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Moreno-Cabrera JM, Feliubadaló L, Pineda M, Prada-Dacasa P, Ramos-Muntada M, Del Valle J, Brunet J, Gel B, Currás-Freixes M, Calsina B, Salazar-Hidalgo ME, Rodríguez-Balada M, Roig B, Fernández-Castillejo S, Durán Domínguez M, Arranz Ledo M, Infante Sanz M, Castillejo A, Dámaso E, Soto JL, de Miguel M, Hidalgo Calero B, Sánchez-Zapardiel JM, Ramon Y Cajal T, Lasa A, Gisbert-Beamud A, López-Novo A, Ruiz-Ponte C, Potrony M, Álvarez-Mora MI, Osorio A, Lorda-Sánchez I, Robledo M, Cascón A, Ruiz A, Spataro N, Hernan I, Borràs E, Moles-Fernández A, Earl J, Cadiñanos J, Sánchez-Heras AB, Bigas A, Capellá G, Lázaro C. SpadaHC: a database to improve the classification of variants in hereditary cancer genes in the Spanish population. Database (Oxford) 2024; 2024:baae055. [PMID: 38965703 PMCID: PMC11223915 DOI: 10.1093/database/baae055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 04/30/2024] [Accepted: 06/25/2024] [Indexed: 07/06/2024]
Abstract
Accurate classification of genetic variants is crucial for clinical decision-making in hereditary cancer. In Spain, genetic diagnostic laboratories have traditionally approached this task independently due to the lack of a dedicated resource. Here we present SpadaHC, a web-based database for sharing variants in hereditary cancer genes in the Spanish population. SpadaHC is implemented using a three-tier architecture consisting of a relational database, a web tool and a bioinformatics pipeline. Contributing laboratories can share variant classifications and variants from individuals in Variant Calling Format (VCF) format. The platform supports open and restricted access, flexible dataset submissions, automatic pseudo-anonymization, VCF quality control, variant normalization and liftover between genome builds. Users can flexibly explore and search data, receive automatic discrepancy notifications and access SpadaHC population frequencies based on many criteria. In February 2024, SpadaHC included 18 laboratory members, storing 1.17 million variants from 4306 patients and 16 343 laboratory classifications. In the first analysis of the shared data, we identified 84 genetic variants with clinically relevant discrepancies in their classifications and addressed them through a three-phase resolution strategy. This work highlights the importance of data sharing to promote consistency in variant classifications among laboratories, so patients and family members can benefit from more accurate clinical management. Database URL: https://spadahc.ciberisciii.es/.
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Affiliation(s)
- José M Moreno-Cabrera
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
- Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L’Hospitalet del Llobregat, Barcelona 08908, Spain
| | - Lidia Feliubadaló
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Marta Pineda
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Patricia Prada-Dacasa
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Mireia Ramos-Muntada
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Jesús Del Valle
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Joan Brunet
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Bernat Gel
- Hereditary Cancer Group, Program for Predictive and Personalized Medicine of Cancer, Germans Trias i Pujol Research Institute (PMPPC-IGTP), Campus Can Ruti, Ctra de Can Ruti, Camí de les Escoles, s/n, Badalona 08916, Spain
| | - María Currás-Freixes
- Familial Cancer Clinical Unit, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Bruna Calsina
- Familial Cancer Clinical Unit, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Milton E Salazar-Hidalgo
- Familial Cancer Clinical Unit, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Marta Rodríguez-Balada
- Institut d’Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), Dr. Josep Laporte, 2, Reus 43204, Spain
| | - Bàrbara Roig
- Institut d’Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), Dr. Josep Laporte, 2, Reus 43204, Spain
| | - Sara Fernández-Castillejo
- Institut d’Oncologia de la Catalunya Sud (IOCS), Hospital Universitari Sant Joan de Reus (HUSJR), Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), Dr. Josep Laporte, 2, Reus 43204, Spain
| | - Mercedes Durán Domínguez
- Cancer Genetics Group, Unit of Excellence Institute of Biomedicine and Molecular Genetics, University of Valladolid-Spanish National Research Council (IBGM, UVa- CSIC), Sanz y Fores, 3, Valladolid 47003, Spain
| | - Mónica Arranz Ledo
- Cancer Genetics Group, Unit of Excellence Institute of Biomedicine and Molecular Genetics, University of Valladolid-Spanish National Research Council (IBGM, UVa- CSIC), Sanz y Fores, 3, Valladolid 47003, Spain
| | - Mar Infante Sanz
- Cancer Genetics Group, Unit of Excellence Institute of Biomedicine and Molecular Genetics, University of Valladolid-Spanish National Research Council (IBGM, UVa- CSIC), Sanz y Fores, 3, Valladolid 47003, Spain
| | - Adela Castillejo
- Unidad de Genética Molecular, Hospital General Universitario de Elche. Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO), Av. de Catalunya, 21, Elche 03203, Spain
| | - Estela Dámaso
- Unidad de Genética Molecular, Hospital General Universitario de Elche. Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO), Av. de Catalunya, 21, Elche 03203, Spain
| | - José L Soto
- Unidad de Genética Molecular, Hospital General Universitario de Elche. Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO), Av. de Catalunya, 21, Elche 03203, Spain
| | - Montserrat de Miguel
- Laboratorio de cáncer hereditario, Servicio de Bioquímica clínica-Análisis clínicos, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - Beatriz Hidalgo Calero
- Laboratorio de cáncer hereditario, Servicio de Bioquímica clínica-Análisis clínicos, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - José M Sánchez-Zapardiel
- Laboratorio de cáncer hereditario, Servicio de Bioquímica clínica-Análisis clínicos, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - Teresa Ramon Y Cajal
- Familial Cancer Clinic, Medical Oncology, Hospital de la Santa Creu i Sant Pau, Sant Quintí, 89, Barcelona 08041, Spain
| | - Adriana Lasa
- Genetics Department, Hospital de la Santa Creu i Sant Pau, Sant Quintí, 89, Barcelona 08041, Spain
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
| | | | - Anael López-Novo
- Fundación Pública Galega de Medicina Xenómica (SERGAS), Instituto de Investigación Sanitaria de Santiago, Grupo de Medicina Xenómica-USC, Av. Barcelona, s/n, Santiago de Compostela 15706, Spain
| | - Clara Ruiz-Ponte
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Fundación Pública Galega de Medicina Xenómica (SERGAS), Instituto de Investigación Sanitaria de Santiago, Grupo de Medicina Xenómica-USC, Av. Barcelona, s/n, Santiago de Compostela 15706, Spain
| | - Miriam Potrony
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Biochemistry and Molecular Genetics Department, Hospital Clinic of Barcelona and Fundació de Recerca Clínic Barcelona-Institut d’Investigacions Biomèdiques August Pi i Sunyer (FRCB-IDIBAPS), University of Barcelona, Rosselló, 149, Barcelona 08036, Spain
| | - María I Álvarez-Mora
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Biochemistry and Molecular Genetics Department, Hospital Clinic of Barcelona and Fundació de Recerca Clínic Barcelona-Institut d’Investigacions Biomèdiques August Pi i Sunyer (FRCB-IDIBAPS), University of Barcelona, Rosselló, 149, Barcelona 08036, Spain
| | - Ana Osorio
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Departamento de Genética y Genómica, Hospital Universitario Fundación Jiménez Diaz (IIS-FJD), Av. de los Reyes Católicos, 2, Madrid 28040, Spain
| | - Isabel Lorda-Sánchez
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Departamento de Genética y Genómica, Hospital Universitario Fundación Jiménez Diaz (IIS-FJD), Av. de los Reyes Católicos, 2, Madrid 28040, Spain
| | - Mercedes Robledo
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Center (CNIO), Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Alberto Cascón
- Biomedical Network Research Centre On Rare Diseases (CIBERER), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid 28029, Spain
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Center (CNIO), Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Anna Ruiz
- Genetics Laboratory, Center for Genomic Medicine, Parc Taulí Hospital Universitari, Institut d’Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, Plaça Torre de l’Aigua, s/n, Sabadell 08208, Spain
| | - Nino Spataro
- Genetics Laboratory, Center for Genomic Medicine, Parc Taulí Hospital Universitari, Institut d’Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, Plaça Torre de l’Aigua, s/n, Sabadell 08208, Spain
| | - Imma Hernan
- Molecular Genetics Unit, Consorci Sanitari de Terrassa, Ctra. Torrebonica, S/N, Terrassa 08227, Spain
| | - Emma Borràs
- Molecular Genetics Unit, Consorci Sanitari de Terrassa, Ctra. Torrebonica, S/N, Terrassa 08227, Spain
| | - Alejandro Moles-Fernández
- Department of Clinical and Molecular Genetics, Vall d’Hebron Barcelona Hospital Campus, Vall d’Hebron Hospital Universitari, Pg. de la Vall d’Hebron, 119, Barcelona 08035, Spain
- Medicine Genetics Group, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Barcelona Hospital Campus, Vall d’Hebron Hospital Universitari, Pg. de la Vall d’Hebron, 119, Barcelona 08035, Spain
| | - Julie Earl
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
- Biomarkers and Personalized Approach to Cancer Group (BioPAC), Ramón y Cajal Health Research Institute (IRYCIS), Ctra. Colmenar Viejo, Km. 9,100, Madrid 28034, Spain
| | - Juan Cadiñanos
- Fundación Centro Médico de Asturias, José María Richard Grandío, s/n, Oviedo, Asturias 33193, Spain
| | - Ana B Sánchez-Heras
- Cancer Genetic Counseling Unit, Medical Oncology Department, Elche General University Hospital, Almazara, 11, Elche 03203, Spain
| | - Anna Bigas
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
- Program in Cancer Research, Institut Hospital del Mar d’Investigacions Mèdiques, Dr. Aiguader, 88, Barcelona 08003, Spain
- Josep Carreras Leukemia Research Institute, Ctra de Can Ruti, Camí de les Escoles, s/n, Barcelona 08916, Spain
| | - Gabriel Capellá
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
| | - Conxi Lázaro
- Hereditary Cancer Program, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL-ONCOBELL, L’Hospitalet de Llobregat, Barcelona 08908, Spain
- Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Monforte de Lemos, 3-5, Madrid, 28029, Spain
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2
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McRonald FE, Pethick J, Santaniello F, Shand B, Tyson A, Tulloch O, Goel S, Lüchtenborg M, Borthwick GM, Turnbull C, Shaw AC, Monahan KJ, Frayling IM, Hardy S, Burn J. Identification of people with Lynch syndrome from those presenting with colorectal cancer in England: baseline analysis of the diagnostic pathway. Eur J Hum Genet 2024; 32:529-538. [PMID: 38355963 PMCID: PMC11061113 DOI: 10.1038/s41431-024-01550-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 01/08/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024] Open
Abstract
It is believed that >95% of people with Lynch syndrome (LS) remain undiagnosed. Within the National Health Service (NHS) in England, formal guidelines issued in 2017 state that all colorectal cancers (CRC) should be tested for DNA Mismatch Repair deficiency (dMMR). We used a comprehensive population-level national dataset to analyse implementation of the agreed diagnostic pathway at a baseline point 2 years post-publication of official guidelines. Using real-world data collected and curated by the National Cancer Registration and Analysis Service (NCRAS), we retrospectively followed up all people diagnosed with CRC in England in 2019. Nationwide laboratory diagnostic data incorporated somatic (tumour) testing for dMMR (via immunohistochemistry or microsatellite instability), somatic testing for MLH1 promoter methylation and BRAF status, and constitutional (germline) testing of MMR genes. Only 44% of CRCs were screened for dMMR; these figures varied over four-fold with respect to geography. Of those CRCs identified as dMMR, only 51% underwent subsequent diagnostic testing. Overall, only 1.3% of patients with colorectal cancer had a germline MMR genetic test performed; up to 37% of these tests occurred outside of NICE guidelines. The low rates of molecular diagnostic testing in CRC support the premise that Lynch syndrome is underdiagnosed, with significant attrition at all stages of the testing pathway. Applying our methodology to subsequent years' data will allow ongoing monitoring and analysis of the impact of recent investment. If the diagnostic guidelines were fully implemented, we estimate that up to 700 additional people with LS could be identified each year.
