Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications

Prediction of the functional impact of missense variants in BRCA1 and BRCA2 with BRCA-ML

In silico predictions of missense variants is an important consideration when interpreting variants of uncertain significance (VUS) in the BRCA1 and BRCA2 genes. We trained and evaluated hundreds of machine learning algorithms based on results from validated functional assays to better predict missense variants in these genes as damaging or neutral. This new optimal "BRCA-ML" model yielded a substantially more accurate method than current algorithms for interpreting the functional impact of variants in these genes, making BRCA-ML a valuable addition to data sources for VUS classification.

Germline variants in DNA repair genes associated with hereditary breast and ovarian cancer syndrome: analysis of a 21 gene panel in the Brazilian population

BACKGROUND

The Hereditary Breast and Ovarian Cancer Syndrome (HBOC) occurs in families with a history of breast/ovarian cancer, presenting an autosomal dominant inheritance pattern. BRCA1 and BRCA2 are high penetrance genes associated with an increased risk of up to 20-fold for breast and ovarian cancer. However, only 20-30% of HBOC cases present pathogenic variants in those genes, and other DNA repair genes have emerged as increasing the risk for HBOC. In Brazil, variants in ATM, ATR, CHEK2, MLH1, MSH2, MSH6, POLQ, PTEN, and TP53 genes have been reported in up to 7.35% of the studied cases. Here we screened and characterized variants in 21 DNA repair genes in HBOC patients.

METHODS

We systematically analyzed 708 amplicons encompassing the coding and flanking regions of 21 genes related to DNA repair pathways (ABRAXAS1, ATM, ATR, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MRE11, MSH2, MSH6, NBN, PALB2, PMS2, PTEN, RAD50, RAD51, TP53 and UIMC1). A total of 95 individuals with HBOC syndrome clinical suspicion in Southeast Brazil were sequenced, and 25 samples were evaluated for insertions/deletions in BRCA1/BRCA2 genes. Identified variants were assessed in terms of population allele frequency and their functional effects were predicted through in silico algorithms.

RESULTS

We identified 80 variants in 19 genes. About 23.4% of the patients presented pathogenic variants in BRCA1, BRCA2 and TP53, a frequency higher than that identified among previous studies in Brazil. We identified a novel variant in ATR, which was predicted as pathogenic by in silico tools. The association analysis revealed 13 missense variants in ABRAXAS1, BARD1, BRCA2, CHEK2, CDH1, MLH1, PALB2, and PMS2 genes, as significantly associated with increased risk to HBOC, and the patients carrying those variants did not present large insertions or deletions in BRCA1/BRCA2 genes.

CONCLUSIONS

This study embodies the third report of a multi-gene analysis in the Brazilian population, and addresses the first report of many germline variants associated with HBOC in Brazil. Although further functional analyses are necessary to better characterize the contribution of those variants to the phenotype, these findings would improve the risk estimation and clinical follow-up of patients with HBOC clinical suspicion.

The Number of Signaling Pathways Altered by Driver Mutations in Chronic Lymphocytic Leukemia Impacts Disease Outcome

PURPOSE

Investigation of signaling pathways altered by recurrent gene mutations and their clinical impact in a consecutive cohort of patients with newly diagnosed chronic lymphocytic leukemia (CLL). The heterogeneous clinical course and genetic complexity of CLL warrant improved molecular prognostication. However, the prognostic value of recurrent mutations at the time of diagnosis remains unclear.

EXPERIMENTAL DESIGN

We sequenced samples from 314 consecutive, newly diagnosed patients with CLL to investigate the clinical impact of 56 recurrently mutated genes assessed by next-generation sequencing.

RESULTS

Mutations were identified in 70% of patients with enrichment among IGHV unmutated cases. With 6.5 years of follow-up, 15 mutated genes investigated at the time of diagnosis demonstrated significant impact on time to first treatment (TTFT). Carrying driver mutations was associated with shorter TTFT and poor overall survival. For outcome from CLL diagnosis, the number of signaling pathways altered by driver mutations stratified patients better than the number of driver mutations. Moreover, we demonstrated gradual impact on TTFT with increasing number of altered pathways independent of CLL-IPI risk. Thus, a 25-gene, pathway-based biomarker assessing recurrent mutations refines prognostication in CLL, in particular for CLL-IPI low- and intermediate-risk patients. External validation emphasized that a broad gene panel including low burden mutations was key for the biomarker based on altered pathways.

CONCLUSIONS

We propose to include the number of pathways altered by driver mutations as a biomarker together with CLL-IPI in prospective studies of CLL from time of diagnosis for incorporation into clinical care and personalized follow-up and treatment.

Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort

Purpose

Genetic testing of individuals often results in identification of genomic variants of unknown significance (VUS). Multiple lines of evidence are used to help determine the clinical significance of these variants.

Methods

We analyzed ~138,000 individuals tested by multigene panel testing (MGPT). We used logistic regression to predict carrier status based on personal and family history of cancer. This was applied to 4644 tested individuals carrying 2383 BRCA1/2 variants to calculate likelihood ratios informing pathogenicity for each. Heterogeneity tests were performed for specific classes of variants defined by in silico predictions.

Results

Twenty-two variants labeled as VUS had odds of >10:1 in favor of pathogenicity. The heterogeneity analysis found that among variants in functional domains that were predicted to be benign by in silico tools, a significantly higher proportion of variants were estimated to be pathogenic than previously indicated; that missense variants outside of functional domains should be considered benign; and that variants predicted to create de novo donor sites were also largely benign.

Conclusion

The evidence presented here supports the use of personal and family history from MGPT in the classification of VUS and will be integrated into ongoing efforts to provide large-scale multifactorial classification.

An extensive computational approach to analyze and characterize the functional mutations in the galactose-1-phosphate uridyl transferase (GALT) protein responsible for classical galactosemia

Type I galactosemia is a very rare autosomal recessive genetic metabolic disorder that occurs because of the mutations present in the galactose-1-phosphate uridyl transferase (GALT) gene, resulting in a deficiency of the GALT enzyme. The action of the GALT enzyme is to convert galactose-1-phosphate and uridine diphosphate glucose into glucose-1-phosphate (G1P) and uridine diphosphate-galactose, a crucial second step of the Leloir pathway. A missense mutation in the GALT enzyme leads to variable galactosemia's clinical presentations, ranging from mild to severe. Our study aimed to employ a comprehensive computational pipeline to analyze the most prevalent missense mutations (p.S135L, p.K285 N, p.Q188R, and p.N314D) responsible for galactosemia; these genes could serve as potential targets for chaperone therapy. We analyzed the four mutations through different computational analyses, including amino acid conservation, in silico pathogenicity and stability predictions, and macromolecular simulations (MMS) at 50 ns The stability and pathogenicity predictors showed that the p.Q188R and p.S135L mutants are the most pathogenic and destabilizing. In agreement with these results, MMS analysis demonstrated that the p.Q188R and p.S135L mutants possess higher deviation patterns, reduced compactness, and intramolecular H-bonds of the protein. This could be due to the physicochemical modifications that occurred in the mutants p.S135L and p.Q188R compared to the native. Evolutionary conservation analysis revealed that the most prevalent mutations positions were conserved among different species except N314. The proposed research study is intended to provide a basis for the therapeutic development of drugs and future treatment of classical galactosemia and possibly other genetic diseases using chaperone therapy.

