Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory

Unlocking the potential of Molecular Tumor Boards: from cutting-edge data interpretation to innovative clinical pathways

The emerging era of precision medicine is characterized by an increasing availability of targeted anticancer therapies and by the parallel development of techniques to obtain more refined molecular data, whose interpretation may not always be straightforward. Molecular tumor boards gather various professional figures, in order to leverage the analysis of molecular data and provide prognostic and predictive insights for clinicians. In addition to healthcare development, they could also become a tool to promote knowledge and research spreading. A growing body of evidence on the application of molecular tumor boards to clinical practice is forming and positive signals are emerging, although a certain degree of heterogeneity exists. This work analyzes molecular tumor boards' potential workflows, figures involved, data sources, sample matrices and eligible patients, as well as available evidence and learning examples. The emerging concept of multi-institutional, disease-specific molecular tumor boards is also considered by presenting two ongoing nationwide experiences.

Clinical implications of conflicting variant interpretations in the cancer genetics clinic

PURPOSE

The aim of this study was to describe the clinical impact of commercial laboratories issuing conflicting classifications of genetic variants.

METHODS

Results from 2000 patients undergoing a multigene hereditary cancer panel by a single laboratory were analyzed. Clinically significant discrepancies between the laboratory-provided test reports and other major commercial laboratories were identified, including differences between pathogenic/likely pathogenic and variant of uncertain significance (VUS) classifications, via review of ClinVar archives. For patients carrying a VUS, clinical documentation was assessed for evidence of provider awareness of the conflict.

RESULTS

Fifty of 975 (5.1%) patients with non-negative results carried a variant with a clinically significant conflict, 19 with a pathogenic/likely pathogenic variant reported in APC or MUTYH, and 31 with a VUS reported in CDKN2A, CHEK2, MLH1, MSH2, MUTYH, RAD51C, or TP53. Only 10 of 28 (36%) patients with a VUS with a clinically significant conflict had a documented discussion by a provider about the conflict. Discrepant counseling strategies were used for different patients with the same variant. Among patients with a CDKN2A variant or a monoallelic MUTYH variant, providers were significantly more likely to make recommendations based on the laboratory-reported classification.

CONCLUSION

Our findings highlight the frequency of variant interpretation discrepancies and importance of clinician awareness. Guidance is needed on managing patients with discrepant variants to support accurate risk assessment.

Regulation of Laboratory-Developed Tests in Preventive Oncology: Emerging Needs and Opportunities

Cancer predictive or diagnostic assays, offered as Laboratory-Developed Tests (LDTs), have been subject to regulatory authority and enforcement discretion by the US Food and Drug Administration. Many LDTs enter the market without US Food and Drug Administration or any regulatory review. The Centers for Medicare & Medicaid Services under the Clinical Laboratory Improvement Amendments focuses on analytic performance, but has limited oversight of the quality or utility of LDTs, including whether patients have been harmed as a result of their use. Increasingly, LDTs for cancer risk or early detection have been marketed directly to consumers, with many LDT developers depicting these tests, requested by patients but ordered by personal or company-associated physicians, as procedures falling under the practice of medicine. This patchwork of regulation and enforcement uncertainty regarding LDTs and public concerns about accuracy of tests given emergency authorization during the COVID-19 pandemic led to the Verifying Accurate Leading-edge IVCT (in vitro clinical test) Development Act of 2021. This pending federal legislation represents an opportunity to harmonize regulatory policies and address growing concerns over quality, utility, and safety of LDTs for cancer genomics, including tests marketed directly to consumers. We review here questions regarding the potential benefits and harms of some cancer-related LDTs for cancer risk and presymptomatic molecular diagnosis, increasingly marketed to oncologists or directly to the worried well. We offer specific proposals to strengthen oversight of the accuracy and clinical utility of cancer genetic testing to ensure public safety.

Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer, Part 1: Technical Considerations

Simple Summary

High-grade serous ovarian cancer (HGSOC) is the most frequent and lethal form of ovarian cancer and is associated with homologous recombination deficiency (HRD) in 50% of cases. This specific alteration is associated with sensitivity to PARP inhibitors (PARPis). Despite vast prognostic improvements due to PARPis, current molecular assays assessing HRD status suffer from several limitations, and there is an urgent need for a more accurate evaluation. In these companion reviews (Part 1: Technical considerations; Part 2: Medical perspectives), we develop an integrative review to provide physicians and researchers involved in HGSOC management with a holistic perspective, from translational research to clinical applications.

Abstract

High-grade serous ovarian cancer (HGSOC), the most frequent and lethal form of ovarian cancer, exhibits homologous recombination deficiency (HRD) in 50% of cases. In addition to mutations in BRCA1 and BRCA2, which are the best known thus far, defects can also be caused by diverse alterations to homologous recombination-related genes or epigenetic patterns. HRD leads to genomic instability (genomic scars) and is associated with PARP inhibitor (PARPi) sensitivity. HRD is currently assessed through BRCA1/2 analysis, which produces a genomic instability score (GIS). However, despite substantial clinical achievements, FDA-approved companion diagnostics (CDx) based on GISs have important limitations. Indeed, despite the use of GIS in clinical practice, the relevance of such assays remains controversial. Although international guidelines include companion diagnostics as part of HGSOC frontline management, they also underscore the need for more powerful and alternative approaches for assessing patient eligibility to PARP inhibitors. In these companion reviews, we review and present evidence to date regarding HRD definitions, achievements and limitations in HGSOC. Part 1 is dedicated to technical considerations and proposed perspectives that could lead to a more comprehensive and dynamic assessment of HR, while Part 2 provides a more integrated approach for clinicians.

Impact of Variant Reclassification in Cancer Predisposition Genes on Clinical Care

PURPOSE

Genetic testing has clinical utility in the management of patients with hereditary cancer syndromes. However, the increased likelihood of encountering a variant of uncertain significance in individuals of non-European descent such as Asians may be challenging to both clinicians and patients. This study aims to evaluate the impact of variant reclassification in an Asian country with variants of uncertain significance reported in cancer predisposition genes.

METHODS

A retrospective analysis of patients seen at the Cancer Genetics Service at the National Cancer Centre Singapore between February 2014 and March 2020 was conducted. The frequency, direction, and time to variant reclassification were evaluated by comparing the reclassified report against the original report.

RESULTS

A total of 1,412 variants of uncertain significance were reported in 49.9% (845 of 1,695) of patients. Over 6 years, 6.7% (94 of 1,412) of variants were reclassified. Most variants of uncertain significance (94.1%, 80 of 85) were downgraded to benign or likely benign variant, with a smaller proportion of variants of uncertain significance (5.9%, 5 of 85) upgraded to pathogenic or likely pathogenic variant. Actionable variants of uncertain significance upgrades and pathogenic or likely pathogenic variant downgrades, which resulted in management changes, happened in 31.0% (39 of 126) of patients. The median and mean time taken for reclassification were 1 and 1.62 year(s), respectively.

CONCLUSION

We propose a clinical guideline to standardize management of patients reported to have variants of uncertain significance. Management should be based on the patient's personal history, family history, and variant interpretation. For clinically relevant or suspicious variants of uncertain significance, follow-up is recommended every 2 years, as actionable reclassifications may happen during this period.