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Affiliation(s)
| | - Joanna Pethick
- National Disease Registration Service, NHS England, London, UK
| | - Francesco Santaniello
- National Disease Registration Service, NHS England, London, UK
- Health Data Insight, Cambridge, UK
| | - Brian Shand
- National Disease Registration Service, NHS England, London, UK
- Health Data Insight, Cambridge, UK
| | - Adele Tyson
- National Disease Registration Service, NHS England, London, UK
- Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Oliver Tulloch
- National Disease Registration Service, NHS England, London, UK
- Health Data Insight, Cambridge, UK
| | - Shilpi Goel
- National Disease Registration Service, NHS England, London, UK
- Health Data Insight, Cambridge, UK
| | - Margreet Lüchtenborg
- National Disease Registration Service, NHS England, London, UK
- Cancer Epidemiology and Cancer Services Research, King's College London, London, UK
| | - Gillian M Borthwick
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Adam C Shaw
- Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Kevin J Monahan
- St Mark's Hospital Centre for Familial Intestinal Cancer, Imperial College, London, UK
| | - Ian M Frayling
- St Mark's Hospital Centre for Familial Intestinal Cancer, Imperial College, London, UK
- St Vincent's University Hospital, Dublin, Ireland
| | - Steven Hardy
- National Disease Registration Service, NHS England, London, UK
| | - John Burn
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.
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3
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McDevitt T, Durkie M, Arnold N, Burghel GJ, Butler S, Claes KBM, Logan P, Robinson R, Sheils K, Wolstenholme N, Hanson H, Turnbull C, Hume S. EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer. Eur J Hum Genet 2024; 32:479-488. [PMID: 38443545 PMCID: PMC11061103 DOI: 10.1038/s41431-023-01507-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/07/2023] [Accepted: 11/21/2023] [Indexed: 03/07/2024] Open
Abstract
Hereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where 'must' is assigned to advocate that the recommendation is essential; and 'should' is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.
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Affiliation(s)
- Trudi McDevitt
- Department of Clinical Genetics, Children's Health Ireland at Crumlin, Dublin, Ireland.
| | - Miranda Durkie
- Sheffield Diagnostic Genetics Service, North East and Yorkshire Genomic Laboratory Hub, Sheffield Children's NHS Foundation Trust Western Bank, Sheffield, UK
| | - Norbert Arnold
- UKSH Campus Kiel, Gynecology and Obstetrics, Institut of Clinical Chemistry, Institut of Clinical Molecular Biology, Kiel, Germany
| | - George J Burghel
- Manchester University NHS Foundation Trust, North West Genomic Laboratory Hub, Manchester, UK
| | - Samantha Butler
- Central and South Genomic Laboratory Hub, West Midlands Regional Genetics Laboratory, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | | | - Peter Logan
- HSCNI / Belfast Trust Laboratories, Regional Molecular Diagnostics Service, Belfast, Northern Ireland
| | - Rachel Robinson
- Leeds Teaching Hospitals NHS Trust, Genetics Department, Leeds, UK
| | | | | | - Helen Hanson
- St George's University Hospitals NHS Foundation Trust, Clinical Genetics, London, UK
| | | | - Stacey Hume
- University of British Columbia, Pathology and Laboratory Medicine, Vancouver, British Columbia, Canada
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4
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Fortuno C, Michailidou K, Parsons M, Dolinsky JS, Pesaran T, Yussuf A, Mester JL, Hruska KS, Hiraki S, O’Connor R, Chan RC, Kim S, Tavtigian SV, Goldgar D, James PA, Spurdle AB. Challenges and approaches to calibrating patient phenotype as evidence for cancer gene variant classification under ACMG/AMP guidelines. Hum Mol Genet 2024; 33:724-732. [PMID: 38271184 PMCID: PMC11000651 DOI: 10.1093/hmg/ddae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 01/27/2024] Open
Abstract
Since first publication of the American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) variant classification guidelines, additional recommendations for application of certain criteria have been released (https://clinicalgenome.org/docs/), to improve their application in the diagnostic setting. However, none have addressed use of the PS4 and PP4 criteria, capturing patient presentation as evidence towards pathogenicity. Application of PS4 can be done through traditional case-control studies, or "proband counting" within or across clinical testing cohorts. Review of the existing PS4 and PP4 specifications for Hereditary Cancer Gene Variant Curation Expert Panels revealed substantial differences in the approach to defining specifications. Using BRCA1, BRCA2 and TP53 as exemplar genes, we calibrated different methods proposed for applying the "PS4 proband counting" criterion. For each approach, we considered limitations, non-independence with other ACMG/AMP criteria, broader applicability, and variability in results for different datasets. Our findings highlight inherent overlap of proband-counting methods with ACMG/AMP frequency codes, and the importance of calibration to derive dataset-specific code weights that can account for potential between-dataset differences in ascertainment and other factors. Our work emphasizes the advantages and generalizability of logistic regression analysis over simple proband-counting approaches to empirically determine the relative predictive capacity and weight of various personal clinical features in the context of multigene panel testing, for improved variant interpretation. We also provide a general protocol, including instructions for data formatting and a web-server for analysis of personal history parameters, to facilitate dataset-specific calibration analyses required to use such data for germline variant classification.
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Affiliation(s)
- Cristina Fortuno
- Population Health Program, QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
| | - Michael Parsons
- Population Health Program, QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia
| | | | - Tina Pesaran
- Ambry Genetics, Aliso Viejo, CA 92656, United States
| | - Amal Yussuf
- Ambry Genetics, Aliso Viejo, CA 92656, United States
| | | | | | | | | | - Raymond C Chan
- Color Genomics, Inc., Burlingame, CA 94010, United States
| | - Serra Kim
- Color Genomics, Inc., Burlingame, CA 94010, United States
| | - Sean V Tavtigian
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, United States
| | - David Goldgar
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, United States
| | - Paul A James
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, VIC 3052, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Amanda B Spurdle
- Population Health Program, QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia
- Faculty of Medicine, The University of Queensland, Herston, QLD 4006, Australia
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5
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Allen S, Loong L, Garrett A, Torr B, Durkie M, Drummond J, Callaway A, Robinson R, Burghel GJ, Hanson H, Field J, McDevitt T, McVeigh TP, Bedenham T, Bowles C, Bradshaw K, Brooks C, Butler S, Del Rey Jimenez JC, Hawkes L, Stinton V, MacMahon S, Owens M, Palmer-Smith S, Smith K, Tellez J, Valganon-Petrizan M, Waskiewicz E, Yau M, Eccles DM, Tischkowitz M, Goel S, McRonald F, Antoniou AC, Morris E, Hardy S, Turnbull C. Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey. J Med Genet 2024; 61:305-312. [PMID: 38154813 PMCID: PMC10982625 DOI: 10.1136/jmg-2023-109645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 10/28/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. METHODS In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). RESULTS Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. CONCLUSION The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation.