Bioinformatics classification of mutations in patients with Mucopolysaccharidosis IIIA

Mucopolysaccharidosis (MPS) IIIA, also known as Sanfilippo syndrome type A, is a severe, progressive disease that affects the central nervous system (CNS). MPS IIIA is inherited in an autosomal recessive manner and is caused by a deficiency in the lysosomal enzyme sulfamidase, which is required for the degradation of heparan sulfate. The sulfamidase is produced by the N-sulphoglucosamine sulphohydrolase (SGSH) gene. In MPS IIIA patients, the excess of lysosomal storage of heparan sulfate often leads to mental retardation, hyperactive behavior, and connective tissue impairments, which occur due to various known missense mutations in the SGSH, leading to protein dysfunction. In this study, we focused on three mutations (R74C, S66W, and R245H) based on in silico pathogenic, conservation, and stability prediction tool studies. The three mutations were further subjected to molecular dynamic simulation (MDS) analysis using GROMACS simulation software to observe the structural changes they induced, and all the mutants exhibited maximum deviation patterns compared with the native protein. Conformational changes were observed in the mutants based on various geometrical parameters, such as conformational stability, fluctuation, and compactness, followed by hydrogen bonding, physicochemical properties, principal component analysis (PCA), and salt bridge analyses, which further validated the underlying cause of the protein instability. Additionally, secondary structure and surrounding amino acid analyses further confirmed the above results indicating the loss of protein function in the mutants compared with the native protein. The present results reveal the effects of three mutations on the enzymatic activity of sulfamidase, providing a molecular explanation for the cause of the disease. Thus, this study allows for a better understanding of the effect of SGSH mutations through the use of various computational approaches in terms of both structure and functions and provides a platform for the development of therapeutic drugs and potential disease treatments.

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants

Accurate prediction of the impact of genomic variation on phenotype is a major goal of computational biology and an important contributor to personalized medicine. Computational predictions can lead to a better understanding of the mechanisms underlying genetic diseases, including cancer, but their adoption requires thorough and unbiased assessment. Cystathionine-beta-synthase (CBS) is an enzyme that catalyzes the first step of the transsulfuration pathway, from homocysteine to cystathionine, and in which variations are associated with human hyperhomocysteinemia and homocystinuria. We have created a computational challenge under the CAGI framework to evaluate how well different methods can predict the phenotypic effect(s) of CBS single amino acid substitutions using a blinded experimental data set. CAGI participants were asked to predict yeast growth based on the identity of the mutations. The performance of the methods was evaluated using several metrics. The CBS challenge highlighted the difficulty of predicting the phenotype of an ex vivo system in a model organism when classification models were trained on human disease data. We also discuss the variations in difficulty of prediction for known benign and deleterious variants, as well as identify methodological and experimental constraints with lessons to be learned for future challenges.

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.

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.

Incorporation of semi-quantitative analysis of splicing alterations for the clinical interpretation of variants in BRCA1 and BRCA2 genes

BRCA1 and BRCA2 (BRCA1/2) genetic variants that disrupt messenger RNA splicing are commonly associated with increased risks of developing breast/ovarian cancer. The majority of splicing studies published to date rely on qualitative methodologies (i.e., Sanger sequencing), but it is necessary to incorporate semi-quantitative or quantitative approaches to accurately interpret the clinical significance of spliceogenic variants. Here, we characterize the splicing impact of 31 BRCA1/2 variants using semi-quantitative capillary electrophoresis of fluorescent amplicons (CE), Sanger sequencing and allele-specific assays. A total of 14 variants were found to disrupt splicing. Allelic-specific assays could be performed for BRCA1 c.302-1G>A and BRCA2 c.516+2T>A, c.1909+1G>A, c.8332-13T>G, c.8332-2A>G, c.8954-2A>T variants, showing a monoallelic contribution to full-length transcript expression that was concordant with semi-quantitative data. The splicing fraction of alternative and aberrant transcripts was also measured by CE, facilitating variant interpretation. Following Evidence-based Network for the Interpretation of Germline Mutant Alleles criteria, we successfully classified eight variants as pathogenic (Class 5), five variants as likely pathogenic (Class 4), and 14 variants as benign (Class 1). We also provide splicing data for four variants classified as uncertain (Class 3), which produced a "leaky" splicing effect or introduced a missense change in the protein sequence, that will require further assessment to determine their clinical significance.

Genetic variant pathogenicity prediction trained using disease-specific clinical sequencing data sets

Recent advances in DNA sequencing have expanded our understanding of the molecular basis of genetic disorders and increased the utilization of clinical genomic tests. Given the paucity of evidence to accurately classify each variant and the difficulty of experimentally evaluating its clinical significance, a large number of variants generated by clinical tests are reported as variants of unknown clinical significance. Population-scale variant databases can improve clinical interpretation. Specifically, pathogenicity prediction for novel missense variants can use features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant data set. Here, we introduce one variant data set derived from clinical sequencing panels and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This data set is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further use this data set to demonstrate the necessity of disease-specific classifiers and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant-level features. PathoPredictor achieves an average precision >90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. The accumulation of larger clinical variant training data sets can significantly enhance their performance in a disease- and gene-specific manner.

Towards controlled terminology for reporting germline cancer susceptibility variants: an ENIGMA report

The vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid expansion of genetic testing brought about by wide availability of high-throughput massively parallel sequencing platforms, accurate variant interpretation has become a major issue. The vocabulary used to describe single genetic variants in silico, in vitro, in vivo and as a contributor to human disease uses terms in common, but the meaning is not necessarily shared across all these contexts. In the setting of cancer genetic tests, the added dimension of using data from genetic sequencing of tumour DNA to direct treatment is an additional source of confusion to those who are not experienced in cancer genetics. The language used to describe variants identified in cancer susceptibility genetic testing typically still reflects an outdated paradigm of Mendelian inheritance with dichotomous outcomes. Cancer is a common disease with complex genetic architecture; an improved lexicon is required to better communicate among scientists, clinicians and patients, the risks and implications of genetic variants detected. This review arises from a recognition of, and discussion about, inconsistencies in vocabulary usage by members of the ENIGMA international multidisciplinary consortium focused on variant classification in breast-ovarian cancer susceptibility genes. It sets out the vocabulary commonly used in genetic variant interpretation and reporting, and suggests a framework for a common vocabulary that may facilitate understanding and clarity in clinical reporting of germline genetic tests for cancer susceptibility.

A quantitative model to predict pathogenicity of missense variants in the TP53 gene

Germline pathogenic variants in the TP53 gene cause Li-Fraumeni syndrome, a condition that predisposes individuals to a wide range of cancer types. Identification of individuals carrying a TP53 pathogenic variant is linked to clinical management decisions, such as the avoidance of radiotherapy and use of high-intensity screening programs. The aim of this study was to develop an evidence-based quantitative model that integrates independent in silico data (Align-GVGD and BayesDel) and somatic to germline ratio (SGR), to assign pathogenicity to every possible missense variant in the TP53 gene. To do this, a likelihood ratio for pathogenicity (LR) was derived from each component calibrated using reference sets of assumed pathogenic and benign missense variants. A posterior probability of pathogenicity was generated by combining LRs, and algorithm outputs were validated using different approaches. A total of 730 TP53 missense variants could be assigned to a clinically interpretable class. The outputs of the model correlated well with existing clinical information, functional data, and ClinVar classifications. In conclusion, these quantitative outputs provide the basis for individualized assessment of cancer risk useful for clinical interpretation. In addition, we propose the value of the novel SGR approach for use within the ACMG/AMP guidelines for variant classification.

