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 (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.
Bibliographical noteFunding Information:
We acknowledge the contributions from members of GA4GH and specifically the Genotype to Phenotype Task Team for their numerous contributions leading to this study. We thank the VICC knowledgebase partners for their input in construction of the meta-knowledgebase and drafting of the paper, M. McCoy for his assistance in proofreading the manuscript and J. McMichael for his work in restyling Fig. 1. A.H.W. was supported by NIH National Cancer Institute (NCI) award F32CA206247 and National Human Genome Research Institute (NHGRI) award K99HG010157. B.W. was supported by NIH NHGRI award U54HG007990, NIH NCI R01CA180778 and Intel SRA-16-037. D.T.R. is a participant in the Berlin Institute of Health—Charité Clinical Scientist Program funded by the Charité—Universitätsmedizin Berlin and the Berlin Institute of Health, and was supported by grant nos. 031L0030E and 031L0023 awarded by the German Federal Ministry of Education and Research. D.I.R. and S.M. are supported by ClinGen, through the NHGRI awards U41HG006834, U41HG009649, U41HG009650 and U01HG007437. T.A. was supported by an award from Academy of Finland (grant no. 330857), Cancer Society of Finland. M.H. was supported by the Monarch Initiative NIH Office of Director award R24OD011883. J. Gao, D.C. and N.S. were supported by NIH NCI award P30CA008748. N.L.B. acknowledges funding from the European Research Council (consolidator grant 682398). M.L. was supported through the Medical Research Council—Cancer Research UK Stratification in Colorectal Cancer Program grant and Health Data Research UK Substantive Site grant. M.G. was supported by NIH NHGRI award R00HG007940 and a V Scholar Award from the V Foundation for Cancer Research. O.L.G., M.G. and the CIViC knowledgebase were supported by the NIH NCI awards U01CA209936 and U24CA237719 and a Cancer Moonshot funding opportunity, specifically an Activities to Promote Technology Research Collaborations for Cancer Research (Administrative Support) award.
© 2020, The Author(s).
Copyright 2020 Elsevier B.V., All rights reserved.
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