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Affiliation(s)
- Sophie Allen
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Lucy Loong
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Alice Garrett
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
- Department of Clinical Genetics, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Bethany Torr
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Miranda Durkie
- Sheffield Diagnostic Genetics Service, NEY Genomic Laboratory Hub, Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | - James Drummond
- East Anglian Medical Genetics Service, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Alison Callaway
- Wessex Regional Genetics Laboratory, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Rachel Robinson
- Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - George J Burghel
- Manchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Helen Hanson
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
- Department of Clinical Genetics, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Joanne Field
- Genomics and Molecular Medicine Service, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Trudi McDevitt
- Department of Clinical Genetics, CHI at Crumlin, Dublin, Ireland
| | - Terri P McVeigh
- Cancer Genetics Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Tina Bedenham
- West Midlands, Oxford and Wessex Genomic Laboratory Hub, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Christopher Bowles
- Department of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Kirsty Bradshaw
- East Midlands and East of England Genomics Laboratory, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Claire Brooks
- North Thames Genomic Laboratory Hub, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Samantha Butler
- Central and South Genomic Laboratory Hub, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | | | - Lorraine Hawkes
- South East Genomics Laboratory Hub, Guy's Hospital, London, UK
| | - Victoria Stinton
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester, UK
| | - Suzanne MacMahon
- Centre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK
- Department of Molecular Diagnostics, The Royal Marsden NHS Foundation Trust, London, UK
| | - Martina Owens
- Department of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Sheila Palmer-Smith
- Institute of Medical Genetics, Cardiff and Vale University Health Board, University Hospital of Wales, Cardiff, UK
| | - Kenneth Smith
- South West Genomic Laboratory Hub, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - James Tellez
- North East and Yorkshire Genomic Laboratory Hub, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Mikel Valganon-Petrizan
- Centre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK
- Department of Molecular Diagnostics, The Royal Marsden NHS Foundation Trust, London, UK
| | - Erik Waskiewicz
- Institute of Medical Genetics, Cardiff and Vale University Health Board, University Hospital of Wales, Cardiff, UK
| | - Michael Yau
- South East Genomics Laboratory Hub, Guy's Hospital, London, UK
| | - Diana M Eccles
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK
| | - Marc Tischkowitz
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Shilpi Goel
- NHS England, National Disease Registration Service, London, UK
- Health Data Insight CIC, Cambridge, UK
| | - Fiona McRonald
- NHS England, National Disease Registration Service, London, UK
| | - Antonis C Antoniou
- Department of Public Health and Primary Care, University of Cambridge Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Eva Morris
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Steven Hardy
- NHS England, National Disease Registration Service, London, UK
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
- Cancer Genetics Unit, The Royal Marsden NHS Foundation Trust, London, UK
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6
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Sahan K, Lyle K, Carley H, Hallowell N, Parker MJ, Lucassen AM. Ethical preparedness in genomic medicine: how NHS clinical scientists navigate ethical issues. JOURNAL OF MEDICAL ETHICS 2024:jme-2023-109692. [PMID: 38320848 DOI: 10.1136/jme-2023-109692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/15/2024] [Indexed: 02/12/2024]
Abstract
Much has been published about the ethical issues encountered by clinicians in genetics/genomics, but those experienced by clinical laboratory scientists are less well described. Clinical laboratory scientists now frequently face navigating ethical problems in their work, but how they should be best supported to do this is underexplored. This lack of attention is also reflected in the ethics tools available to clinical laboratory scientists such as guidance and deliberative ethics forums, developed primarily to manage issues arising within the clinic.We explore what ethical issues are being experienced by clinical scientists, how they think such issues could be best analysed and managed, and whether their practice might be enhanced by more situated approaches to ethics deliberation and practice such as ethical preparedness. From thematic analysis of cases presented by clinical scientists at a specially convened meeting of the UK Genethics Forum, we derived three main ethical themes: (1) the redistribution of labour and responsibilities resulting from the practice of genomic medicine; (2) the interpretation and certainty of results and (3) the proposal that better standardisation and consistency of ethical approaches (for example, more guidelines and policy) could resolve some of the challenges arising.We argue that although standardisation is important for promoting shared understandings of good (including ethical) practice, supplementary approaches to enhance and sustain ethical preparedness will be important to help clinical scientists and others in the recently expanded genetic/genomic medicine environment foster quality ethical thinking.
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Affiliation(s)
- Kate Sahan
- Ethox Centre, University of Oxford Nuffield Department of Population Health, Oxford, UK
| | - Kate Lyle
- Wellcome Trust Centre for Human Genetics, Oxford, UK
- Clinical Ethics, Law, and Society (CELS) Oxford, Nuffield Dept of Medicine, University of Oxford, Oxford, UK
| | - Helena Carley
- Clinical Ethics, Law, and Society (CELS) Oxford, Nuffield Dept of Medicine, University of Oxford, Oxford, UK
- South East Thames Regional Genetics Service, Guy's & St Thomas NHS Foundation Trust, London, UK
| | - Nina Hallowell
- Ethox Centre, University of Oxford Nuffield Department of Population Health, Oxford, UK
| | - Michael J Parker
- Ethox Centre, University of Oxford Nuffield Department of Population Health, Oxford, UK
| | - Anneke M Lucassen
- Wellcome Trust Centre for Human Genetics, Oxford, UK
- Clinical Ethics, Law, and Society (CELS) Oxford, Nuffield Dept of Medicine, University of Oxford, Oxford, UK
- Centre for Personalised Medicine, University of Oxford, Oxford, UK
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7
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Morgan RD, Burghel GJ, Schlecht H, Clamp AR, Hasan J, Mitchell CL, Salih Z, Shaw J, Desai S, Jayson GC, Woodward ER, Evans DGR. Real-World Concordance between Germline and Tumour BRCA1/2 Status in Epithelial Ovarian Cancer. Cancers (Basel) 2023; 16:177. [PMID: 38201604 PMCID: PMC10778166 DOI: 10.3390/cancers16010177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 12/22/2023] [Accepted: 12/26/2023] [Indexed: 01/12/2024] Open
Abstract
Patients diagnosed with epithelial ovarian cancer may undergo reflex tumour BRCA1/2 testing followed by germline BRCA1/2 testing in patients with a positive tumour test result. This testing model relies on tumour BRCA1/2 tests being able to detect all types of pathogenic variant. We analysed germline and tumour BRCA1/2 test results from patients treated for epithelial ovarian cancer at our specialist oncological referral centre. Tumour BRCA1/2 testing was performed using the next-generation sequencing (NGS)-based myChoice® companion diagnostic (CDx; Myriad Genetics, Inc.). Germline BRCA1/2 testing was performed in the North West Genomic Laboratory Hub using NGS and multiplex ligation-dependent probe amplification. Between 11 April 2021 and 11 October 2023, 382 patients were successfully tested for tumour BRCA1 and BRCA2 variants. Of these, 367 (96.1%) patients were tested for germline BRCA1/2 variants. In those patients who underwent tumour and germline testing, 15.3% (56/367) had a BRCA1/2 pathogenic variant (36 germline and 20 somatic). All germline BRCA1/2 pathogenic small sequencing variants were detected in tumour DNA. By contrast, 3 out of 8 germline BRCA1/2 pathogenic large rearrangements were not reported in tumour DNA. The overall concordance of germline BRCA1/2 pathogenic variants detected in germline and tumour DNA was clinically acceptable at 91.7% (33/36). The myChoice® CDx was able to detect most germline BRCA1/2 pathogenic variants in tumour DNA, although a proportion of pathogenic large rearrangements were not reported. If Myriad's myChoice® CDx is used for tumour BRCA1/2 testing, our data supports a testing strategy of germline and tumour BRCA1/2 testing in all patients diagnosed with epithelial ovarian cancer aged < 79 years old, with germline BRCA1/2 testing only necessary for patients aged ≥ 80 years old with a tumour BRCA1/2 pathogenic variant.
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Affiliation(s)
- Robert D. Morgan
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, School of Medical Sciences, University of Manchester, Manchester M13 9PL, UK
| | - George J. Burghel
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
- Division of Evolution, Infection and Genomics, Faculty of Biology, Medicine and Health, School of Biological Sciences, University of Manchester, Manchester M13 9PL, UK
| | - Helene Schlecht
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
| | - Andrew R. Clamp
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, School of Medical Sciences, University of Manchester, Manchester M13 9PL, UK
| | - Jurjees Hasan
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - Claire L. Mitchell
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - Zena Salih
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - Joseph Shaw
- Department of Gynaecological Pathology, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
| | - Sudha Desai
- Department of Pathology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - Gordon C. Jayson
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, School of Medical Sciences, University of Manchester, Manchester M13 9PL, UK
| | - Emma R. Woodward
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
- Division of Evolution, Infection and Genomics, Faculty of Biology, Medicine and Health, School of Biological Sciences, University of Manchester, Manchester M13 9PL, UK
- Department of Clinical Genetics, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
| | - D. Gareth R. Evans
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
- Division of Evolution, Infection and Genomics, Faculty of Biology, Medicine and Health, School of Biological Sciences, University of Manchester, Manchester M13 9PL, UK
- Department of Clinical Genetics, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
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8
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Hansen EB, Karlsson Q, Merson S, Wakerell S, Rageevakumar R, Jensen JB, Borre M, Kote-Jarai Z, Eeles RA, Sørensen KD. Impact of germline DNA repair gene variants on prognosis and treatment of men with advanced prostate cancer. Sci Rep 2023; 13:19135. [PMID: 37932350 PMCID: PMC10628129 DOI: 10.1038/s41598-023-46323-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 10/30/2023] [Indexed: 11/08/2023] Open
Abstract
The clinical importance of germline variants in DNA repair genes (DRGs) is becoming increasingly recognized, but their impact on advanced prostate cancer prognosis remains unclear. A cohort of 221 newly diagnosed metastatic castration-resistant prostate cancer (mCRPC) patients were screened for pathogenic germline variants in 114 DRGs. The primary endpoint was progression-free survival (PFS) on first-line androgen signaling inhibitor (ARSI) treatment for mCRPC. Secondary endpoints were time to mCRPC progression on initial androgen deprivation therapy (ADT) and overall survival (OS). Twenty-seven patients (12.2%) carried a germline DRG variant. DRG carrier status was independently associated with shorter PFS on first-line ARSI [HR 1.72 (1.06-2.81), P = 0.029]. At initiation of ADT, DRG carrier status was independently associated with shorter progression time to mCRPC [HR 1.56, (1.02-2.39), P = 0.04] and shorter OS [HR 1.99, (1.12-3.52), P = 0.02]. Investigating the contributions of individual germline DRG variants on PFS and OS revealed CHEK2 variants to have little effect. Furthermore, prior taxane treatment was associated with worse PFS on first-line ARSI for DRG carriers excluding CHEK2 (P = 0.0001), but not for noncarriers. In conclusion, germline DRG carrier status holds independent prognostic value for predicting advanced prostate cancer patient outcomes and may potentially inform on optimal treatment sequencing already at the hormone-sensitive stage.
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Affiliation(s)
- Emma B Hansen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Questa Karlsson
- Division of Genetics & Epidemiology, The Institute of Cancer Research, London, UK
| | - Susan Merson
- Division of Genetics & Epidemiology, The Institute of Cancer Research, London, UK
| | - Sarah Wakerell
- Division of Genetics & Epidemiology, The Institute of Cancer Research, London, UK
| | - Reshma Rageevakumar
- Division of Genetics & Epidemiology, The Institute of Cancer Research, London, UK
| | - Jørgen B Jensen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Urology, Regional Hospital of West Jutland, Gødstrup Hospital, Gødstrup, Denmark
| | - Michael Borre
- Department of Urology, Aarhus University Hospital, Aarhus, Denmark
| | - Zsofia Kote-Jarai
- Division of Genetics & Epidemiology, The Institute of Cancer Research, London, UK
| | - Rosalind A Eeles
- Division of Genetics & Epidemiology, The Institute of Cancer Research, London, UK
- Royal Marsden NHS Foundation Trust, London, UK
| | - Karina D Sørensen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
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9
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Flowers M, Dickson A, Miller MJ, Spector E, Enns GM, Baudet H, Pasquali M, Racacho L, Sadre-Bazzaz K, Wen T, Fogarty M, Fernandez R, Weaver MA, Feigenbaum A, Graham BH, Mao R. Specifications of the ACMG/AMP guidelines for ACADVL variant interpretation. Mol Genet Metab 2023; 140:107668. [PMID: 37549443 PMCID: PMC10811274 DOI: 10.1016/j.ymgme.2023.107668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023]
Abstract
Very long-chain acyl-CoA dehydrogenase (VLCAD) deficiency (VLCADD) is a relatively common inborn error of metabolism, but due to difficulty in accurately predicting affected status through newborn screening, molecular confirmation of the causative variants by sequencing of the ACADVL gene is necessary. Although the ACMG/AMP guidelines have helped standardize variant classification, ACADVL variant classification remains disparate due to a phenotype that can be nonspecific, the possibility of variants that produce late-onset disease, and relatively high carrier frequency, amongst other challenges. Therefore, an ACADVL-specific variant curation expert panel (VCEP) was created to facilitate the specification of the ACMG/AMP guidelines for VLCADD. We expect these guidelines to help streamline, increase concordance, and expedite the classification of ACADVL variants.