GFP-Fragment Reassembly Screens for the Functional Characterization of Variants of Uncertain Significance in Protein Interaction Domains of the BRCA1 and BRCA2 Genes

Genetic testing for BRCA1 and BRCA2 genes has led to the identification of many unique variants of uncertain significance (VUS). Multifactorial likelihood models that predict the odds ratio for VUS in favor or against cancer causality, have been developed, but their use is conditioned by the amount of necessary data, which are difficult to obtain if a variant is rare. As an alternative, variants mapping to the coding regions can be examined using in vitro functional assays. BRCA1 and BRCA2 proteins promote genome protection by interacting with different proteins. In this study, we assessed the functional effect of two sets of variants in BRCA genes by exploiting the green fluorescent protein (GFP)-reassembly in vitro assay, which was set-up to test the BRCA1/BARD1, BRCA1/UbcH5a, and BRCA2/DSS1 interactions. Based on the findings observed for the validation panels of previously classified variants, BRCA1/UbcH5a and BRCA2/DSS1 binding assays showed 100% sensitivity and specificity in identifying pathogenic and non-pathogenic variants. While the actual efficiency of these assays in assessing the clinical significance of BRCA VUS has to be verified using larger validation panels, our results suggest that the GFP-reassembly assay is a robust method to identify variants affecting normal protein functioning and contributes to the classification of VUS.

BRCA Challenge: BRCA Exchange as a global resource for variants in BRCA1 and BRCA2

The BRCA Challenge is a long-term data-sharing project initiated within the Global Alliance for Genomics and Health (GA4GH) to aggregate BRCA1 and BRCA2 data to support highly collaborative research activities. Its goal is to generate an informed and current understanding of the impact of genetic variation on cancer risk across the iconic cancer predisposition genes, BRCA1 and BRCA2. Initially, reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org. The purpose of the BRCA Exchange is to provide the community with a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype. More than 20,000 variants have been aggregated, three times the number found in the next-largest public database at the project’s outset, of which approximately 7,250 have expert classifications. The data set is based on shared information from existing clinical databases—Breast Cancer Information Core (BIC), ClinVar, and the Leiden Open Variation Database (LOVD)—as well as population databases, all linked to a single point of access. The BRCA Challenge has brought together the existing international Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium expert panel, along with expert clinicians, diagnosticians, researchers, and database providers, all with a common goal of advancing our understanding of BRCA1 and BRCA2 variation. Ongoing work includes direct contact with national centers with access to BRCA1 and BRCA2 diagnostic data to encourage data sharing, development of methods suitable for extraction of genetic variation at the level of individual laboratory reports, and engagement with participant communities to enable a more comprehensive understanding of the clinical significance of genetic variation in BRCA1 and BRCA2.

The goal of this study and paper has been to develop an international resource to generate an informed and current understanding of the impact of genetic variation on cancer risk across the cancer predisposition genes, BRCA1 and BRCA2. Reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org, to provide a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype.

Familial breast cancer and DNA repair genes: Insights into known and novel susceptibility genes from the GENESIS study, and implications for multigene panel testing

Pathogenic variants in BRCA1 and BRCA2 only explain the underlying genetic cause of about 10% of hereditary breast and ovarian cancer families. Because of cost‐effectiveness, multigene panel testing is often performed even if the clinical utility of testing most of the genes remains questionable. The purpose of our study was to assess the contribution of rare, deleterious‐predicted variants in DNA repair genes in familial breast cancer (BC) in a well‐characterized and homogeneous population. We analyzed 113 DNA repair genes selected from either an exome sequencing or a candidate gene approach in the GENESIS study, which includes familial BC cases with no BRCA1 or BRCA2 mutation and having a sister with BC (N = 1,207), and general population controls (N = 1,199). Sequencing data were filtered for rare loss‐of‐function variants (LoF) and likely deleterious missense variants (MV). We confirmed associations between LoF and MV in PALB2, ATM and CHEK2 and BC occurrence. We also identified for the first time associations between FANCI, MAST1, POLH and RTEL1 and BC susceptibility. Unlike other associated genes, carriers of an ATM LoF had a significantly higher risk of developing BC than carriers of an ATM MV (OR_LoF = 17.4 vs. OR_MV = 1.6; p_Het = 0.002). Hence, our approach allowed us to specify BC relative risks associated with deleterious‐predicted variants in PALB2, ATM and CHEK2 and to add MAST1, POLH, RTEL1 and FANCI to the list of DNA repair genes possibly involved in BC susceptibility. We also highlight that different types of variants within the same gene can lead to different risk estimates.

What's new?

Pathogenic variants in BRCA1 and BRCA2 only explain the genetic cause of about 10% of hereditary breast and ovarian cancer families, and the clinical usefulness of testing other genes following the recent introduction of cost‐effective multigene panel sequencing in diagnostics laboratories remains questionable. This large case‐control study describes genetic variation in 113 DNA repair genes and specifies breast cancer relative risks associated with rare deleterious‐predicted variants in PALB2, ATM, and CHEK2. Importantly, different types of variants within the same gene can lead to different risk estimates. The results may help improve risk prediction models and define gene‐specific consensus management guidelines.

Accurate classification of BRCA1 variants with saturation genome editing

Variants of uncertain significance fundamentally limit the clinical utility of genetic information. The challenge they pose is epitomized by BRCA1, a tumour suppressor gene in which germline loss-of-function variants predispose women to breast and ovarian cancer. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Here we use saturation genome editing to assay 96.5% of all possible single-nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Functional effects for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Over 400 non-functional missense SNVs are identified, as well as around 300 SNVs that disrupt expression. We predict that these results will be immediately useful for the clinical interpretation of BRCA1 variants, and that this approach can be extended to overcome the challenge of variants of uncertain significance in additional clinically actionable genes.

Genetic and epigenetic analyses guided by high resolution whole-genome SNP array reveals a possible role of CHEK2 in Wilms tumour susceptibility

Wilms tumour (WT), the most frequent malignant childhood renal tumour, shows a high degree of genetic and epigenetic heterogeneity. Loss of imprinting on chromosome 11p15 is found in a large fraction of cases and mutations in a few genes, including WT1, CTNNB1, WTX, TP53 and, more recently, SIX1, SIX2 and micro RNA processing genes (miRNAPGs), have been observed. However, these alterations are not sufficient to describe the entire spectrum of genetic defects underlying WT development. We inspected data obtained from a previously performed genome-wide single nucleotide polymorphism (SNP) array analysis on 96 WT samples. By selecting focal regions commonly involved in chromosomal anomalies, we identified genes with a possible role in WT development, based on the prior knowledge of their biological relevance, including MYCN, DIS3L2, MIR562, HACE1, GLI3, CDKN2A and CDKN2B, PALB2, and CHEK2. The MYCN hotspot mutation c.131C>T was detected in seven cases (7.3%). Full sequencing of the remaining genes disclosed 16 rare missense variants and a splicing mutation. Most of these were present at the germline level. Promoter analysis of HACE1, CDKN2A and CDKN2B disclosed partial methylation affecting HACE1 in a consistent fraction of cases (85%). Interestingly, of the four missense variants identified in CHEK2, three were predicted to be deleterious by in silico analyses, while an additional variant was observed to alter mRNA splicing, generating a functionally defective protein. Our study adds additional information on putative WT genes, and adds evidences involving CHEK2 in WT susceptibility.

