Abstract 3211: Evolution of the CIViC knowledgebase for community driven curation of clinical variants in cancer

• Published in: Cancer research (Chicago, Ill.) Ill.), 2020-08, Vol.80 (16_Supplement), p.3211-3211
• Main Authors: Danos, Arpad, Krysiak, Kilannin, Barnell, Erica K., Coffman, Adam C., McMichael, Joshua F., Kiwala, Susanna, Spies, Nicholas C., Sheta, Lana M., Pema, Shahil P., Kujan, Lynzey, Clark, Kaitlin A., Anderson, Sydney, Wollam, Amber, Li, Brian, Guerra, Justin, Rao, Shruti, Ritter, Deborah I., Grisdale, Cameron J., Raca, Gordana, Wagner, Alex H., Madhavan, Subha, Griffith, Malachi, Griffith, Obi L.
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2020-3211

With increasing adoption of next generation sequencing into clinical practice, the problem of clinical interpretation of tumor variants arises as a bottleneck for patient care, as effective annotation of these variants draws from a constantly increasing body of largely unstructured clinical and preclinical results. One model to sustain clinical variant curation is to house variant annotation behind a paywall, using access fees to fund further curation effort. An alternate approach is to leverage public curation and expert moderation to create a free public resource to house and distribute this knowledge. The Clinical Interpretation of Variants in Cancer (CIViC, www.civicdb.org) knowledgebase employs the latter approach, and is a free and open-access public resource with an intuitive user interface and flexible public API for programmatic access to all content, which is available to the public with no restrictions on usage. All data is available for retrieval without login, while registration with a free account is required to contribute curation. The provenance of all curation and revision in CIViC is viewable through the web interface, and curators may also leave public comments on all content. Selected expert editors review and revise submitted content, which is clearly labeled as accepted once it has fully undergone moderation. All content in CIViC adheres to a structured data model which follows a published standard operating procedure for curation. This data model incorporates ontologies, standards and guidelines from across the field to promote interoperability and compatibility with other efforts. The CIViC interface also allows curators and organizations to track and display summary statistics of all their activity. CIViC currently has a community of over 190 curators and 16,000 clinical and research users around the world. CIViC continually develops and improves both new and existing features in response to user feedback as well as collaborative and internal development goals. Recently, the drugs and treatment terms used in predictive/therapeutic annotation have been normalized to the NCI Thesaurus. A conflict of interest (COI) statement is now required for all CIViC Editors, and functionality for writing and displaying the COI has been built into the interface. CIViC employs Predictive (Therapeutic), Prognostic, Diagnostic, Predisposing evidence types, and we highlight the recently introduced Functional evidence type, which has seen continued dev