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Affiliation(s)
- May Flowers
- Invitae Corporation, San Francisco, CA 94103, USA
| | - Alexa Dickson
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Marcus J Miller
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Elaine Spector
- Department of Pathology, University of Colorado School of Medicine, Aurora, CO 80045, USA; Section of Clinical Genetics and Metabolism, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Gregory Mark Enns
- Division of Medical Genetics, Department of Pediatrics, Lucile Packard Children's Hospital, Stanford University, Stanford, CA 94304, USA
| | - Heather Baudet
- Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Marzia Pasquali
- Department of Pathology, University of Utah, Salt Lake City, UT 84112, USA; ARUP Laboratories, Salt Lake City, UT 84108, USA
| | - Lemuel Racacho
- Department of Medical Genetics, Alberta Children's Hospital, Calgary, Alberta T3B6A8, Canada
| | | | - Ting Wen
- ARUP Laboratories, Salt Lake City, UT 84108, USA
| | | | - Raquel Fernandez
- American College of Medical Genetics and Genomics, Bethesda, MD 20814, USA
| | - Meredith A Weaver
- American College of Medical Genetics and Genomics, Bethesda, MD 20814, USA
| | - Annette Feigenbaum
- Department of Pediatrics, Division of Genetics, Rady Children's Hospital and The University of California, San Diego, CA 92123, USA
| | - Brett H Graham
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Rong Mao
- Department of Pathology, University of Utah, Salt Lake City, UT 84112, USA; ARUP Laboratories, Salt Lake City, UT 84108, USA.
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10
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Guarischi-Sousa R, Kroll JE, Bonaldi A, Pierry PM, Villela D, Souza CA, Silva JS, Bürger MC, Oliveira FA, de Paula MG, Meliso FM, de Almeida LG, Monfredini PM, de Oliveira AG, Milanezi F, Scapulatempo-Neto C, Yamamoto GL. A Benchmark of In-House Homologous Recombination Repair Deficiency Testing Solutions for High-Grade Serous Ovarian Cancer Diagnosis. Diagnostics (Basel) 2023; 13:3293. [PMID: 37958189 PMCID: PMC10648202 DOI: 10.3390/diagnostics13213293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/24/2023] [Accepted: 08/28/2023] [Indexed: 11/15/2023] Open
Abstract
Homologous recombination deficiency (HRD) has become an important prognostic and predictive biomarker for patients with high-grade serous ovarian cancer who may benefit from poly-ADP ribose polymerase inhibitors (PARPi) and platinum-based therapies. HRD testing provides relevant information to personalize patients' treatment options and has been progressively incorporated into diagnostic laboratories. Here, we assessed the performance of an in-house HRD testing system deployable in a diagnostic clinical setting, comparing results from two commercially available next-generation sequencing (NGS)-based tumor tests (SOPHiA DDMTM HRD Solution and AmoyDx® (HRD Focus Panel)) with the reference assay from Myriad MyChoice® (CDx). A total of 85 ovarian cancer samples were subject to HRD testing. An overall strong correlation was observed across the three assays evaluated, regardless of the different underlying methods employed to assess genomic instability, with the highest pairwise correlation between Myriad and SOPHiA (R = 0.87, p-value = 3.39 × 10-19). The comparison of the assigned HRD status to the reference Myriad's test revealed a positive predictive value (PPV) and negative predictive value (NPV) of 90.9% and 96.3% for SOPHiA's test, while AmoyDx's test achieved 75% PPV and 100% NPV. This is the largest HRD testing evaluation using different methodologies and provides a clear picture of the robustness of NGS-based tests currently offered in the market. Our data shows that the implementation of in-house HRD testing in diagnostic laboratories is technically feasible and can be reliably performed with commercial assays. Also, the turnaround time is compatible with clinical needs, making it an ideal alternative to offer to a broader number of patients while maintaining high-quality standards at more accessible price tiers.
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11
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Walker LC, Hoya MDL, Wiggins GAR, Lindy A, Vincent LM, Parsons MT, Canson DM, Bis-Brewer D, Cass A, Tchourbanov A, Zimmermann H, Byrne AB, Pesaran T, Karam R, Harrison SM, Spurdle AB. Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup. Am J Hum Genet 2023; 110:1046-1067. [PMID: 37352859 PMCID: PMC10357475 DOI: 10.1016/j.ajhg.2023.06.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 06/25/2023] Open
Abstract
The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.
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Affiliation(s)
- Logan C Walker
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Miguel de la Hoya
- Molecular Oncology Laboratory, CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Madrid, Spain
| | - George A R Wiggins
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | | | | | - Michael T Parsons
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Daffodil M Canson
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | | | | | | | - Alicia B Byrne
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Steven M Harrison
- Ambry Genetics, Aliso Viejo, CA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Amanda B Spurdle
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
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12
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Walker LC, de la Hoya M, Wiggins GA, Lindy A, Vincent LM, Parsons M, Canson DM, Bis-Brewer D, Cass A, Tchourbanov A, Zimmermann H, Byrne AB, Pesaran T, Karam R, Harrison SM, Spurdle AB. APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.24.23286431. [PMID: 36865205 PMCID: PMC9980257 DOI: 10.1101/2023.02.24.23286431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.
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13
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Hanson H, Durkie M, Lalloo F, Izatt L, McVeigh TP, Cook JA, Brewer C, Drummond J, Butler S, Cranston T, Casey R, Tan T, Morganstein D, Eccles DM, Tischkowitz M, Turnbull C, Woodward ER, Maher ER. UK recommendations for SDHA germline genetic testing and surveillance in clinical practice. J Med Genet 2023; 60:107-111. [PMID: 35260474 PMCID: PMC9887350 DOI: 10.1136/jmedgenet-2021-108355] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 02/13/2022] [Indexed: 02/03/2023]
Abstract
SDHA pathogenic germline variants (PGVs) are identified in up to 10% of patients with paraganglioma and phaeochromocytoma and up to 30% with wild-type gastrointestinal stromal tumours. Most SDHA PGV carriers present with an apparently sporadic tumour, but often the pathogenic variant has been inherited from parent who has the variant, but has not developed any clinical features. Studies of SDHA PGV carriers suggest that lifetime penetrance for SDHA-associated tumours is low, particularly when identified outside the context of a family history. Current recommended surveillance for SDHA PGV carriers follows an intensive protocol. With increasing implementation of tumour and germline large panel and whole-genome sequencing, it is likely more SDHA PGV carriers will be identified in patients with tumours not strongly associated with SDHA, or outside the context of a strong family history. This creates a complex situation about what to recommend in clinical practice considering low penetrance for tumour development, surveillance burden and patient anxiety. An expert SDHA working group was formed to discuss and consider this situation. This paper outlines the recommendations from this working group for testing and management of SDHA PGV carriers in clinical practice.
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Affiliation(s)
- Helen Hanson
- South West Thames Regional Genetic Services, St George's University Hospitals NHS Foundation Trust, London, UK
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Miranda Durkie
- Sheffield Diagnostic Genetics Service, Sheffield Children's NHS Foundation Trust, North East and Yorkshire Genomic Laboratory Hub, Sheffield, UK
| | - Fiona Lalloo
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Louise Izatt
- Clinical Genetics, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Terri P McVeigh
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
| | - Jackie A Cook
- Department of Clinical Genetics, Sheffield Children's NHS FoundationTrust, Sheffield, UK
| | - Carole Brewer
- Department of Clinical Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - James Drummond
- East NHS Genomic Laboratory Hub, Cambridge University Hospitals Genomic Laboratory, Cambridge University Hospital Foundation Trust, Cambridge, UK
| | - Samantha Butler
- Molecular Genetics, West Midlands Regional Genetics Laboratory, Birmingham, West Midlands, UK
| | - Treena Cranston
- Oxford Molecular Genetics Laboratory, Churchill Hospital, Oxford, UK
| | - Ruth Casey
- Department of Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Medical Genetics, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Tricia Tan
- Section of Investigative Medicine, Imperial College London, London, UK
| | | | - Diana M Eccles
- Cancer Sciences Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Marc Tischkowitz
- Department of Medical Genetics, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Emma Roisin Woodward
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK
| | - Eamonn R Maher
- Department of Medical Genetics, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Functional Analyses of Rare Germline Missense BRCA1 Variants Located within and outside Protein Domains with Known Functions. Genes (Basel) 2023; 14:genes14020262. [PMID: 36833189 PMCID: PMC9957003 DOI: 10.3390/genes14020262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 01/20/2023] Open
Abstract
The BRCA1 protein is implicated in numerous important cellular processes to prevent genomic instability and tumorigenesis, and pathogenic germline variants predispose carriers to hereditary breast and ovarian cancer (HBOC). Most functional studies of missense variants in BRCA1 focus on variants located within the Really Interesting New Gene (RING), coiled-coil and BRCA1 C-terminal (BRCT) domains, and several missense variants in these regions have been shown to be pathogenic. However, the majority of these studies focus on domain specific assays, and have been performed using isolated protein domains and not the full-length BRCA1 protein. Furthermore, it has been suggested that BRCA1 missense variants located outside domains with known function are of no functional importance, and could be classified as (likely) benign. However, very little is known about the role of the regions outside the well-established domains of BRCA1, and only a few functional studies of missense variants located within these regions have been published. In this study, we have, therefore, functionally evaluated the effect of 14 rare BRCA1 missense variants considered to be of uncertain clinical significance, of which 13 are located outside the well-established domains and one within the RING domain. In order to investigate the hypothesis stating that most BRCA1 variants located outside the known protein domains are benign and of no functional importance, multiple protein assays including protein expression and stability, subcellular localisation and protein interactions have been performed, utilising the full-length protein to better mimic the native state of the protein. Two variants located outside the known domains (p.Met297Val and p.Asp1152Asn) and one variant within the RING domain (p.Leu52Phe) were found to make the BRCA1 protein more prone to proteasome-mediated degradation. In addition, two variants (p.Leu1439Phe and p.Gly890Arg) also located outside known domains were found to have reduced protein stability compared to the wild type protein. These findings indicate that variants located outside the RING, BRCT and coiled-coiled domains could also affect the BRCA1 protein function. For the nine remaining variants, no significant effects on BRCA1 protein functions were observed. Based on this, a reclassification of seven variants from VUS to likely benign could be suggested.
