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


Journal

Cancer genomics & proteomics
ISSN: 1790-6245
Titre abrégé: Cancer Genomics Proteomics
Pays: Greece
ID NLM: 101188791

Informations de publication

Date de publication:
Historique:
received: 29 12 2020
revised: 23 01 2021
accepted: 29 01 2021
entrez: 20 2 2021
pubmed: 21 2 2021
medline: 29 9 2021
Statut: ppublish

Résumé

Recently, guidelines for variant interpretation in cancer have been established. However, these guidelines do not mention which databases are most suited to performing this task. We give an overview of existing databases and evaluate their benefit in practical application. We compared three meta-databases and 12 databases for a dataset of patients with myelodysplastic syndrome or acute myeloid leukemia. Clinical implications were found for 13% of all variants. One-third of variants with therapeutic implications were uniquely contained in one database. The VICC meta-database was the most extensive source of information, featuring 92% of variants with a drug association. However, a comparison of meta-databases and original sources indicated that some variants are missing in those meta-databases. Public databases provide decision support for interpreting variants but there is still need for manual curation. Meta-databases facilitate the use of multiple resources but should be interpreted with caution.

Sections du résumé

BACKGROUND BACKGROUND
Recently, guidelines for variant interpretation in cancer have been established. However, these guidelines do not mention which databases are most suited to performing this task.
MATERIALS AND METHODS METHODS
We give an overview of existing databases and evaluate their benefit in practical application. We compared three meta-databases and 12 databases for a dataset of patients with myelodysplastic syndrome or acute myeloid leukemia.
RESULTS RESULTS
Clinical implications were found for 13% of all variants. One-third of variants with therapeutic implications were uniquely contained in one database. The VICC meta-database was the most extensive source of information, featuring 92% of variants with a drug association. However, a comparison of meta-databases and original sources indicated that some variants are missing in those meta-databases.
CONCLUSION CONCLUSIONS
Public databases provide decision support for interpreting variants but there is still need for manual curation. Meta-databases facilitate the use of multiple resources but should be interpreted with caution.

Identifiants

pubmed: 33608312
pii: 18/2/157
doi: 10.21873/cgp.20250
pmc: PMC7943210
doi:

Types de publication

Case Reports Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

157-166

Informations de copyright

Copyright© 2021, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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Auteurs

Henrik Banck (H)

Institute of Medical Informatics, University of Münster, Münster, Germany.

Martin Dugas (M)

Institute of Medical Informatics, University of Münster, Münster, Germany.

Carsten MÜller-Tidow (C)

Medizinische Klinik, Abteilung Innere Medizin V, University Hospital Heidelberg, Heidelberg, Germany.

Sarah Sandmann (S)

Institute of Medical Informatics, University of Münster, Münster, Germany; sarah.sandmann@unimuenster.de.

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Classifications MeSH