Factors predicting reclassification of variants of unknown significance

Genetic variants of unknown significance (VUS) are an increasingly common result of genetic testing. VUS present dilemmas for treatment and surveillance. Family history may play a role in VUS reclassification over time.

METHODS

All genetic tests performed at a tertiary referral center 2006-2015 were evaluated for the presence of VUS. Patients with VUS were evaluated for demographics, clinical characteristics, family history, and gene characteristics.

RESULTS

In total, 2291 individuals were tested from 1639 families; 150 VUS were identified. Twenty-eight VUS reclassified, 21 to benign and 7 to pathogenic. Logistic regression demonstrated the number of family members with associated phenotypic disease was a significant predictor of reclassification.

CONCLUSION

The likelihood of VUS reclassification can be predicted by increased positive family history of disease. Most VUS reclassify to benign, but one-fourth reclassify to pathogenic. The actual risk of a VUS should be assessed based on family history and routinely checked for reclassification.

Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework

PURPOSE

We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning.

METHODS

The ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity.

RESULTS

We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as variant of uncertain significance (VUS).

CONCLUSION

By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.

Substantial evidence for the clinical significance of missense variant BRCA1 c.5309G>T p.(Gly1770Val)

PURPOSE

Classification of rare BRCA1 missense variants presents a major challenge for the counseling and treatment of patients. Variant classification can be complicated by conflicting lines of evidence. BRCA1 c.5309G>T p.(Gly1770Val) has been shown to abrogate BRCA1 protein homologous DNA repair; however, multiple sequence alignment demonstrates a lack of sequence conservation at this position, suggesting that glycine at position 1770 may not be essential for cellular maintenance in humans. We analyzed clinical information to resolve the classification of BRCA1 c.5309G>T p.(Gly1770Val).

METHODS

We performed multifactorial likelihood analysis combining segregation data for 14 informative families, and breast tumor histopathological data for 17 variant carriers, ascertained through the ENIGMA consortium.

RESULTS

Bayes segregation analysis gave a likelihood ratio of 101:1 in favor of pathogenicity. The vast majority of breast tumors showed features indicative of pathogenic variant carrier status, resulting in a likelihood ratio of 15800794:1 towards pathogenicity. Despite a low prior probability of pathogenicity (0.03) based on bioinformatic prediction, multifactorial likelihood analysis including segregation and histopathology analysis gave a posterior probability of > 0.99 and final classification of Pathogenic.

CONCLUSIONS

We provide evidence that BRCA1 c.5309G>T p.(Gly1770Val), previously described as a Moroccan founder variant, should be treated as a disease-causing variant despite a lack of evolutionary conservation at this amino acid position. Additionally, we stress that bioinformatic information should be used in combination with other data, either direct clinical evidence or some form of clinical calibration, to arrive at a final clinical classification.

Pancreatic cancer as a sentinel for hereditary cancer predisposition

BACKGROUND

Genes associated with hereditary breast and ovarian cancer (HBOC) and colorectal cancer (CRC) predisposition have been shown to play a role in pancreatic cancer susceptibility. Growing evidence suggests that pancreatic cancer may be useful as a sentinel cancer to identify families that could benefit from HBOC or CRC surveillance, but to date pancreatic cancer is only considered an indication for genetic testing in the context of additional family history.

METHODS

Preliminary data generated at the Huntsman Cancer Hospital (HCH) included variants identified on a custom 34-gene panel or 59-gene panel including both known HBOC and CRC genes for respective sets of 66 and 147 pancreatic cancer cases, unselected for family history. Given the strength of preliminary data and corresponding literature, 61 sequential pancreatic cancer cases underwent a custom 14-gene clinical panel. Sequencing data from HCH pancreatic cancer cases, pancreatic cancer cases of the Cancer Genome Atlas (TCGA), and an unselected pancreatic cancer screen from the Mayo Clinic were combined in a meta-analysis to estimate the proportion of carriers with pathogenic and high probability of pathogenic variants of uncertain significance (HiP-VUS).

RESULTS

Approximately 8.6% of unselected pancreatic cancer cases at the HCH carried a variant with potential HBOC or CRC screening recommendations. A meta-analysis of unselected pancreatic cancer cases revealed that approximately 11.5% carry a pathogenic variant or HiP-VUS.

CONCLUSION

With the inclusion of both HBOC and CRC susceptibility genes in a panel test, unselected pancreatic cancer cases act as a useful sentinel cancer to identify asymptomatic at-risk relatives who could benefit from relevant HBOC and CRC surveillance measures.

Structural analysis of missense mutations in galactokinase 1 (GALK1) leading to galactosemia type-2

Galactosemia type 2 is an autosomal recessive disorder characterized by the deficiency of galactokinase (GALK) enzyme due to missense mutations in GALK1 gene, which is associated with various manifestations such as hyper galactosemia and formation of cataracts. GALK enzyme catalyzes the adenosine triphosphate (ATP)-dependent phosphorylation of α-d-galactose to galactose-1-phosphate. We searched 4 different literature databases (Google Scholar, PubMed, PubMed Central, and Science Direct) and 3 gene-variant databases (Online Mendelian Inheritance in Man, Human Gene Mutation Database, and UniProt) to collect all the reported missense mutations associated with GALK deficiency. Our search strategy yielded 32 missense mutations. We used several computational tools (pathogenicity and stability, biophysical characterization, and physiochemical analyses) to prioritize the most significant mutations for further analyses. On the basis of the pathogenicity and stability predictions, 3 mutations (P28T, A198V, and L139P) were chosen to be tested further for physicochemical characterization, molecular docking, and simulation analyses. Molecular docking analysis revealed a decrease in interaction between the protein and ATP in all the 3 mutations, and molecular dynamic simulations of 50 ns showed a loss of stability and compactness in the mutant proteins. As the next step, comparative physicochemical changes of the native and the mutant proteins were carried out using essential dynamics. Overall, P28T and A198V were predicted to alter the structure and function of GALK protein when compared to the mutant L139P. This study demonstrates the power of computational analysis in variant classification and interpretation and provides a platform for developing targeted therapeutics.

Comprehensive annotation of BRCA1 and BRCA2 missense variants by functionally validated sequence-based computational prediction models

Purpose:

To improve methods for predicting the impact of missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 on protein function.

Methods:

Functional data for 248 BRCA1 and 207 BRCA2 variants from assays with established high sensitivity and specificity for damaging variants were used to recalibrate 40 in silico algorithms predicting the impact of variants on protein activity. Additional RandomForest (RF) and Naïve Voting Method (NVM) meta-predictors for both BRCA1 and BRCA2 were developed to increase predictive accuracy.