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15
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Dace P, Findlay GM. Reducing uncertainty in genetic testing with Saturation Genome Editing. MED GENET-BERLIN 2022; 34:297-304. [PMID: 38836089 PMCID: PMC11006300 DOI: 10.1515/medgen-2022-2159] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Accurate interpretation of human genetic data is critical for optimizing outcomes in the era of genomic medicine. Powerful methods for testing genetic variants for functional effects are allowing researchers to characterize thousands of variants across disease genes. Here, we review experimental tools enabling highly scalable assays of variants, focusing specifically on Saturation Genome Editing (SGE). We discuss examples of how this technique is being implemented for variant testing at scale and describe how SGE data for BRCA1 have been clinically validated and used to aid variant interpretation. The initial success at predicting variant pathogenicity with SGE has spurred efforts to expand this and related techniques to many more genes.
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Affiliation(s)
- Phoebe Dace
- The Genome Function Laboratory, The Francis Crick Institute, 1 Midland Rd, London, United Kingdom
| | - Gregory M Findlay
- The Genome Function Laboratory, The Francis Crick Institute, 1 Midland Rd, London, United Kingdom
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16
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Loong L, Garrett A, Allen S, Choi S, Durkie M, Callaway A, Drummond J, Burghel GJ, Robinson R, Torr B, Berry IR, Wallace AJ, Eccles DM, Ellard S, Baple E, Evans DG, Woodward ER, Kulkarni A, Lalloo F, Tischkowitz M, Lucassen A, Hanson H, Turnbull C. Reclassification of clinically-detected sequence variants: Framework for genetic clinicians and clinical scientists by CanVIG-UK (Cancer Variant Interpretation Group UK). Genet Med 2022; 24:1867-1877. [PMID: 35657381 DOI: 10.1016/j.gim.2022.05.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 04/29/2022] [Accepted: 05/02/2022] [Indexed: 02/05/2023] Open
Abstract
PURPOSE Variant classifications may change over time, driven by emergence of fresh or contradictory evidence or evolution in weighing or combination of evidence items. For variant classifications above the actionability threshold, which is classification of likely pathogenic or pathogenic, clinical actions may be irreversible, such as risk-reducing surgery or prenatal interventions. Variant reclassification up or down across the actionability threshold can therefore have significant clinical consequences. Laboratory approaches to variant reinterpretation and reclassification vary widely. METHODS Cancer Variant Interpretation Group UK is a multidisciplinary network of clinical scientists and genetic clinicians from across the 24 Molecular Diagnostic Laboratories and Clinical Genetics Services of the United Kingdom (NHS) and Republic of Ireland. We undertook surveys, polls, and national meetings of Cancer Variant Interpretation Group UK to evaluate opinions about clinical and laboratory management regarding variant reclassification. RESULTS We generated a consensus framework on variant reclassification applicable to cancer susceptibility genes and other clinical areas, which provides explicit recommendations for clinical and laboratory management of variant reclassification scenarios on the basis of the nature of the new evidence, the magnitude of evidence shift, and the final classification score. CONCLUSION In this framework, clinical and laboratory resources are targeted for maximal clinical effect and minimal patient harm, as appropriate to all resource-constrained health care settings.
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Affiliation(s)
- Lucy Loong
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Alice Garrett
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Sophie Allen
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Subin Choi
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Miranda Durkie
- Sheffield Diagnostic Genetics Service, NHS North East and Yorkshire Genomic Laboratory Hub, Sheffield Children's NHS Foundation Trust, Sheffield, United Kingdom
| | - Alison Callaway
- Wessex Regional Genetics Laboratory, Central and South Genomics Laboratory Hub, Salisbury NHS Foundation Trust, Salisbury District Hospital, Salisbury, Wiltshire, United Kingdom
| | - James Drummond
- Cambridge Genomic Laboratory, East Genomic Laboratory Hub, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
| | - George J Burghel
- Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Rachel Robinson
- North East and Yorkshire Genomic Laboratory Hub, The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Beth Torr
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Ian R Berry
- Bristol Genetics Laboratory, Southmead Hospital, North Bristol NHS Trust, Bristol, United Kingdom
| | - Andrew J Wallace
- Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Diana M Eccles
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; Human Genetics and Genomic Medicine, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Sian Ellard
- Exeter Genomics Laboratory, South West Genomic Laboratory Hub, Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom; University of Exeter Medical School, Exeter, United Kingdom
| | - Emma Baple
- University of Exeter Medical School, Exeter, United Kingdom; Genomics England, London, United Kingdom
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Division of Evolution & Genomic Sciences, The University of Manchester, Manchester, United Kingdom
| | - Emma R Woodward
- Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Division of Evolution & Genomic Sciences, The University of Manchester, Manchester, United Kingdom
| | - Anjana Kulkarni
- Southeast Thames Regional Genetics Service, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Fiona Lalloo
- Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Marc Tischkowitz
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Anneke Lucassen
- Wellcome Centre for Human Genetics/Centre for Personalised Medicine, University of Oxford, Oxford, United Kingdom; Clinical Ethics and Law, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Helen Hanson
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom; Department of Clinical Genetics, St. George's University Hospitals NHS Foundation Trust, London, United Kingdom
| | - Clare Turnbull
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom; Cancer Genetics Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
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17
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Gonzalez A, Del Greco F, Vargas-Roig L, Brun B, Tabares G, Mampel A, Montes C, Martin C, Lopez M, Rossi N, Bruno L, Ponce C, Quaglio P, Yanzi A, Acevedo S, Lugo L, Lopez Breccia P, Avila S, Sisterna S, Del Castillo MS, Vazquez M, Nuñez LM. PALB2 germline mutations in a multi-gene panel testing cohort of 1905 breast-ovarian cancer patients in Argentina. Breast Cancer Res Treat 2022; 194:403-412. [PMID: 35610400 DOI: 10.1007/s10549-022-06620-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 04/30/2022] [Indexed: 11/24/2022]
Abstract
PURPOSE PALB2 variants have been scarcely described in Argentinian and Latin-American reports. In this study, we describe molecular and clinical characteristics of PALB2 mutations found in multi-gene panels (MP) from breast-ovarian cancer (BOC) families in different institutions from Argentina. METHODS We retrospectively identified PALB2 pathogenic (PV) and likely pathogenic (LPV) variants from a cohort of 1905 MP results, provided by one local lab (Heritas) and SITHER (Hereditary Tumor Information System) public database. All patients met hereditary BOC clinical criteria for testing, according to current guidelines. RESULTS The frequency of PALB2 mutations is 2.78% (53/1905). Forty-eight (90.5%) are PV and five (9.5%) are LPV. Most of the 18 different mutations (89%) are nonsense and frameshift types and 2 variants are novel. One high-rate recurrent PV (Y551*) is present in 43% (23/53) of the unrelated index cases. From the 53 affected carriers, 94% have BC diagnosis with 14% of bilateral cases. BC phenotype is mainly invasive ductal (78%) with 62% of hormone-receptor positive and 22% of triple negative tumors. Self-reported ethnic background of the cohort is West European (66%) and native Latin-American (20%) which is representative of Buenos Aires and other big urban areas of the country. CONCLUSION This is the first report describing molecular and clinical characteristics of PALB2 carriers in Argentina. Frequency of PALB2 PV in Argentinian HBOC families is higher than in other reported populations. Y551* is a recurrent mutation that seems to be responsible for almost 50% of PALB2 cases.
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Affiliation(s)
| | | | | | | | | | | | - Cecilia Montes
- Instituto Modelo de Ginecología Y Obstetricia, Córdoba, Argentina
| | - Claudia Martin
- Hospital Privado Universitario de Córdoba, Córdoba, Argentina
| | | | - Norma Rossi
- Fundación Para el Progreso de La Medicina, Córdoba, Argentina
| | - Luisina Bruno
- Instituto de Oncología Alexander Fleming, Buenos Aires, Argentina
| | - Carolina Ponce
- Instituto de Oncología Alexander Fleming, Buenos Aires, Argentina
| | | | | | | | - Lilia Lugo
- Clínica San Gerónimo, Santa Fe, Argentina
| | | | - Silvia Avila
- Facultad de Ciencias Médicas, Universidad Nacional del Comahue, Neuquén, Argentina.,Heritas - CONICET, Rosario, Argentina.,Hospital Alemán de Buenos Aires, Buenos Aires, Argentina
| | | | | | | | - Lina M Nuñez
- Hospital Alemán de Buenos Aires, Buenos Aires, Argentina.
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18
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Woodward ER, Green K, Burghel GJ, Bulman M, Clancy T, Lalloo F, Schlecht H, Wallace AJ, Evans DG. 30 year experience of index case identification and outcomes of cascade testing in high-risk breast and colorectal cancer predisposition genes. Eur J Hum Genet 2022; 30:413-419. [PMID: 34866136 PMCID: PMC8645350 DOI: 10.1038/s41431-021-01011-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 09/27/2021] [Accepted: 11/15/2021] [Indexed: 11/19/2022] Open
Abstract
It is 30 years since the first diagnostic cancer predisposition gene (CPG) test in the Manchester Centre for Genomic Medicine (MCGM), providing opportunities for cancer prevention, early detection and targeted treatments in index cases and at-risk family members. Here, we present time trends (1990-2020) of identification of index cases with a germline CPG variant and numbers of subsequent cascade tests, for 15 high-risk breast and gastro-intestinal tract cancer-associated CPGs: BRCA1, BRCA2, PALB2, PTEN, TP53, APC, BMPR1a, CDH1, MLH1, MSH2, MSH6, PMS2, SMAD4, STK11 and MUTYH. We recorded 2082 positive index case diagnostic screening tests, generating 3216 positive and 3140 negative family cascade (non-index) tests. This is equivalent to an average of 3.05 subsequent cascade tests per positive diagnostic index test, with 1.54 positive and 1.51 negative non-index tests per family. The CPGs with the highest numbers of non-index positive cases identified on cascade testing were BRCA1/2 (n = 1999) and the mismatch repair CPGs associated with Lynch Syndrome (n = 731). These data are important for service provision and health economic assessment of CPG diagnostic testing, in terms of cancer prevention and early detection strategies, and identifying those likely to benefit from targeted treatment strategies.
