A Collaborative Effort to Define Classification Criteria for ATM Variants in Hereditary Cancer Patients.


Journal

Clinical chemistry
ISSN: 1530-8561
Titre abrégé: Clin Chem
Pays: England
ID NLM: 9421549

Informations de publication

Date de publication:
01 03 2021
Historique:
received: 17 06 2020
accepted: 29 09 2020
pubmed: 7 12 2020
medline: 24 9 2021
entrez: 6 12 2020
Statut: ppublish

Résumé

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. 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. 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%. 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.

Sections du résumé

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.

Identifiants

pubmed: 33280026
pii: 6024902
doi: 10.1093/clinchem/hvaa250
doi:

Substances chimiques

ATM protein, human EC 2.7.11.1
Ataxia Telangiectasia Mutated Proteins EC 2.7.11.1

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

518-533

Informations de copyright

© American Association for Clinical Chemistry 2020.

Auteurs

Lidia Feliubadaló (L)

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.

Alejandro Moles-Fernández (A)

Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.

Marta Santamariña-Pena (M)

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 (AT)

Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.
Oncobell Program, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain.

Anael López-Novo (A)

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 (LM)

Research Unit in Clinical and Translational Bioinformatics, Vall d'Hebron Institute of Research (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.

Ana Blanco (A)

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 (G)

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 (M)

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 (IJ)

Institute of Biopathology and Regenerative Medicine, Center for Biomedical Research, Health Sciences Technology Park, Universtity of Granada, Granada, Spain.

Ana Osorio (A)

Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain.
Human Genetics Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.

Marta Pineda (M)

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 (D)

Hereditary Cancer Laboratory, Doce de Octubre University Hospital, i+12 Research Institute, Madrid, Spain.

Xavier de la Cruz (X)

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 (O)

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 (C)

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 (S)

Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.

Ana Vega (A)

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 (C)

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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Classifications MeSH