration. How well we will be able to eventually resolve the missing heritability for breast cancer in a clinically meaningful way crucially depends on the underlying complexity of the genetic architecture.

BRCA1/2 sequence variants of uncertain significance: a primer for providers to assist in discussions and in medical management

INTRODUCTION

DNA variants of uncertain significance (VUS) are common outcomes of clinical genetic testing for susceptibility to cancer. A statistically rigorous model that provides a pathogenicity score for each variant has been developed to aid in the clinical management of patients undergoing genetic testing.

METHODS

The information in this article is derived from multiple publications on VUS in BRCA genes, distilled for communicating with clinicians who may encounter VUS in their practice.

RESULTS

The posterior probability scores for BRCA1 or BRCA2 VUS, calculated from a multifactorial likelihood model, are explained, and links for looking up specific VUS are provided. The International Agency on Cancer Research (IARC) of the World Health Organization has proposed a simple five-tier system for clinical management that is not widely known to clinicians. Classes 1 and 2 in this system are managed as neutral variants, classes 4 and 5 are managed as pathogenic variants, and class 3 variants still have insufficient evidence to move to either end of this scale and, thus, cannot be used in medical management.

CONCLUSIONS

Development of models that integrate multiple independent lines of evidence has allowed classification of a growing number of VUS in the BRCA1 and BRCA2 genes. The pathogenicity score that is generated by this model maps to the IARC system for clinical management, which will assist clinicians in the medical management of those patients who obtain a VUS result upon testing.

P.Arg82Leu von Hippel-Lindau (VHL) gene mutation among three members of a family with familial bilateral pheochromocytoma in India: molecular analysis and in silico characterization

Various missense mutations in the VHL gene have been reported among patients with familial bilateral pheochromocytoma. However, the p.Arg82Leu mutation in the VHL gene described here among patients with familial bilateral pheochromocytoma, has never been reported previously in a germline configuration. Interestingly, long-term follow-up of these patients indicated that the mutation might have had little impact on the normal function of the VHL gene, since all of them have remained asymptomatic. We further attempted to correlate this information with the results obtained by in silico analysis of this mutation using SIFT, PhD-SNP SVM profile, MutPred, PolyPhen2, and SNPs&GO prediction tools. To gain, new mechanistic insight into the structural effect, we mapped the mutation on to 3D structure (PDB ID 1LM8). Further, we analyzed the structural level changes in time scale level with respect to native and mutant protein complexes by using 12 ns molecular dynamics simulation method. Though these methods predict the mutation to have a pathogenic potential, it remains to be seen if these patients will eventually develop symptomatic disease.

BRCA1 R1699Q variant displaying ambiguous functional abrogation confers intermediate breast and ovarian cancer risk

BACKGROUND

Clinical classification of rare sequence changes identified in the breast cancer susceptibility genes BRCA1 and BRCA2 is essential for appropriate genetic counselling of individuals carrying these variants. We previously showed that variant BRCA1 c.5096G>A p.Arg1699Gln in the BRCA1 transcriptional transactivation domain demonstrated equivocal results from a series of functional assays, and proposed that this variant may confer low to moderate risk of cancer.

METHODS

Measures of genetic risk (report of family history, segregation) were assessed for 68 BRCA1 c.5096G>A p.Arg1699Gln (R1699Q) families recruited through family cancer clinics, comparing results with 34 families carrying the previously classified pathogenic BRCA1 c.5095C>T p.Arg1699Trp (R1699W) mutation at the same residue, and to 243 breast cancer families with no BRCA1 pathogenic mutation (BRCA-X).

RESULTS

Comparison of BRCA1 carrier prediction scores of probands using the BOADICEA risk prediction tool revealed that BRCA1 c.5096G>A p.Arg1699Gln variant carriers had family histories that were less 'BRCA1-like' than BRCA1 c.5095C>T p.Arg1699Trp mutation carriers (p<0.00001), but more 'BRCA1-like' than BRCA-X families (p=0.0004). Further, modified segregation analysis of the subset of 30 families with additional genotyping showed that BRCA1 c.5096G >A p.Arg1699Gln had reduced penetrance compared with the average truncating BRCA1 mutation penetrance (p=0.0002), with estimated cumulative risks to age 70 of breast or ovarian cancer of 24%.

CONCLUSIONS

Our results provide substantial evidence that the BRCA1 c.5096G>A p.Arg1699Gln (R1699Q) variant, demonstrating ambiguous functional deficiency across multiple assays, is associated with intermediate risk of breast and ovarian cancer, highlighting challenges for risk modelling and clinical management of patients of this and other potential moderate-risk variants.

Functional evaluation of BRCA2 variants mapping to the PALB2-binding and C-terminal DNA-binding domains using a mouse ES cell-based assay

Single-nucleotide substitutions and small in-frame insertions or deletions identified in human breast cancer susceptibility genes BRCA1 and BRCA2 are frequently classified as variants of unknown clinical significance (VUS) due to the availability of very limited information about their functional consequences. Such variants can most reliably be classified as pathogenic or non-pathogenic based on the data of their co-segregation with breast cancer in affected families and/or their co-occurrence with a pathogenic mutation. Biological assays that examine the effect of variants on protein function can provide important information that can be used in conjunction with available familial data to determine the pathogenicity of VUS. In this report, we have used a previously described mouse embryonic stem (mES) cell-based functional assay to characterize eight BRCA2 VUS that affect highly conserved amino acid residues and map to the N-terminal PALB2-binding or the C-terminal DNA-binding domains. For several of these variants, very limited co-segregation information is available, making it difficult to determine their pathogenicity. Based on their ability to rescue the lethality of Brca2-deficient mES cells and their effect on sensitivity to DNA-damaging agents, homologous recombination and genomic integrity, we have classified these variants as pathogenic or non-pathogenic. In addition, we have used homology-based modeling as a predictive tool to assess the effect of some of these variants on the structural integrity of the C-terminal DNA-binding domain and also generated a knock-in mouse model to analyze the physiological significance of a residue reported to be essential for the interaction of BRCA2 with meiosis-specific recombinase, DMC1.

A review of a multifactorial probability-based model for classification of BRCA1 and BRCA2 variants of uncertain significance (VUS)

Clinical mutation screening of the BRCA1 and BRCA2 genes for the presence of germline inactivating mutations is used to identify individuals at elevated risk of breast and ovarian cancer. Variants identified during screening are usually classified as pathogenic (increased risk of cancer) or not pathogenic (no increased risk of cancer). However, a significant proportion of genetic tests yields variants of uncertain significance (VUS) that have undefined risk of cancer. Individuals carrying these VUS cannot benefit from individualized cancer risk assessment. Recently, a quantitative "posterior probability model" for assessing the clinical relevance of VUS in BRCA1 or BRCA2, which integrates multiple forms of genetic evidence has been developed. Here, we provide a detailed review of this model. We describe the components of the model and explain how these can be combined to calculate a posterior probability of pathogenicity for each VUS. We explain how the model can be applied to public data and provide tables that list the VUS that have been classified as not pathogenic or pathogenic using this method. While we use BRCA1 and BRCA2 VUS as examples, the method can be used as a framework for classification of the pathogenicity of VUS in other cancer genes.