Genetic testing for homologous recombination repair (HRR) in metastatic castration-resistant prostate cancer (mCRPC): challenges and solutions

Patients with metastatic castration-resistant prostate cancer (mCRPC) have an average survival of only 13 months. Identification of novel predictive and actionable biomarkers in the homologous recombination repair (HRR) pathway in up to a quarter of patients with mCRPC has led to the approval of targeted therapies like poly-ADP ribose polymerase inhibitors (PARPi), with the potential to improve survival outcomes. The approval of PARPi has led to guideline bodies such as the National Comprehensive Cancer Network (NCCN) to actively recommend germline and or somatic HRR gene panel testing to identify patients who will benefit from PARPi. However, there are several challenges as genetic testing is still at an early stage especially in low- and middle-income countries, with cost and availability being major impediments. In addition, there are issues such as choice of optimal tissue for genetic testing, archival, storage, retrieval of tissue blocks, interpretation and classification of variants in the HRR pathway, and the need for pretest and post-test genetic counseling. This review provides insights into the HRR gene mutations prevalent in mCRPC and the challenges for a more widespread gene testing to identify actionable germline pathogenic variants and somatic mutations in the HRR pathway, and proposes a clinical algorithm to enhance the efficiency of the gene testing process.

Local Laboratory Testing of Germline BRCA Mutations vs. Myriad: A Single-Institution Experience in Korea

Genetic diagnosis for human epidermal growth factor receptor 2-negative metastatic breast cancer patients with the germline BRCA (gBRCA) mutation has been emphasized since the development of polyadenosine diphosphate-ribose polymerase inhibitors. Myriad Genetics, Inc.’s (Salt Lake City, UT, USA) companion diagnostics service is almost exclusively used for genetic testing. The aim of this study was to compare the results of germline BRCA mutation tests returned by a local laboratory and those performed by Myriad. Between April 2014 and February 2018, 31 patients with gBRCA 1/2 mutation test results from both Samsung Medical Center (Seoul, Korea) and Myriad were enrolled. “Discordant: Opposite classification” was observed for only one among 27 (3.7%). This discrepancy was due to the detection of a deleterious large genomic rearrangement of BRCA 1 by Myriad. Samsung Medical Center performed multiple ligation-dependent probe amplifications (MLPA) to detect large genomic rearrangements only in high-risk patients. This one case was not suspected as high risk and MLPA was not performed. The concordant rate was 74.1% for all 27 patients. “Discordant: Laboratory’s uncertain classification” was found in 22.2% of the sample (six patients). All discrepancies were generated during interpretation of BRCA 2 gene sequencing. Further studies and standardization of genetic testing for BRCA 1/2 genes are required.

Comparison of Open-access Databases for Clinical Variant Interpretation in Cancer: A Case Study of MDS/AML

BACKGROUND

Recently, guidelines for variant interpretation in cancer have been established. However, these guidelines do not mention which databases are most suited to performing this task.

MATERIALS AND METHODS

We give an overview of existing databases and evaluate their benefit in practical application. We compared three meta-databases and 12 databases for a dataset of patients with myelodysplastic syndrome or acute myeloid leukemia.

RESULTS

Clinical implications were found for 13% of all variants. One-third of variants with therapeutic implications were uniquely contained in one database. The VICC meta-database was the most extensive source of information, featuring 92% of variants with a drug association. However, a comparison of meta-databases and original sources indicated that some variants are missing in those meta-databases.

CONCLUSION

Public databases provide decision support for interpreting variants but there is still need for manual curation. Meta-databases facilitate the use of multiple resources but should be interpreted with caution.

Mastermind: A Comprehensive Genomic Association Search Engine for Empirical Evidence Curation and Genetic Variant Interpretation