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Affiliation(s)
- Emma R Woodward
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PL, UK
| | - Kate Green
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
| | - George J Burghel
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Michael Bulman
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Tara Clancy
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PL, UK
| | - Fiona Lalloo
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Helene Schlecht
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Andrew J Wallace
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, M13 9WL, UK.
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PL, UK.
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Menko FH, Monkhorst K, Hogervorst FB, Rosenberg EH, Adank M, Ruijs MW, Bleiker EM, Sonke GS, Russell NS, Oldenburg HS, van der Kolk LE. Challenges in breast cancer genetic testing. A call for novel forms of multidisciplinary care and long-term evaluation. Crit Rev Oncol Hematol 2022; 176:103642. [DOI: 10.1016/j.critrevonc.2022.103642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 02/04/2022] [Accepted: 02/16/2022] [Indexed: 11/25/2022] Open
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20
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Evaluation of the Clinical Utility of Genomic Profiling to Inform Selection of Clinical Trial Therapy in Salivary Gland Cancer. Cancers (Basel) 2022; 14:cancers14051133. [PMID: 35267442 PMCID: PMC8909363 DOI: 10.3390/cancers14051133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 02/18/2022] [Accepted: 02/21/2022] [Indexed: 11/27/2022] Open
Abstract
For most patients with salivary gland cancer, there are no effective standard systemic therapies. Although clinical trials of biomarker-led drug therapies have delivered significant recent advances, there remains a need to understand the clinical utility of genomic profiling of cancer as a means to match patients with recurrent or metastatic salivary gland cancer to clinical trial therapies. In total, 209 patients with salivary gland cancers were profiled with 24 gene (n = 209)) and >325 gene (n = 32) DNA-based next-generation sequencing panels. A retrospective systematic evaluation was performed to identify the frequency of available matched drug therapies within clinical trials based on the results. The matches were then stratified based upon the level of evidence supporting the drug−biomarker combination being investigated using the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) to determine the strength of the clinical rationale for each gene−drug match identified. DNA-based next generation sequencing (NGS) analysis was successful in 175/209 (84%) patients with salivary gland cancer. Using the 24-gene NGS panel, actionable alterations were identified in 27% (48/175) patients. Alterations were most frequent in salivary duct carcinoma (88%) characterized by TP53 and/or PIK3CA mutations, with matched trials available for 63% (10/16). In ACC, biomarker-matched trials were available for 7% (8/115), and no genomic alterations were found in 96/115 (83%) of ACC patients. TP53 was the most frequently altered gene across all subtypes; however, there were no trials recruiting based on TP53 status. In 32 ACC patients with no genomic alterations using the 24-gene panel, a broader (>325 gene) panel identified alterations in 87% (27/32) of cases with biomarker-matched trials available in 40% (13/32) cases. This study identified that genomic profiling using focused (24-gene) NGS panels has potential utility in matching to trial therapies for most patients with non-ACC salivary gland cancer. For patients with ACC, broader genomic profiling has demonstrated added clinical utility. We describe the application of an approach to classification of levels of evidence which may be helpful to inform the clinician and patient decision making around the selection of clinical trial therapies.
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21
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BRCA1 Norway: comparison of classification for BRCA1 germline variants detected in families with suspected hereditary breast and ovarian cancer between different laboratories. Fam Cancer 2022; 21:389-398. [PMID: 34981296 PMCID: PMC9636114 DOI: 10.1007/s10689-021-00286-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 12/03/2021] [Indexed: 01/07/2023]
Abstract
Pathogenic germline variants in Breast cancer susceptibility gene 1 (BRCA1) predispose carriers to hereditary breast and ovarian cancer (HBOC). Through genetic testing of patients with suspected HBOC an increasing number of novel BRCA1 variants are discovered. This creates a growing need to determine the clinical significance of these variants through correct classification (class 1-5) according to established guidelines. Here we present a joint collection of all BRCA1 variants of class 2-5 detected in the four diagnostic genetic laboratories in Norway. The overall objective of the study was to generate an overview of all BRCA1 variants in Norway and unveil potential discrepancies in variant interpretation between the hospitals, serving as a quality control at the national level. For a subset of variants, we also assessed the change in classification over a ten-year period with increasing information available. In total, 463 unique BRCA1 variants were detected. Of the 126 variants found in more than one hospital, 70% were interpreted identically, while 30% were not. The differences in interpretation were mainly by one class (class 2/3 or 4/5), except for one larger discrepancy (class 3/5) which could affect the clinical management of patients. After a series of digital meetings between the participating laboratories to disclose the cause of disagreement for all conflicting variants, the discrepancy rate was reduced to 10%. This illustrates that variant interpretation needs to be updated regularly, and that data sharing and improved national inter-laboratory collaboration greatly improves the variant classification and hence increases the accuracy of cancer risk assessment.
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22
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Garrett A, Loveday C, King L, Butler S, Robinson R, Horton C, Yussuf A, Choi S, Torr B, Durkie M, Burghel GJ, Drummond J, Berry I, Wallace A, Callaway A, Eccles D, Tischkowitz M, Tatton-Brown K, Snape K, McVeigh T, Izatt L, Woodward ER, Burnichon N, Gimenez-Roqueplo AP, Mazzarotto F, Whiffin N, Ware J, Hanson H, Pesaran T, LaDuca H, Buffet A, Maher ER, Turnbull C. Quantifying evidence toward pathogenicity for rare phenotypes: The case of succinate dehydrogenase genes, SDHB and SDHD. Genet Med 2021; 24:41-50. [PMID: 34906457 PMCID: PMC8759765 DOI: 10.1016/j.gim.2021.08.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 03/26/2021] [Accepted: 08/10/2021] [Indexed: 10/25/2022] Open
Abstract
PURPOSE The weight of the evidence to attach to observation of a novel rare missense variant in SDHB or SDHD in individuals with the rare neuroendocrine tumors, pheochromocytomas and paragangliomas (PCC/PGL), is uncertain. METHODS We compared the frequency of SDHB and SDHD very rare missense variants (VRMVs) in 6328 and 5847 cases of PCC/PGL, respectively, with that of population controls to generate a pan-gene VRMV likelihood ratio (LR). Via windowing analysis, we measured regional enrichments of VRMVs to calculate the domain-specific VRMV-LR (DS-VRMV-LR). We also calculated subphenotypic LRs for variant pathogenicity for various clinical, histologic, and molecular features. RESULTS We estimated the pan-gene VRMV-LR to be 76.2 (54.8-105.9) for SDHB and 14.8 (8.7-25.0) for SDHD. Clustering analysis revealed an SDHB enriched region (ɑɑ 177-260, P = .001) for which the DS-VRMV-LR was 127.2 (64.9-249.4) and an SDHD enriched region (ɑɑ 70-114, P = .000003) for which the DS-VRMV-LR was 33.9 (14.8-77.8). Subphenotypic LRs exceeded 6 for invasive disease (SDHB), head-and-neck disease (SDHD), multiple tumors (SDHD), family history of PCC/PGL, loss of SDHB staining on immunohistochemistry, and succinate-to-fumarate ratio >97 (SDHB, SDHD). CONCLUSION Using methodology generalizable to other gene-phenotype dyads, the LRs relating to rarity and phenotypic specificity for a single observation in PCC/PGL of a SDHB/SDHD VRMV can afford substantial evidence toward pathogenicity.
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Affiliation(s)
- Alice Garrett
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Chey Loveday
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Laura King
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Samantha Butler
- Central and South Genomic Laboratory Hub, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, United Kingdom
| | - Rachel Robinson
- North East and Yorkshire Genomic Laboratory Hub, Central Lab, The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | | | | | - Subin Choi
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Beth Torr
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom
| | - Miranda Durkie
- North East and Yorkshire Genomic Laboratory Hub, Sheffield Children's NHS Foundation Trust, Sheffield, United Kingdom
| | - George J Burghel
- The Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - James Drummond
- East Genomic Laboratory Hub, Cambridge University Hospitals Genomic Laboratory, Cambridge University Hospitals, Cambridge, United Kingdom
| | - Ian Berry
- North East and Yorkshire Genomic Laboratory Hub, Central Lab, The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Andrew Wallace
- The Manchester Centre for Genomic Medicine and North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Alison Callaway
- Central and South Genomics Laboratory Hub, Wessex Regional Genetics Laboratory, Salisbury Hospital NHS Foundation Trust, Salisbury District Hospital, Salisbury, United Kingdom
| | - Diana Eccles
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; Human Genetics and Genomic Medicine, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Marc Tischkowitz
- Department of Medical Genetics, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom; East Anglian Medical Genetics Unit, Cambridge University Hospitals NHS Trust, Cambridge, United Kingdom
| | - Katrina Tatton-Brown
- St. George's University, London, United Kingdom; Department of Clinical Genetics, St. George's University Hospitals NHS Foundation Trust, London, United Kingdom
| | - Katie Snape
- St. George's University, London, United Kingdom; Department of Clinical Genetics, St. George's University Hospitals NHS Foundation Trust, London, United Kingdom
| | - Terri McVeigh
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Louise Izatt
- Clinical Genetics, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Emma R Woodward
- Manchester Centre for Genomic Medicine, Manchester Academic Health Sciences Centre (MAHSC), Manchester University NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution and Genomic Sciences, School of Biological Sciences, Manchester Academic Health Sciences Centre (MAHSC), University of Manchester, Manchester, United Kingdom
| | - Nelly Burnichon
- University of Paris, PARCC, INSERM, Equipe Labellisée par la Ligue contre le Cancer, Paris, France; Genetics Department, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Paris, France
| | - Anne-Paule Gimenez-Roqueplo
- University of Paris, PARCC, INSERM, Equipe Labellisée par la Ligue contre le Cancer, Paris, France; Genetics Department, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Paris, France
| | - Francesco Mazzarotto
- National Heart and Lung Institute and MRC London Institute of Medical Sciences, Imperial College London, London, United Kingdom; Royal Brompton and Harefield Hospitals, London, United Kingdom
| | - Nicola Whiffin
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom; The Centre for Personalised Medicine, St Anne's College, University of Oxford, Oxford, United Kingdom
| | - James Ware
- National Heart and Lung Institute and MRC London Institute of Medical Sciences, Imperial College London, London, United Kingdom; Royal Brompton and Harefield Hospitals, London, United Kingdom
| | - Helen Hanson
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom; Department of Clinical Genetics, St. George's University Hospitals NHS Foundation Trust, London, United Kingdom
| | | | | | - Alexandre Buffet
- University of Paris, PARCC, INSERM, Equipe Labellisée par la Ligue contre le Cancer, Paris, France; Genetics Department, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Paris, France
| | - Eamonn R Maher
- Department of Medical Genetics, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Clare Turnbull
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, United Kingdom; Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, United Kingdom.