Results:

Optimized thresholds for in silico prediction models significantly improved the accuracy of predicted functional effects for BRCA1 and BRCA2 variants. In addition, new BRCA1-RF and BRCA2-RF meta-predictors showed AUC values of 0.92 (95%CI:0.88–0.96) and 0.90 (95%CI:0.84–0.95), respectively. Similarly, the BRCA1-NVM and BRCA2-NVM models had AUCs of 0.93 and 0.90. The RF and NVM models were used to predict the pathogenicity of all possible missense variants in BRCA1 and BRCA2.

Conclusion:

The recalibrated algorithms and new meta-predictors significantly improved upon current models for predicting the impact of variants in cancer risk-associated domains of BRCA1 and BRCA2. Prediction of the functional impact of all possible variants in BRCA1 and BRCA2 provides important information about the clinical relevance of variants in these genes.

Distinct Clinical and Genetic Findings in Iranian Patients With Glycogen Storage Disease Type 3

OBJECTIVES

Glycogen storage disease type 3 (GSD-III) is a rare inherited metabolic disorder caused by glycogen debranching enzyme deficiency. Various pathogenic mutations of the AGL gene lead to abnormal accumulation of glycogen in liver, skeletal, and cardiac muscles. Here, we report distinct clinical and genetic data of Iranian patients with GSD-III.

METHODS

Clinical and laboratory data of 5 patients with GSD-III were recorded. Genetic investigation was performed to identify the causative mutations.

RESULTS

Three patients had typical liver involvement in childhood and one was diagnosed 2 years after liver transplantation for cirrhosis of unknown etiology. Four patients had vacuolar myopathy with glycogen excess in muscle biopsy. All patients had novel homozygous mutations of the AGL gene namely c.378T>A, c.3295T>C, c.3777G>A, c.2002-2A>G, and c.1183C>T.

CONCLUSIONS

This is the first comprehensive report of patients with GSD-III in Iran with 2 uncommon clinical presentations and 5 novel mutations in the AGL gene.

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics

Background

The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer.

Methods

We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches.

Results

PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer.

Conclusion

We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0353-y) contains supplementary material, which is available to authorized users.

Somatic BRCA1 mutations in clinically sporadic breast cancer with medullary histological features

BACKGROUND

The role of somatic BRCA1/2 gene mutations in breast cancer is getting increasing attention in view of hereditary disease. The medullary phenotype and triple negative intrinsic subtypes are often, but not exclusively encountered in BRCA1 germline mutated breast cancer, whilst for BRCA2, no association to specific histological features are known. In this study, we addressed the relationship between morphological medullary phenotype and BRCA1/2 somatic mutations in breast cancer without known positive family anamnesis.

METHODS

32 clinically sporadic breast cancers with medullary features were analyzed for somatic BRCA1/2 mutations (all coding exons) with next-generation sequencing technology. Paraffin-embedded formalin-fixed breast cancer samples from all patients were analyzed.

RESULTS

Three of 32 tumors (9%) had pathogenic (ARUP class-5) BRCA1 gene alterations. Two of these pathogenic variants exhibited deletions leading to frameshift mutations (p.Glu23fs, p.Val1234fs), and the remaining single-nucleotid-variant resulted in premature STOP codon (p.Glu60Ter). In one patient, the same pathogenic BRCA1 mutation was detected (p.Glu23fs) in normal breast tissue. Retrospective follow-up in two patients revealed a positive family history for breast cancer and consecutive germline mutation testing confirmed presence of BRCA1 mutations. No somatic pathogenic BRCA2 mutations were detected.

CONCLUSIONS

BRCA1 mutation testing may be useful in clinically sporadic breast cancer patients with medullary features to identify potential mutation carriers independently from intrinsic molecular subtype. Formalin-fixed paraffin-embedded cancer tissue can undergo testing within a routine molecular-diagnostic setting as a clinical BRCA1/2 mutation screening strategy.

Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ?99% probability of pathogenicity, and 73 had ?95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.

BRCA1 and BRCA2 mutation spectrum - an update on mutation distribution in a large cancer genetics clinic in Norway

Background

Founder mutations in the two breast cancer genes, BRCA1 and BRCA2, have been described in many populations, among these are Ashkenazi-Jewish, Polish, Norwegian and Icelandic. Founder mutation testing in patients with relevant ancestry has been a cost-efficient approach in such populations. Four Norwegian BRCA1 founder mutations were defined by haplotyping in 2001, and accounted for 68% of BRCA1 mutation carriers at the time. After 15 more years of genetic testing, updated knowledge on the mutation spectrum of both BRCA1 and BRCA2 in Norway is needed. In this study, we aim at describing the mutation spectrum and frequencies in the BRCA1/2 carrier population of the largest clinic of hereditary cancer in Norway.

Methods

A total of 2430 BRCA1 carriers from 669 different families, and 1092 BRCA2 carriers from 312 different families were included in a quality of care study. All variants were evaluated regarding pathogenicity following ACMG/ENIGMA criteria. The variants were assessed in AlaMut and supplementary databases to determine whether they were known to be founder mutations in other populations.

Results

There were 120 different BRCA1 and 87 different BRCA2 variants among the mutation carriers. Forty-six per cent of the registered BRCA1/2 families (454/981) had a previously reported Norwegian founder mutation. The majority of BRCA1/2 mutations (71%) were rare, each found in only one or two families. Fifteen per cent of BRCA1 families and 25% of BRCA2 families had one of these rare variants. The four well-known Norwegian BRCA1 founder mutations previously confirmed through haplotyping were still the four most frequent mutations in BRCA1 carriers, but the proportion of BRCA1 mutation carriers accounted for by these mutations had fallen from 68 to 52%, and hence the founder effect was weaker than previously described.

Conclusions

The spectrum of BRCA1 and BRCA2 mutations in the carrier population at Norway’s largest cancer genetics clinic is diverse, and with a weaker founder effect than previously described. As a consequence, retesting the families that previously have been tested with specific tests/founder mutation tests should be a prioritised strategy to find more mutation positive families and possibly prevent cancer in healthy relatives.

The genetic profile of Leber congenital amaurosis in an Australian cohort

BACKGROUND

Leber congenital amaurosis (LCA) is a severe visual impairment responsible for infantile blindness, representing ~5% of all inherited retinal dystrophies. LCA encompasses a group of heterogeneous disorders, with 24 genes currently implicated in pathogenesis. Such clinical and genetic heterogeneity poses great challenges for treatment, with personalized therapies anticipated to be the best treatment candidates. Unraveling the individual genetic etiology of disease is a prerequisite for personalized therapies, and could identify potential treatment candidates, inform patient management, and discriminate syndromic forms of disease.

METHODS

We have genetically analyzed 45 affected and 82 unaffected individuals from 34 unrelated LCA pedigrees using predominantly next-generation sequencing and Array CGH technology.

RESULTS

We present the molecular findings for an Australian LCA cohort, sourced from the Australian Inherited Retinal Disease Registry & DNA Bank. CEP290 and GUCY2D mutations, each represent 19% of unrelated LCA cases, followed by NMNAT1 (12%). Genetic subtypes were consistent with other reports, and were resolved in 90% of this cohort.