Design and interpretation of genome sequencing assays in clinical diagnostics and research labs is complicated by an inability to identify information from the medical literature and related databases quickly, comprehensively and reproducibly. This challenge is compounded by the complexity and heterogeneity of nomenclatures used to describe diseases, genes and genetic variants. Mastermind is a widely-used bioinformatic platform of genomic associations that has indexed more than 7.5 M full-text articles and 2.5 M supplemental datasets. It has automatically identified, disambiguated and annotated >6.1 M genetic variants and identified >50 K disease-gene associations. Here, we describe how Mastermind improves the sensitivity and reproducibility of clinical variant interpretation and produces comprehensive genomic landscapes of genetic variants driving pharmaceutical research. We demonstrate an alarmingly high degree of heterogeneity across commercially available panels for hereditary cancer that is resolved by evidence from Mastermind. We further examined the sensitivity of Mastermind for variant interpretation by examining 108 clinically-encountered variants and comparing the results to alternate methods. Mastermind demonstrated a sensitivity of 98.4% compared to 4.4, 45.6, and 37.4% for alternatives PubMed, Google Scholar, and ClinVar, respectively, and a specificity of 98.5% compared to 45.1, 57.6, and 68.8% as well as an increase in content yield of 22.6-, 2.2-, and 2.6-fold. When curated for clinical significance, Mastermind identified more than 4.9-fold more pathogenic variants than ClinVar for representative genes. For structural variants, we compared Mastermind's ability to sensitively identify evidence for 10 representative disease-causing CNVs versus results identified in PubMed, as well as its ability to identify evidence for fusion events compared to COSMIC. Mastermind demonstrated a 4.0- to 43.9-fold increase in references for specific CNVs compared to PubMed, as well as 5.4-fold more fusion genes when compared with COSMIC's curated database. Additionally, Mastermind produced an 8.0-fold increase in reference citations for fusion events common to Mastermind and outside databases. Taken together, these results demonstrate the utility and superiority of Mastermind in terms of both sensitivity and specificity of automated results for clinical diagnostic variant interpretation for multiple genetic variant types and highlight the potential benefit in informing pharmaceutical research.

Implications of Incidental Germline Findings Identified In the Context of Clinical Whole Exome Sequencing for Guiding Cancer Therapy

PURPOSE

Identification of incidental germline mutations in the context of next-generation sequencing is an unintended consequence of advancing technologies. These data are critical for family members to understand disease risks and take action.

PATIENTS AND METHODS

A retrospective cohort analysis was conducted of 1,028 adult patients with metastatic cancer who were sequenced with tumor and germline whole exome sequencing (WES). Germline variant call files were mined for pathogenic/likely pathogenic (P/LP) variants using the ClinVar database and narrowed to high-quality submitters.

RESULTS

Median age was 59 years, with 16% of patients ≤ 45 years old. The most common tumor types were breast cancer (12.5%), colorectal cancer (11.5%), sarcoma (9.3%), prostate cancer (8.4%), and lung cancer (6.6%). We identified 3,427 P/LP variants in 471 genes, and 84% of patients harbored one or more variant. One hundred thirty-two patients (12.8%) carried a P/LP variant in a cancer predisposition gene, with BRCA2 being the most common (1.6%). Patients with breast cancer were most likely to carry a P/LP variant (19.2%). One hundred ten patients (10.7%) carried a P/LP variant in a gene that would be recommended by the American College of Medical Genetics and Genomics to be reported as a result of clinical actionability, with the most common being ATP7B (2.7%), BRCA2 (1.6%), MUTYH (1.4%), and BRCA1 (1%). Of patients who carried a P/LP variant in a cancer predisposition gene, only 53% would have been offered correct testing based on current clinical practice guidelines. Of 471 mutated genes, 231 genes had a P/LP variant identified in one patient, demonstrating significant genetic heterogeneity.

CONCLUSION

The majority of patients undergoing clinical cancer WES harbor a pathogenic germline variation. Identification of clinically actionable germline findings will create additional burden on oncology clinics as broader WES becomes common.

The Frequency of Discordant Variant Classification in the Human Gene Mutation Database: A Comparison of the American College of Medical Genetics and Genomics Guidelines and ClinVar

OBJECTIVE

Discordant variant classifications among public databases is one of the well-documented limitations when interpreting the pathogenicity of variants. The aim of this study is to investigate the level of germline variant misannotation from the Human Gene Mutation Database (HGMD) and the annotation concordance between databases.

METHODS

We used a total of 188,106 classified variants (disease-causing mutations [n = 179,454] and polymorphisms [n = 8652]) in 6466 genes from the HGMD. All variants were reanalyzed based on the American College of Medical Genetics and Genomics (ACMG) guidelines and compared to ClinVar database variants.