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23
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Frugtniet B, Morgan S, Murray A, Palmer-Smith S, White R, Jones R, Hanna L, Fuller C, Hudson E, Mullard A, Quinton AE. The detection of germline and somatic BRCA1/2 genetic variants through parallel testing of patients with high-grade serous ovarian cancer: a national retrospective audit. BJOG 2021; 129:433-442. [PMID: 34657373 PMCID: PMC9298909 DOI: 10.1111/1471-0528.16975] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 08/11/2021] [Accepted: 09/12/2021] [Indexed: 12/05/2022]
Abstract
Objective To determine the frequency of germline and somatic pathogenic BRCA1 and BRCA2 variants in patients with high‐grade serous ovarian cancer tested by next‐generation sequencing (NGS), with the aim of defining the best strategy to be implemented in future routine testing. Design National retrospective audit. Setting The All Wales Medical Genomics Service (AWMGS). Population Patients with high‐grade serous ovarian/fallopian tube/peritoneal cancer referred by oncologists to the AWMGS between February 2015 and February 2021 for germline and/or tumour testing of the BRCA1 and BRCA2 genes by NGS. Methods Analysis of NGS data from germline and/or tumour testing. Main outcome measures Frequency of BRCA1 and BRCA2 pathogenic variants. Results The overall observed germline/somatic pathogenic variant detection rate was 11.6% in the 844 patients included in this study, with a 9.2% (73/791) germline pathogenic variant detection rate. Parallel tumour and germline testing was carried out for 169 patients and the overall pathogenic variant detection rate for this cohort was 14.8%, with 6.5% (11/169) shown to have a somatic pathogenic variant. Two BRCA1 dosage variants were found during germline screens, representing 2.0% (2/98) of patients with a pathogenic variant that would have been missed through tumour testing alone. Conclusions Parallel germline and tumour BRCA1 and BRCA2 testing maximises the detection of pathogenic variants in patients with high‐grade serous ovarian cancer. Tweetable abstract Parallel germline and tumour testing maximises BRCA pathogenic variant detection in ovarian cancer. Parallel germline and tumour testing maximises BRCA pathogenic variant detection in ovarian cancer. Linked article This article is commented on by C Gourley, p. 443 in this issue. To view this mini commentary visit https://doi.org/10.1111/1471-0528.16978.
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Affiliation(s)
- B Frugtniet
- All Wales Medical Genomics Laboratory, University Hospital of Wales, Cardiff, UK
| | - S Morgan
- All Wales Medical Genomics Laboratory, University Hospital of Wales, Cardiff, UK
| | - A Murray
- All Wales Medical Genomics Service, University Hospital of Wales, Cardiff, UK
| | - S Palmer-Smith
- All Wales Medical Genomics Laboratory, University Hospital of Wales, Cardiff, UK
| | - R White
- All Wales Medical Genomics Laboratory, University Hospital of Wales, Cardiff, UK
| | - R Jones
- South West Wales Cancer Centre, Singleton Hospital, Swansea, UK
| | - L Hanna
- Velindre Cancer Centre, Velindre University NHS Trust, Cardiff, UK
| | - C Fuller
- Bwrdd Iechyd Prifysgol Betsi Cadwaladr University Health Board, Bangor, UK
| | - E Hudson
- Velindre Cancer Centre, Velindre University NHS Trust, Cardiff, UK
| | - A Mullard
- Bwrdd Iechyd Prifysgol Betsi Cadwaladr University Health Board, Bangor, UK
| | - A E Quinton
- Velindre Cancer Centre, Velindre University NHS Trust, Cardiff, UK
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24
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Chandrasekaran D, Sobocan M, Blyuss O, Miller RE, Evans O, Crusz SM, Mills-Baldock T, Sun L, Hammond RFL, Gaba F, Jenkins LA, Ahmed M, Kumar A, Jeyarajah A, Lawrence AC, Brockbank E, Phadnis S, Quigley M, El Khouly F, Wuntakal R, Faruqi A, Trevisan G, Casey L, Burghel GJ, Schlecht H, Bulman M, Smith P, Bowers NL, Legood R, Lockley M, Wallace A, Singh N, Evans DG, Manchanda R. Implementation of Multigene Germline and Parallel Somatic Genetic Testing in Epithelial Ovarian Cancer: SIGNPOST Study. Cancers (Basel) 2021; 13:cancers13174344. [PMID: 34503154 PMCID: PMC8431198 DOI: 10.3390/cancers13174344] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/09/2021] [Accepted: 08/24/2021] [Indexed: 11/16/2022] Open
Abstract
We present findings of a cancer multidisciplinary-team (MDT) coordinated mainstreaming pathway of unselected 5-panel germline BRCA1/BRCA2/RAD51C/RAD51D/BRIP1 and parallel somatic BRCA1/BRCA2 testing in all women with epithelial-OC and highlight the discordance between germline and somatic testing strategies across two cancer centres. Patients were counselled and consented by a cancer MDT member. The uptake of parallel multi-gene germline and somatic testing was 97.7%. Counselling by clinical-nurse-specialist more frequently needed >1 consultation (53.6% (30/56)) compared to a medical (15.0% (21/137)) or surgical oncologist (15.3% (17/110)) (p < 0.001). The median age was 54 (IQR = 51-62) years in germline pathogenic-variant (PV) versus 61 (IQR = 51-71) in BRCA wild-type (p = 0.001). There was no significant difference in distribution of PVs by ethnicity, stage, surgery timing or resection status. A total of 15.5% germline and 7.8% somatic BRCA1/BRCA2 PVs were identified. A total of 2.3% patients had RAD51C/RAD51D/BRIP1 PVs. A total of 11% germline PVs were large-genomic-rearrangements and missed by somatic testing. A total of 20% germline PVs are missed by somatic first BRCA-testing approach and 55.6% germline PVs missed by family history ascertainment. The somatic testing failure rate is higher (23%) for patients undergoing diagnostic biopsies. Our findings favour a prospective parallel somatic and germline panel testing approach as a clinically efficient strategy to maximise variant identification. UK Genomics test-directory criteria should be expanded to include a panel of OC genes.
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Affiliation(s)
- Dhivya Chandrasekaran
- Wolfson Institute of Population Health, Barts CRUK Cancer Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; (D.C.); (M.S.); (O.E.); (L.S.); (F.G.)
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
| | - Monika Sobocan
- Wolfson Institute of Population Health, Barts CRUK Cancer Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; (D.C.); (M.S.); (O.E.); (L.S.); (F.G.)
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
- Divison for Gynaecology and Perinatology, University Medical Centre Maribor, 2000 Maribor, Slovenia
| | - Oleg Blyuss
- School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK;
- Department of Paediatrics and Paediatric Infectious Diseases, Sechenov First Moscow State Medical University, Moscow 119991, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Rowan E. Miller
- Department of Medical Oncology, Barts Health NHS Trust, London EC1A 7BE, UK; (R.E.M.); (S.M.C.)
| | - Olivia Evans
- Wolfson Institute of Population Health, Barts CRUK Cancer Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; (D.C.); (M.S.); (O.E.); (L.S.); (F.G.)
| | - Shanthini M. Crusz
- Department of Medical Oncology, Barts Health NHS Trust, London EC1A 7BE, UK; (R.E.M.); (S.M.C.)
| | - Tina Mills-Baldock
- Department of Medical Oncology, Barking, Havering & Redbridge University Hospitals, Essex RM7 0AG, UK; (T.M.-B.); (M.Q.); (F.E.K.)
| | - Li Sun
- Wolfson Institute of Population Health, Barts CRUK Cancer Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; (D.C.); (M.S.); (O.E.); (L.S.); (F.G.)
- Department of Health Services Research, Faculty of Public Health & Policy, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK;
| | - Rory F. L. Hammond
- Department of Pathology, Barts Health NHS Trust, London E1 1FR, UK; (R.F.L.H.); (A.F.); (G.T.); (L.C.); (N.S.)
| | - Faiza Gaba
- Wolfson Institute of Population Health, Barts CRUK Cancer Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; (D.C.); (M.S.); (O.E.); (L.S.); (F.G.)
| | - Lucy A. Jenkins
- North East Thames Regional Genetics Service, Great Ormond Street Hospital, London WC1N 3JH, UK; (L.A.J.); (M.A.); (A.K.)
| | - Munaza Ahmed
- North East Thames Regional Genetics Service, Great Ormond Street Hospital, London WC1N 3JH, UK; (L.A.J.); (M.A.); (A.K.)
| | - Ajith Kumar
- North East Thames Regional Genetics Service, Great Ormond Street Hospital, London WC1N 3JH, UK; (L.A.J.); (M.A.); (A.K.)
| | - Arjun Jeyarajah
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
| | - Alexandra C. Lawrence
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
| | - Elly Brockbank
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
| | - Saurabh Phadnis
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
| | - Mary Quigley
- Department of Medical Oncology, Barking, Havering & Redbridge University Hospitals, Essex RM7 0AG, UK; (T.M.-B.); (M.Q.); (F.E.K.)
| | - Fatima El Khouly
- Department of Medical Oncology, Barking, Havering & Redbridge University Hospitals, Essex RM7 0AG, UK; (T.M.-B.); (M.Q.); (F.E.K.)
| | - Rekha Wuntakal
- Department of Gynaecology, Barking, Havering & Redbridge University Hospitals, Essex RM7 0AG, UK;
| | - Asma Faruqi
- Department of Pathology, Barts Health NHS Trust, London E1 1FR, UK; (R.F.L.H.); (A.F.); (G.T.); (L.C.); (N.S.)
| | - Giorgia Trevisan
- Department of Pathology, Barts Health NHS Trust, London E1 1FR, UK; (R.F.L.H.); (A.F.); (G.T.); (L.C.); (N.S.)
| | - Laura Casey
- Department of Pathology, Barts Health NHS Trust, London E1 1FR, UK; (R.F.L.H.); (A.F.); (G.T.); (L.C.); (N.S.)
| | - George J. Burghel
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Helene Schlecht
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Michael Bulman
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Philip Smith
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Naomi L. Bowers
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Rosa Legood
- Department of Health Services Research, Faculty of Public Health & Policy, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK;
| | - Michelle Lockley
- Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK;
| | - Andrew Wallace
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Naveena Singh
- Department of Pathology, Barts Health NHS Trust, London E1 1FR, UK; (R.F.L.H.); (A.F.); (G.T.); (L.C.); (N.S.)
| | - D. Gareth Evans
- Manchester Centre for Genomic Medicine, Saint Marys Hospital, Manchester M13 9WL, UK; (G.J.B.); (H.S.); (M.B.); (P.S.); (N.L.B.); (A.W.); (D.G.E.)
| | - Ranjit Manchanda
- Wolfson Institute of Population Health, Barts CRUK Cancer Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; (D.C.); (M.S.); (O.E.); (L.S.); (F.G.)