CONCLUSION

The high resolution rate achieved, equivalent to recent findings using whole exome/genome sequencing, reflects the progression from hypothesis (LCA Panel) to non-hypothesis (RD Panel) testing and, coupled with Array CGH analysis, is a highly effective first-tier test for LCA.

BRCA1/2 missense mutations and the value of in-silico analyses

INTRODUCTION

The clinical implications of genetic variants in BRCA1/2 in healthy and affected individuals are considerable. Variant interpretation, however, is especially challenging for missense variants. The majority of them are classified as variants of unknown clinical significance (VUS). Computational (in-silico) predictive programs are easy to access, but represent only one tool out of a wide range of complemental approaches to classify VUS. With this single-center study, we aimed to evaluate the impact of in-silico analyses in a spectrum of different BRCA1/2 missense variants.

METHODS

We conducted mutation analysis of BRCA1/2 in 523 index patients with suspected hereditary breast and ovarian cancer (HBOC). Classification of the genetic variants was performed according to the German Consortium (GC)-HBOC database. Additionally, all missense variants were classified by the following three in-silico prediction tools: SIFT, Mutation Taster (MT2) and PolyPhen2 (PPH2).

RESULTS

Overall 201 different variants, 68 of which constituted missense variants were ranked as pathogenic, neutral, or unknown. The classification of missense variants by in-silico tools resulted in a higher amount of pathogenic mutations (25% vs. 13.2%) compared to the GC-HBOC-classification. Altogether, more than fifty percent (38/68, 55.9%) of missense variants were ranked differently. Sensitivity of in-silico-tools for mutation prediction was 88.9% (PPH2), 100% (SIFT) and 100% (MT2).

CONCLUSION

We found a relevant discrepancy in variant classification by using in-silico prediction tools, resulting in potential overestimation and/or underestimation of cancer risk. More reliable, notably gene-specific, prediction tools and functional tests are needed to improve clinical counseling.

In Silico Systems Biology Analysis of Variants of Uncertain Significance in Lynch Syndrome Supports the Prioritization of Functional Molecular Validation

Lynch syndrome (LS) is a genetic condition secondary to germline alterations in the DNA mismatch repair (MMR) genes with 30% of changes being variants of uncertain significance (VUS). Our aim was to perform an in silico reclassification of VUS from a large single institutional cohort that will help prioritizing functional validation. A total of 54 VUS were detected with 33 (61%) novel variants. We integrated family history, pathology, and genetic information along with supporting evidence from eight different in silico tools at the RNA and protein level. Our assessment allowed us to reclassify 54% (29/54) of the VUS as probably damaging, 13% (7/54) as possibly damaging, and 28% (15/54) as probably neutral. There are more than 1,000 VUS reported in MMR genes and our approach facilitates the prioritization of further functional efforts to assess the pathogenicity to those classified as probably damaging. Cancer Prev Res; 10(10); 580-7. ©2017 AACR.

The BRCA1 c. 5096G>A p.Arg1699Gln (R1699Q) intermediate risk variant: breast and ovarian cancer risk estimation and recommendations for clinical management from the ENIGMA consortium

BACKGROUND

We previously showed that the BRCA1 variant c.5096G>A p.Arg1699Gln (R1699Q) was associated with an intermediate risk of breast cancer (BC) and ovarian cancer (OC). This study aimed to assess these cancer risks for R1699Q carriers in a larger cohort, including follow-up of previously studied families, to further define cancer risks and to propose adjusted clinical management of female BRCA1*R1699Q carriers.

METHODS

Data were collected from 129 BRCA1*R1699Q families ascertained internationally by ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium members. A modified segregation analysis was used to calculate BC and OC risks. Relative risks were calculated under both monogenic model and major gene plus polygenic model assumptions.

RESULTS

In this cohort the cumulative risk of BC and OC by age 70 years was 20% and 6%, respectively. The relative risk for developing cancer was higher when using a model that included the effects of both the R1699Q variant and a residual polygenic component compared with monogenic model (for BC 3.67 vs 2.83, and for OC 6.41 vs 5.83).

CONCLUSION

Our results confirm that BRCA1*R1699Q confers an intermediate risk for BC and OC. Breast surveillance for female carriers based on mammogram annually from age 40 is advised. Bilateral salpingo-oophorectomy should be considered based on family history.

Suggestion of BRCA1 c.5339T>C (p.L1780P) variant confer from 'unknown significance' to 'Likely pathogenic' based on clinical evidence in Korea

PURPOSE

We describe a rationale for the re-classification of the BRCA1 c.5539T>C (L1780P) variant using a clinical evidence.

METHODS

A retrospective review was conducted to identify all patients with breast or ovarian cancer and the L1780P variant between 2002 and 2015 at a single institution.

RESULTS

We identified the BRCA1/2 genetic mutation test results of 1223 breast cancer patients and 174 patients with ovarian cancer. Of the 160 BRCA 1/2 variant unknown significance, 16 (10.0%) patients were identified as having the L1780P variant. Among them, 10 had breast cancer, 4 had ovarian cancer, and 2 had both breast and ovarian cancer. Thirteen (81.3%) patients with this variant had family histories of breast or ovarian cancer. Two (16.7%) also had comorbid ovarian cancer. Two patients with this variant showed that co-segregation of the disease in multiple family members and family histories of breast and ovarian cancer. This variant was found to be either absent or at extremely low frequency in general population databases.

CONCLUSION

The L1780P variant might confer to "Likely pathogenic" according to a clinical evidence and the ACMG standards and guidelines. A nation-wide or global survey and a functional analysis are needed to confirm the pathogenicity of the L1780P variant.

The RET E616Q Variant is a Gain of Function Mutation Present in a Family with Features of Multiple Endocrine Neoplasia 2A

The REarranged during Transfection (RET) proto-oncogene is a receptor tyrosine kinase involved in growth and differentiation during embryogenesis and maintenance of the urogenital and nervous systems in mammals. Distinct mutations across hotspot RET exons can cause Multiple Endocrine Neoplasia Type 2A (MEN2A) characterised by development of medullary thyroid cancer (MTC), phaeochromocytoma (PCC) and primary hyperparathyroidism (PHPT), with a strong correlation between genotype and phenotype. Here, we report a 42-year-old man presented in the clinic with a unilateral PCC, with subsequent investigations revealing a nodular and cystic thyroid gland. He proceeded to thyroidectomy, which showed bilateral C-cell hyperplasia (CCH) without evidence of MTC. His brother had neonatal Hirschsprung disease (HSCR). Genetic testing revealed the presence of a heterozygous variant of unknown significance (VUS) in the cysteine-rich region of exon 10 in the RET gene (c.1846G>C, p.E616Q), in both affected siblings and their unaffected mother. Exon 10 RET mutations are known to be associated with HSCR and MEN2. Variants in the cysteine-rich region of the RET gene, outside of the key cysteine residues, may contribute to the development of MEN2 in a less aggressive manner, with a lower penetrance of MTC. Currently, a VUS in RET cannot be used to inform clinical management and direct future care. Analysis of RET^E616Q reveals a gain of function mutant phenotype for this variant, which has not previously been reported, indicating that this VUS should be considered at risk for future clinical management.