RESULTS

When variants were classified based on the ACMG guidelines, misclassification was observed in 3.47% (2289/65,896) of variants. The overall concordance between HGMD and ClinVar was 97.62% (52,499/53,780) of variants studied.

CONCLUSION

Variants in databases must be used with caution when variant pathogenicity is interpreted. This study reveals the frequency of misannotation of the HGMD variants and annotation concordance between databases in depth.

Impact of a Cancer Gene Variant Reclassification Program Over a 20-Year Period

PURPOSE

Hereditary cancer genetic testing can inform personalized medical management for individuals at increased cancer risk. However, many variants in cancer predisposition genes are individually rare, and traditional tools may be insufficient to evaluate pathogenicity. This analysis presents data on variant classification and reclassification over a 20-year period.

PATIENTS AND METHODS

This is a retrospective analysis of > 1.9 million individuals who received hereditary cancer genetic testing from a single clinical laboratory (March 1997 to December 2017). Variant classification included review of evidence from traditional tools (eg, population frequency databases, literature) and laboratory-developed tools (eg, novel statistical methods, in-house RNA analysis) by a multidisciplinary expert committee. Variants may have been reclassified more than once and with more than one line of evidence.

RESULTS

In this time period, 62,842 unique variants were observed across 25 cancer predisposition genes, and 2,976 variants were reclassified. Overall, 82.1% of reclassification events were downgrades (eg, variant of uncertain significance [VUS] to benign), and 17.9% were upgrades (eg, VUS to pathogenic). Among reclassified variants, 82.8% were initially classified as VUS, and 47.5% were identified in ≤ 20 individuals (allele frequency ≤ 0.001%). Laboratory-developed tools were used in 72.3% of variant reclassification events, which affected > 600,000 individuals. More than 1.3 million patients were identified as carrying a variant that was reclassified within this 20-year time period.

CONCLUSION

The variant classification program used by the laboratory evaluated here enabled the reclassification of variants that were individually rare. Laboratory-developed tools were a key component of this program and were used in the majority of reclassifications. This demonstrates the importance of using robust and novel tools to reclassify rare variants to appropriately inform personalized medical management.

SVAD: A genetic database curates non-ischemic sudden cardiac death-associated variants

Sudden cardiac death (SCD) is an important cause of mortality worldwide. It accounts for approximately half of all deaths from cardiovascular disease. While coronary artery disease and acute myocardial infarction account for the majority of SCD in the elderly population, inherited cardiac diseases (inherited CDs) comprise a substantial proportion of younger SCD victims with a significant genetic component. Currently, the use of next-generation sequencing enables the rapid analysis to investigate relationships between genetic variants and inherited CDs causing SCD. Genetic contribution to risk has been considered an alternate predictor of SCD. In the past years, large numbers of SCD susceptibility variants were reported, but these results are scattered in numerous publications. Here, we present the SCD-associated Variants Annotation Database (SVAD) to facilitate the interpretation of variants and to meet the needs of data integration. SVAD contains data from a broad screening of scientific literature. It was constructed to provide a comprehensive collection of genetic variants along with integrated information regarding their effects. At present, SVAD has accumulated 2,292 entries within 1,239 variants by manually surveying pertinent literature, and approximately one-third of the collected variants are pathogenic/likely-pathogenic following the ACMG guidelines. To the best of our knowledge, SVAD is the most comprehensive database that can provide integrated information on the associated variants in various types of inherited CDs. SVAD represents a valuable source of variant information based on scientific literature and benefits clinicians and researchers, and it is now available on http://svad.mbc.nctu.edu.tw/.

Myeloid neoplasms with germline predisposition: Practical considerations and complications in the search for new susceptibility loci

Genomic research in hematological malignancies has focused far more prominently on somatic mutations than on germline variants. Although increasing numbers of germline variants are being identified, a substantial proportion of familial myeloid malignancies have no causal allele pinpointed. Here we review the biological, technological, and clinical challenges that stand in the way of the goal of establishing, implementing, and interpreting a comprehensive panel of germline variants for testing. Achieving this goal would inform care for large numbers of myeloid malignancy patients. Furthermore, knowledge of germline susceptibility variants and their corresponding genes will shed light on disease processes, potentially suggesting therapeutic strategies tailored to specific variants.