- Department of Gynaecological Oncology, Barts Health NHS Trust, London EC1 1BB, UK; (A.J.); (A.C.L.); (E.B.); (S.P.)
- Department of Health Services Research, Faculty of Public Health & Policy, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK;
- Correspondence:
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25
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Woodward ER, van Veen EM, Evans DG. From BRCA1 to Polygenic Risk Scores: Mutation-Associated Risks in Breast Cancer-Related Genes. Breast Care (Basel) 2021; 16:202-213. [PMID: 34248461 DOI: 10.1159/000515319] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/16/2021] [Indexed: 12/12/2022] Open
Abstract
Background There has been huge progress over the last 30 years in identifying the familial component of breast cancer. Summary Currently around 20% is explained by the high-risk genes BRCA1 and BRCA2, a further 2% by other high-penetrance genes, and around 5% by the moderate risk genes ATM and CHEK2. In contrast, the more than 300 low-penetrance single-nucleotide polymorphisms (SNP) now account for around 28% and they are predicted to account for most of the remaining 45% yet to be found. Even for high-risk genes which confer a 40-90% risk of breast cancer, these SNP can substantially affect the level of breast cancer risk. Indeed, the strength of family history and hormonal and reproductive factors is very important in assessing risk even for a BRCA carrier. The risks of contralateral breast cancer are also affected by SNP as well as by the presence of high or moderate risk genes. Genetic testing using gene panels is now commonplace. Key-Messages There is a need for a more parsimonious approach to panels only testing those genes with a definite 2-fold increased risk and only testing those genes with challenging management implications, such as CDH1 and TP53, when there is strong clinical indication to do so. Testing of SNP alongside genes is likely to provide a more accurate risk assessment.
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Affiliation(s)
- Emma R Woodward
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Elke M van Veen
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.,PREVENT Breast Cancer Prevention Centre, Nightingale Centre, Manchester Universities Foundation Trust, Wythenshawe Hospital, Manchester, United Kingdom.,Manchester Breast Centre, Manchester Cancer Research Centre, The Christie, University of Manchester, Manchester, United Kingdom
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26
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Wedderburn S, McVeigh TP. Should All Individuals Be Screened for Genetic Predisposition to Cancer? Genet Res (Camb) 2021; 2021:6611963. [PMID: 33762893 PMCID: PMC7953527 DOI: 10.1155/2021/6611963] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 11/30/2020] [Indexed: 12/02/2022] Open
Affiliation(s)
- Sarah Wedderburn
- West of Scotland Regional Genetics Service, Laboratory Medicine Building, Queen Elizabeth University Hospital, Glasgow, UK
| | - Terri P. McVeigh
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
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27
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Feliubadaló L, Moles-Fernández A, Santamariña-Pena M, Sánchez AT, López-Novo A, Porras LM, Blanco A, Capellá G, de la Hoya M, Molina IJ, Osorio A, Pineda M, Rueda D, de la Cruz X, Diez O, Ruiz-Ponte C, Gutiérrez-Enríquez S, Vega A, Lázaro C. A Collaborative Effort to Define Classification Criteria for ATM Variants in Hereditary Cancer Patients. Clin Chem 2020; 67:518-533. [PMID: 33280026 DOI: 10.1093/clinchem/hvaa250] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 09/29/2020] [Indexed: 12/30/2022]
Abstract
BACKGROUND Gene panel testing by massive parallel sequencing has increased the diagnostic yield but also the number of variants of uncertain significance. Clinical interpretation of genomic data requires expertise for each gene and disease. Heterozygous ATM pathogenic variants increase the risk of cancer, particularly breast cancer. For this reason, ATM is included in most hereditary cancer panels. It is a large gene, showing a high number of variants, most of them of uncertain significance. Hence, we initiated a collaborative effort to improve and standardize variant classification for the ATM gene. METHODS Six independent laboratories collected information from 766 ATM variant carriers harboring 283 different variants. Data were submitted in a consensus template form, variant nomenclature and clinical information were curated, and monthly team conferences were established to review and adapt American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria to ATM, which were used to classify 50 representative variants. RESULTS Amid 283 different variants, 99 appeared more than once, 35 had differences in classification among laboratories. Refinement of ACMG/AMP criteria to ATM involved specification for twenty-one criteria and adjustment of strength for fourteen others. Afterwards, 50 variants carried by 254 index cases were classified with the established framework resulting in a consensus classification for all of them and a reduction in the number of variants of uncertain significance from 58% to 42%. CONCLUSIONS Our results highlight the relevance of data sharing and data curation by multidisciplinary experts to achieve improved variant classification that will eventually improve clinical management.
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Affiliation(s)
- Lidia Feliubadaló
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Oncobell Program, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | | | - Marta Santamariña-Pena
- Fundación Pública Galega Medicina Xenómica (FPGMX), SERGAS, Santiago de Compostela, Spain.,Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain.,Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Alysson T Sánchez
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Oncobell Program, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
| | - Anael López-Novo
- Fundación Pública Galega Medicina Xenómica (FPGMX), SERGAS, Santiago de Compostela, Spain.,Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Luz-Marina Porras
- Research Unit in Clinical and Translational Bioinformatics, Vall d'Hebron Institute of Research (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ana Blanco
- Fundación Pública Galega Medicina Xenómica (FPGMX), SERGAS, Santiago de Compostela, Spain.,Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain.,Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Gabriel Capellá
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Oncobell Program, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Miguel de la Hoya
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Molecular Oncology Laboratory, Hospital Clínico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Madrid, Spain
| | - Ignacio J Molina
- Institute of Biopathology and Regenerative Medicine, Center for Biomedical Research, Health Sciences Technology Park, Universtity of Granada, Granada, Spain
| | - Ana Osorio
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain.,Human Genetics Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Marta Pineda
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Oncobell Program, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Daniel Rueda
- Hereditary Cancer Laboratory, Doce de Octubre University Hospital, i+12 Research Institute, Madrid, Spain
| | - Xavier de la Cruz
- Research Unit in Clinical and Translational Bioinformatics, Vall d'Hebron Institute of Research (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Orland Diez
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.,Clinical and Molecular Genetics Area, University Hospital Vall d'Hebron, Barcelona, Spain
| | - Clara Ruiz-Ponte
- Fundación Pública Galega Medicina Xenómica (FPGMX), SERGAS, Santiago de Compostela, Spain.,Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain.,Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Sara Gutiérrez-Enríquez
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Ana Vega
- Fundación Pública Galega Medicina Xenómica (FPGMX), SERGAS, Santiago de Compostela, Spain.,Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain.,Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Conxi Lázaro
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Oncobell Program, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
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28
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Garrett A, Durkie M, Callaway A, Burghel GJ, Robinson R, Drummond J, Torr B, Cubuk C, Berry IR, Wallace AJ, Ellard S, Eccles DM, Tischkowitz M, Hanson H, Turnbull C. Combining evidence for and against pathogenicity for variants in cancer susceptibility genes: CanVIG-UK consensus recommendations. J Med Genet 2020; 58:297-304. [PMID: 33208383 PMCID: PMC8086256 DOI: 10.1136/jmedgenet-2020-107248] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 08/07/2020] [Accepted: 08/13/2020] [Indexed: 12/15/2022]
Abstract
Accurate classification of variants in cancer susceptibility genes (CSGs) is key for correct estimation of cancer risk and management of patients. Consistency in the weighting assigned to individual elements of evidence has been much improved by the American College of Medical Genetics (ACMG) 2015 framework for variant classification, UK Association for Clinical Genomic Science (UK-ACGS) Best Practice Guidelines and subsequent Cancer Variant Interpretation Group UK (CanVIG-UK) consensus specification for CSGs. However, considerable inconsistency persists regarding practice in the combination of evidence elements. CanVIG-UK is a national subspecialist multidisciplinary network for cancer susceptibility genomic variant interpretation, comprising clinical scientist and clinical geneticist representation from each of the 25 diagnostic laboratories/clinical genetic units across the UK and Republic of Ireland. Here, we summarise the aggregated evidence elements and combinations possible within different variant classification schemata currently employed for CSGs (ACMG, UK-ACGS, CanVIG-UK and ClinGen gene-specific guidance for PTEN, TP53 and CDH1). We present consensus recommendations from CanVIG-UK regarding (1) consistent scoring for combinations of evidence elements using a validated numerical 'exponent score' (2) new combinations of evidence elements constituting likely pathogenic' and 'pathogenic' classification categories, (3) which evidence elements can and cannot be used in combination for specific variant types and (4) classification of variants for which there are evidence elements for both pathogenicity and benignity.
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Affiliation(s)
- Alice Garrett
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, London, UK
| | - Miranda Durkie
- Sheffield Diagnostic Genetics Service, Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | - Alison Callaway
- Wessex Regional Genetics Laboratory, Salisbury Hospital NHS Foundation Trust, Salisbury, Wiltshire, UK.,Human Genetics and Genomic Medicine, University of Southampton Faculty of Medicine, Southampton, UK
| | - George J Burghel
- Manchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Rachel Robinson
- Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - James Drummond
- East Anglian Medical Genetics Service, Addenbrooke's Hospital, Cambridge, Cambridgeshire, UK
| | - Bethany Torr
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, London, UK
| | - Cankut Cubuk
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, London, UK
| | - Ian R Berry
- Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Andrew J Wallace
- Manchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Sian Ellard
- Department of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, Devon, UK
| | - Diana M Eccles
- Cancer Sciences Research Group, University of Southampton Faculty of Medicine, Southampton, UK
| | - Marc Tischkowitz
- Department of Medical Genetics and National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, Cambridgeshire, UK
| | - Helen Hanson
- Department of Clinical Genetics, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, London, UK .,Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
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