Genetic Profiles of Korean Patients With Glucose-6-Phosphate Dehydrogenase Deficiency

Background

We describe the genetic profiles of Korean patients with glucose-6-phosphate dehydrogenase (G6PD) deficiencies and the effects of G6PD mutations on protein stability and enzyme activity on the basis of in silico analysis.

Methods

In parallel with a genetic analysis, the pathogenicity of G6PD mutations detected in Korean patients was predicted in silico. The simulated effects of G6PD mutations were compared to the WHO classes based on G6PD enzyme activity. Four previously reported mutations and three newly diagnosed patients with missense mutations were estimated.

Results

One novel mutation (p.Cys385Gly, labeled G6PD Kangnam) and two known mutations [p.Ile220Met (G6PD São Paulo) and p.Glu416Lys (G6PD Tokyo)] were identified in this study. G6PD mutations identified in Koreans were also found in Brazil (G6PD São Paulo), Poland (G6PD Seoul), United States of America (G6PD Riley), Mexico (G6PD Guadalajara), and Japan (G6PD Tokyo). Several mutations occurred at the same nucleotide, but resulted in different amino acid residue changes in different ethnic populations (p.Ile380 variant, G6PD Calvo Mackenna; p.Cys385 variants, Tomah, Madrid, Lynwood; p.Arg387 variant, Beverly Hills; p.Pro396 variant, Bari; and p.Pro396Ala in India). On the basis of the in silico analysis, Class I or II mutations were predicted to be highly deleterious, and the effects of one Class IV mutation were equivocal.

Conclusions

The genetic profiles of Korean individuals with G6PD mutations indicated that the same mutations may have arisen by independent mutational events, and were not derived from shared ancestral mutations. The in silico analysis provided insight into the role of G6PD mutations in enzyme function and stability.

Computational predictors fail to identify amino acid substitution effects at rheostat positions

Many computational approaches exist for predicting the effects of amino acid substitutions. Here, we considered whether the protein sequence position class - rheostat or toggle - affects these predictions. The classes are defined as follows: experimentally evaluated effects of amino acid substitutions at toggle positions are binary, while rheostat positions show progressive changes. For substitutions in the LacI protein, all evaluated methods failed two key expectations: toggle neutrals were incorrectly predicted as more non-neutral than rheostat non-neutrals, while toggle and rheostat neutrals were incorrectly predicted to be different. However, toggle non-neutrals were distinct from rheostat neutrals. Since many toggle positions are conserved, and most rheostats are not, predictors appear to annotate position conservation better than mutational effect. This finding can explain the well-known observation that predictors assign disproportionate weight to conservation, as well as the field's inability to improve predictor performance. Thus, building reliable predictors requires distinguishing between rheostat and toggle positions.

Screening of BRCA1/2 Mutations Using Direct Sequencing in Indonesian Familial Breast Cancer Cases

Breast cancer has emerged as the most prevalent cancer among women worldwide, including in Indonesia. The contribution of genes associated with high-risk breast-ovarian cancers, BRCA1 and BRCA2, in the Indonesian population is relatively unknown. We have characterized family history of patients with moderate- to high-risk of breast cancer predisposition in 26 unrelated cases from Indonesia for BRCA1/2 mutation analyses using direct sequencing. Known deleterious mutations were not found in either BRCA1 or BRCA2 genes. Seven variants in BRCA2 were documented in 10 of 26 patients (38%). All variants were categorized as unclassified (VUSs). Two synonymous variants, c.3623A>G and c.4035T>C, were found in 5 patients. One variant, c4600T>C, was found in a 38 year old woman with a family history of breast cancer. We have found 4 novel variants in BRCA2 gene including c.6718C>G, c.3281A>G, c.10176C>G, and c4490T>C in 4 unrelated patients, all of them having a positive family history of breast cancer. In accordance to other studies in Asian population, our study showed more frequent variants in BRCA2 compared to BRCA1. Further studies involving larger numbers of hereditary breast cancer patients are required to reveal contribution of BRCA1/2 mutations and/or other predisposing genes among familial breast cancer patients in Indonesia.

Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging

PURPOSE

To present en face optical coherence tomography (OCT) images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities.

METHODS

En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory) and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering)) were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO) and microperimetry.

RESULTS

Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE) pathology due to segmentation error at the level of Bruch's membrane (BM). Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities.

CONCLUSIONS

Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis.

DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer

Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set).  Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.

Assessment of the InSiGHT Interpretation Criteria for the Clinical Classification of 24 MLH1 and MSH2 Gene Variants

Pathogenicity assessment of DNA variants in disease genes to explain their clinical consequences is an integral component of diagnostic molecular testing. The International Society for Gastrointestinal Hereditary Tumors (InSiGHT) has developed specific criteria for the interpretation of mismatch repair (MMR) gene variants. Here, we performed a systematic investigation of 24 MLH1 and MSH2 variants. The assessments were done by analyzing population frequency, segregation, tumor molecular characteristics, RNA effects, protein expression levels, and in vitro MMR activity. Classifications were confirmed for 15 variants and changed for three, and for the first time determined for six novel variants. Overall, based on our results, we propose the introduction of some refinements to the InSiGHT classification rules. The proposed changes have the advantage of homogenizing the InSIGHT interpretation criteria with those set out by the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium for the BRCA1/BRCA2 genes. We also observed that the addition of only few clinical data was sufficient to obtain a more stable classification for variants considered as "likely pathogenic" or "likely nonpathogenic." This shows the importance of obtaining as many as possible points of evidence for variant interpretation, especially from the clinical setting.

Multigene testing of moderate-risk genes: be mindful of the missense

BACKGROUND

Moderate-risk genes have not been extensively studied, and missense substitutions in them are generally returned to patients as variants of uncertain significance lacking clearly defined risk estimates. The fraction of early-onset breast cancer cases carrying moderate-risk genotypes and quantitative methods for flagging variants for further analysis have not been established.

METHODS

We evaluated rare missense substitutions identified from a mutation screen of ATM, CHEK2, MRE11A, RAD50, NBN, RAD51, RINT1, XRCC2 and BARD1 in 1297 cases of early-onset breast cancer and 1121 controls via scores from Align-Grantham Variation Grantham Deviation (GVGD), combined annotation dependent depletion (CADD), multivariate analysis of protein polymorphism (MAPP) and PolyPhen-2. We also evaluated subjects by polygenotype from 18 breast cancer risk SNPs. From these analyses, we estimated the fraction of cases and controls that reach a breast cancer OR≥2.5 threshold.

RESULTS

Analysis of mutation screening data from the nine genes revealed that 7.5% of cases and 2.4% of controls were carriers of at least one rare variant with an average OR≥2.5. 2.1% of cases and 1.2% of controls had a polygenotype with an average OR≥2.5.

CONCLUSIONS

Among early-onset breast cancer cases, 9.6% had a genotype associated with an increased risk sufficient to affect clinical management recommendations. Over two-thirds of variants conferring this level of risk were rare missense substitutions in moderate-risk genes. Placement in the estimated OR≥2.5 group by at least two of these missense analysis programs should be used to prioritise variants for further study. Panel testing often creates more heat than light; quantitative approaches to variant prioritisation and classification may facilitate more efficient clinical classification of variants.