Legacy Genetic Testing Results for Cancer Susceptibility: How Common are Conflicting Classifications in a Large Variant Dataset from Multiple Practices?

PURPOSE

The classification of germline variants may differ between labs and change over time. We apply a variant harmonization tool, Ask2Me VarHarmonizer, to map variants to ClinVar and identify discordant variant classifications in a large multipractice variant dataset.

METHODS

A total of 7496 variants sequenced between 1996 and 2019 were collected from 11 clinical practices. Variants were mapped to ClinVar, and lab-reported and ClinVar variant classifications were analyzed and compared.

RESULTS

Of the 4798 unique variants identified, 3699 (77%) were mappable to ClinVar. Among mappable variants, variants of unknown significance (VUS) accounted for 74% of lab-reported classifications and 60% of ClinVar classifications. Lab-reported and ClinVar discordances were present in 783 unique variants (21.2% of all mappable variants); 121 variants (2.5% of all unique variants) had within-practice lab-reported discordances; and 56 variants (1.2% of all unique variants) had lab-reported discordances across practices. The unmappable variants were associated with a higher proportion of lab-reported pathogenic classifications (50% vs. 21%, p < 0.0001) and a lower proportion of lab-reported VUS classifications (46% vs. 74%, p < 0.0001).

CONCLUSIONS

Our study shows that discordant variant classification occurs frequently, which may lead to inappropriate recommendations for prophylactic treatments or clinical management.

Implementing the VMC Specification to Reduce Ambiguity in Genomic Variant Representation

Current methods used for representing biological sequence variants allow flexibility, which has created redundancy within variant archives and discordance among variant representation tools. While research methodologies have been able to adapt to this ambiguity, strict clinical standards make it difficult to use this data in what would otherwise be useful clinical interventions. We implemented a specification developed by the GA4GH Variant Modeling Collaboration (VMC), which details a new approach to unambiguous representation of variants at the allelic level, as a haplotype, or as a genotype. Our implementation, called the VMC Test Suite (http://vcfclin.org), offers web tools to generate and insert VMC identifiers into a VCF file and to generate a VMC bundle JSON representation of a VCF file or HGVS expression. A command line tool with similar functionality is also introduced. These tools facilitate use of this standard-an important step toward reliable querying of variants and their associated annotations.

Predicting Functional Effects of Synonymous Variants: A Systematic Review and Perspectives

Recent advances in high-throughput experimentation have put the exploration of genome sequences at the forefront of precision medicine. In an effort to interpret the sequencing data, numerous computational methods have been developed for evaluating the effects of genome variants. Interestingly, despite the fact that every person has as many synonymous (sSNV) as non-synonymous single nucleotide variants, our ability to predict their effects is limited. The paucity of experimentally tested sSNV effects appears to be the limiting factor in development of such methods. Here, we summarize the details and evaluate the performance of nine existing computational methods capable of predicting sSNV effects. We used a set of observed and artificially generated variants to approximate large scale performance expectations of these tools. We note that the distribution of these variants across amino acid and codon types suggests purifying evolutionary selection retaining generated variants out of the observed set; i.e., we expect the generated set to be enriched for deleterious variants. Closer inspection of the relationship between the observed variant frequencies and the associated prediction scores identifies predictor-specific scoring thresholds of reliable effect predictions. Notably, across all predictors, the variants scoring above these thresholds were significantly more often generated than observed. which confirms our assumption that the generated set is enriched for deleterious variants. Finally, we find that while the methods differ in their ability to identify severe sSNV effects, no predictor appears capable of definitively recognizing subtle effects of such variants on a large scale.

