A1 Refereed original research article in a scientific journal
A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer
Authors: Alex H. Wagner, Brian Walsh, Georgia Mayfield, David Tamborero, Dmitriy Sonkin, Kilannin Krysiak, Jordi Deu-Pons, Ryan P. Duren, Jianjiong Gao, Julie McMurry, Sara Patterson, Catherine del Vecchio Fitz, Beth A. Pitel, Ozman U. Sezerman, Kyle Ellrott, Jeremy L. Warner, Damian T. Rieke, Tero Aittokallio, Ethan Cerami, Deborah I. Ritter, Lynn M. Schriml, Robert R. Freimuth, Melissa Haendel, Gordana Raca, Subha Madhavan, Michael Baudis, Jacques S. Beckmann, Rodrigo Dienstmann, Debyani Chakravarty,Xuan Shirley Li, Susan Mockus, Olivier Elemento, Nikolaus Schultz, Nuria Lopez-Bigas, Mark Lawler, Jeremy Goecks, Malachi Griffith, Obi L. Griffith, Adam A. Margolin
Publisher: NATURE PUBLISHING GROUP
Publication year: 2020
Journal: Nature Genetics
Journal name in source: NATURE GENETICS
Journal acronym: NAT GENET
Volume: 52
Issue: 4
First page : 448
Last page: 457
Number of pages: 17
ISSN: 1061-4036
eISSN: 1546-1718
DOI: https://doi.org/10.1038/s41588-020-0603-8
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/46959005
Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface () for exploring the harmonized interpretations from these six knowledgebases.
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