Detection of Germline Mutation in Hereditary Breast and/or Ovarian Cancers by Next-Generation Sequencing on a Four-Gene Panel

Mutation in BRCA1/BRCA2 genes accounts for 20% of familial breast cancers, 5% to 10% of which may be due to other less penetrant genes which are still incompletely studied. Herein, a four-gene panel was used to examine the prevalence of BRCA1, BRCA2, TP53, and PTEN in hereditary breast and ovarian cancers in Southern Chinese population. In this cohort, 948 high-risk breast and/or ovarian patients were recruited for genetic screening by next-generation sequencing (NGS). The performance of our NGS pipeline was evaluated with 80 Sanger-validated known mutations and eight negative cases. With appropriate bioinformatics analysis pipeline, the detection sensitivity of NGS is comparable with Sanger sequencing. The prevalence of BRCA1/BRCA2 germline mutations was 9.4% in our Chinese cohort, of which 48.8% of the mutations arose from hotspot mutations. With the use of a tailor-made algorithm, HomopolymerQZ, more mutations were detected compared with single mutation detection algorithm. The frequencies of PTEN and TP53 were 0.21% and 0.53%, respectively, in the Southern Chinese patients with breast and/or ovarian cancers. High-throughput NGS approach allows the incorporation of control cohort that provides an ethnicity-specific data for polymorphic variants. Our data suggest that hotspot mutations screening such as SNaPshot could be an effective preliminary screening alternative adopted in a standard clinical laboratory without NGS setup.

Comparative analysis of BRCA1 and BRCA2 variants of uncertain significance in patients with breast cancer: a multifactorial probability-based model versus ACMG standards and guidelines for interpreting sequence variants

PURPOSE

To investigate variants of uncertain significance (VUS) in BRCA1 and BRCA2, we assessed the multifactorial posterior probability of VUS in BRCA1 and BRCA2 and compared these analyses with interpretations according to the recently released American College of Medical Genetics and Genomics (ACMG) standards and guidelines.

METHODS

The analysis involved 715 Korean patients with breast cancer. The multifactorial probability of a VUS was analyzed using the prior probability and combined likelihoods of personal and family history, the pathologic profile of the breast cancer, and co-occurrence with pathogenic variants. Results were compared with those obtained according to the ACMG standards/guidelines.

RESULTS

Sixteen VUS from 51 BRCA1 VUS carriers and 28 VUS from 62 BRCA2 VUS carriers were analyzed. There was a slight agreement between the two analyses, with a kappa value of 0.14 (95% confidence interval (CI) = -0.34 to 0.62) for the BRCA1 VUS and a kappa value of 0.17 (95% CI = -0.10 to 0.49) for the BRCA2 VUS.

CONCLUSION

We propose that genetic counseling should be based on the concordant results between these two analyses. When discrepancies are found, those variants are still considered VUS and careful counseling should be provided.Genet Med 18 12, 1250-1257.

Adding In Silico Assessment of Potential Splice Aberration to the Integrated Evaluation of BRCA Gene Unclassified Variants

Clinical mutation screening of the cancer susceptibility genes BRCA1 and BRCA2 generates many unclassified variants (UVs). Most of these UVs are either rare missense substitutions or nucleotide substitutions near the splice junctions of the protein coding exons. Previously, we developed a quantitative method for evaluation of BRCA gene UVs—the “integrated evaluation”—that combines a sequence analysis‐based prior probability of pathogenicity with patient and/or tumor observational data to arrive at a posterior probability of pathogenicity. One limitation of the sequence analysis‐based prior has been that it evaluates UVs from the perspective of missense substitution severity but not probability to disrupt normal mRNA splicing. Here, we calibrated output from the splice‐site fitness program MaxEntScan to generate spliceogenicity‐based prior probabilities of pathogenicity for BRCA gene variants; these range from 0.97 for variants with high probability to damage a donor or acceptor to 0.02 for exonic variants that do not impact a splice junction and are unlikely to create a de novo donor. We created a database http://priors.hci.utah.edu/PRIORS/ that provides the combined missense substitution severity and spliceogenicity‐based probability of pathogenicity for BRCA gene single‐nucleotide substitutions. We also updated the BRCA gene Ex‐UV LOVD, available at http://hci‐exlovd.hci.utah.edu, with 77 re‐evaluable variants.

Functional assays provide a robust tool for the clinical annotation of genetic variants of uncertain significance

Variants of Uncertain Significance (VUS) are genetic variants whose association with a disease phenotype has not been established. They are a common finding in sequencing-based genetic tests and pose a significant clinical challenge. The objective of this study was to assess the use of functional data to classify variants according to pathogenicity. We conduct functional analysis of a large set of BRCA1 VUS combining a validated functional assay with VarCall, a Bayesian hierarchical model to estimate the likelihood of pathogenicity given the functional data. The results from the functional assays were incorporated into a joint analysis of 214 BRCA1 VUS to predict their likelihood of pathogenicity (breast cancer). We show that applying the VarCall model (1.0 sensitivity; lower bound of 95% confidence interval (CI)=0.75 and 1.0 specificity; lower bound of 95% CI=0.83) to the current set of BRCA1 variants, use of the functional data would significantly reduce the number of VUS associated with the C-terminal region of the BRCA1 protein by ~87%. We extend this work developing yeast-based functional assays for two other genes coding for BRCT domain containing proteins, MCPH1 and MDC1. Analysis of missense variants in MCPH1 and MDC1 shows that structural inference based on the BRCA1 data set can aid in prioritising variants for further analysis. Taken together our results indicate that systematic functional assays can provide a robust tool to aid in clinical annotation of VUS. We propose that well-validated functional assays could be used for clinical annotation even in the absence of additional sources of evidence.

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.

Improving performance of multigene panels for genomic analysis of cancer predisposition

PURPOSE

Screening multiple genes for inherited cancer predisposition expands opportunities for cancer prevention; however, reports of variants of uncertain significance (VUS) may limit clinical usefulness. We used an expert-driven approach, exploiting all available information, to evaluate multigene panels for inherited cancer predisposition in a clinical series that included multiple cancer types and complex family histories.

METHODS

For 1,462 sequential patients referred for testing by BROCA or ColoSeq multigene panels, genomic DNA was sequenced and variants were interpreted by multiple experts using International Agency for Research on Cancer guidelines and incorporating evolutionary conservation, known and predicted variant consequences, and personal and family cancer history. Diagnostic yield was evaluated for various presenting conditions and family-history profiles.

RESULTS

Of 1,462 patients, 12% carried damaging mutations in established cancer genes. Diagnostic yield varied by clinical presentation. Actionable results were identified for 13% of breast and colorectal cancer patients and for 4% of cancer-free subjects, based on their family histories of cancer. Incidental findings explaining cancer in neither the patient nor the family were present in 1.7% of subjects. Less than 1% of patients carried VUS in BRCA1 or BRCA2. For all genes combined, initial reports contained VUS for 10.5% of patients, which declined to 7.5% of patients after reclassification based on additional information.

CONCLUSIONS

Individualized interpretation of gene panels is a complex medical activity. Interpretation by multiple experts in the context of personal and family histories maximizes actionable results and minimizes reports of VUS.Genet Med 18 10, 974-981.