Scaling resolution of variant classification differences in ClinVar between 41 clinical laboratories through an outlier approach

ClinVar provides open access to variant classifications shared from many clinical laboratories. Although most classifications are consistent across laboratories, classification differences exist. To facilitate resolution of classification differences on a large scale, clinical laboratories were encouraged to reassess outlier classifications of variants with medically significant differences (MSDs). Outliers were identified by first comparing ClinVar submissions from 41 clinical laboratories to detect variants with MSDs between the laboratories (650 variants). Next, MSDs were filtered for variants with ≥3 classifications (244 variants), of which 87.6% (213 variants) had a majority consensus in ClinVar, thus allowing for identification of outlier classifications in need of reassessment. Laboratories with outlier classifications were sent a custom report and encouraged to reassess variants. Results were returned for 204 (96%) variants, of which 62.3% (127) were resolved. Of those 127, 64.6% (82) were resolved due to reassessment prompted by this study and 35.4% (45) resolved by a previously completed reassessment. This study demonstrates a scalable approach to classification resolution and capitalizes on the value of data sharing within ClinVar. These activities will help the community move toward more consistent variant classifications, which will improve the care of patients with, or at risk for, genetic disorders.

Management of Gynecologic Cancers In Relation to Genetic Predisposition

OBJECTIVE

To review hereditary gynecologic cancer syndromes and outline current clinical management considerations.

DATA SOURCES

Retrieved articles and guidelines dated 2013-2018 from PubMed, National Comprehensive Cancer Network, American College of Medical Genetics and Genomics, American College of Obstetricians and Gynecologists, American Cancer Society, National Cancer Institute, Centers for Disease Control and Prevention, and National Institutes of Health databases.

CONCLUSION

Advances in genetic testing technology have allowed for the identification of a growing number of patients with genetic mutations associated with hereditary cancer. Individuals with a hereditary predisposition to cancer may qualify for targeted drug therapies, risk-reducing surgeries, and/or high-risk cancer surveillance depending on the specific gene mutation(s) they harbor. Furthermore, there are clinical implications for relatives.

IMPLICATIONS FOR NURSING PRACTICE

This article is an educational guide for oncology nurses who often play a key role in identifying patients at risk for hereditary cancer, prompting referrals for genetic evaluation, and providing follow-up care for these patients.

Genomic variant sharing: a position statement

Sharing de-identified genetic variant data is essential for the practice of genomic medicine and is demonstrably beneficial to patients. Robust genetic diagnoses that inform medical management cannot be made accurately without reference to genetic test results from other patients, as well as population controls. Errors in this process can result in delayed, missed or erroneous diagnoses, leading to inappropriate or missed medical interventions for the patient and their family. The benefits of sharing individual genetic variants, and the harms of not sharing them, are numerous and well-established. Databases and mechanisms already exist to facilitate deposition and sharing of pseudonomised genetic variants, but clarity and transparency around best practice is needed to encourage widespread use, prevent inconsistencies between different communities, maximise individual privacy and ensure public trust. We therefore recommend that widespread sharing of a small number of individual genetic variants associated with limited clinical information should become standard practice in genomic medicine. Information robustly linking genetic variants with specific conditions is fundamental biological knowledge, not personal information, and therefore should not require consent to share. For additional case-level detail about individual patients or more extensive genomic information, which is often essential for clinical interpretation, it may be more appropriate to use a controlled-access model for data sharing, with the ultimate aim of making as much information as open and de-identified as possible with appropriate consent.

Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls

Background

Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8–5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n = 1173) and in cancer-free ethnicity-matched controls (n = 982).

Methods

We used InterVar to classify variants and subsequently conducted a manual review to further examine variants of unknown significance (VUS).

Results

In the 24 genes on the ACMG SF v2.0 list associated with a cancer phenotype, we observed 8 P/LP unique variants (8 individuals; 0.8%) in controls and 11 P/LP unique variants (14 individuals; 1.2%) in cases, a non-significant difference. We reviewed 115 VUS. The median estimated per-variant review time required was 30 min; the first variant within a gene took significantly (p = 0.0009) longer to review (median = 60 min) compared with subsequent variants (median = 30 min). The concordance rate was 83.3% for the variants examined by two reviewers.

