CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase

Krysiak, K. et al. (2023) CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase. Nucleic Acids Research, 51(D1), D1230-D1241. (doi: 10.1093/nar/gkac979) (PMID:36373660)

Abstract

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC’s functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lever, Dr Jake
• Authors: Krysiak, K., Danos, A. M., Saliba, J., McMichael, J. F., Coffman, A. C., Kiwala, S., Barnell, E. K., Sheta, L., Grisdale, C. J., Kujan, L., Pema, S., Lever, J., Ridd, S., Spies, N. C., Andric, V., Chiorean, A., Rieke, D. T., Clark, K. A., Reisle, C., Venigalla, A. C., Evans, M., Jani, P., Takahashi, H., Suda, A., Horak, P., Ritter, D. I., Zhou, X., Ainscough, B. J., Delong, S., Kesserwan, C., Lamping, M., Shen, H., Marr, A. R., Hoang, M. H., Singhal, K., Khanfar, M., Li, B. V., Lin, W.-H., Terraf, P., Corson, L. B., Salama, Y., Campbell, K. M., Farncombe, K. M., Ji, J., Zhao, X., Xu, X., Kanagal-Shamanna, R., King, I., Cotto, K. C., Skidmore, Z. L., Walker, J. R., Zhang, J., Milosavljevic, A., Patel, R. Y., Giles, R. H., Kim, R. H., Schriml, L. M., Mardis, E. R., Jones, S. J.M., Raca, G., Rao, S., Madhavan, S., Wagner, A. H., Griffith, M., and Griffith, O. L.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Nucleic Acids Research
• Publisher: Oxford University Press
• ISSN: 0305-1048
• ISSN (Online): 1362-4962
• Published Online: 14 November 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Nucleic Acids Research 51(D1): D1230-D1241
• Publisher Policy: Reproduced under a Creative Commons License

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