Conclusion

The 115 VUS required database and literature review, a time- and labor-intensive process hampered by the difficulty in interpreting conflicting P/LP determinations. By rigorously investigating the 24 ACMG SF v2.0 cancer genes, our work establishes a benchmark P/LP variant prevalence rate in a familial cancer cohort and controls.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0607-5) contains supplementary material, which is available to authorized users.

ClinVar Miner: Demonstrating utility of a Web-based tool for viewing and filtering ClinVar data

ClinVar Miner is a Web-based suite that utilizes the data held in the National Center for Biotechnology Information's ClinVar archive. The goal is to render the data more accessible to processes pertaining to conflict resolution of variant interpretation as well as tracking details of data submission and data management for detailed variant curation. Here, we establish the use of these tools to address three separate use cases and to perform analyses across submissions. We demonstrate that the ClinVar Miner tools are an effective means to browse and consolidate data for variant submitters, curation groups, and general oversight. These tools are also relevant to the variant interpretation community in general.

Inherited Cancer in the Age of Next-Generation Sequencing

Next-generation sequencing (NGS) technology has led to the ability to test for multiple cancer susceptibility genes simultaneously without significantly increasing cost or turnaround time. With growing usage of multigene testing for inherited cancer, ongoing education for nurses and other health-care providers about hereditary cancer screening is imperative to ensure appropriate testing candidate identification, test selection, and posttest management. The purpose of this review article is to (1) provide an overview of how NGS works to detect germline mutations, (2) summarize the benefits and limitations of multigene panel testing, (3) describe risk categories of cancer susceptibility genes, and (4) highlight the counseling considerations for patients pursuing multigene testing.

Observed frequency and challenges of variant reclassification in a hereditary cancer clinic

PurposeEfforts have been made by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology to make variant classification more uniform, but many limitations remain. Reclassification of a variant of uncertain significance (VUS) is expected, but other more certain calls, like pathogenic or benign, can also be reclassified once additional information is gathered. Variant reclassification can create difficult circumstances for both patients and clinicians.MethodsRetrospective review of all variant reclassifications in genes associated with hereditary cancer syndromes at one clinic between September 2013 and February 2017 was completed. All variant reclassifications were completed and reported by the original testing laboratory.ResultsA total of 1,103 hereditary cancer tests were ordered. Fewer than 5% (40/1,103) of the initial reports were updated during that time period. Most reclassifications (29/40) were downgrades of VUS to likely benign. Only three reclassifications could potentially alter medical management.ConclusionThe majority of variant reclassifications do not impact medical management. Upgrading a variant call to pathogenic could be important for a patient's care and shows the importance of open communication between laboratories and clinicians. A variant downgrade from pathogenic can be a significant reclassification as well, especially if prophylactic surgery has been completed.

Genomic medicine and data sharing

Introduction

Effective data sharing does not occur in the UK despite being essential for the delivery of high-quality genomic services to patients across clinical specialities and to optimize advances in genomic medicine.

Sources of data

Original papers, reviews, guidelines, policy papers and web-resources.

Areas of agreement

Data sharing for genomic medicine requires appropriate infrastructure and policies, together with acceptance by health professionals and the public of the necessity of data sharing for clinical care.

Areas of controversy

There is ongoing debate around the different technical approaches and safeguards that could be used to facilitate data sharing while minimizing the risks to individuals of identification. Lack of consensus undermines trust and confidence.

Growing points

Ongoing policy developments around genomics and health data create opportunities to ensure systems and policies are in place to support proportionate, effective and safeguarded data sharing.

Areas timely for developing research

Mechanisms to improve public trust.

ClinVar Is a Critical Resource to Advance Variant Interpretation

In this Letter to the Editor, potentially flawed conclusions of a recent study are discussed.