Back to Search Start Over

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

Authors :
Krysiak K
Danos AM
Saliba J
McMichael JF
Coffman AC
Kiwala S
Barnell EK
Sheta L
Grisdale CJ
Kujan L
Pema S
Lever J
Ridd S
Spies NC
Andric V
Chiorean A
Rieke DT
Clark KA
Reisle C
Venigalla AC
Evans M
Jani P
Takahashi H
Suda A
Horak P
Ritter DI
Zhou X
Ainscough BJ
Delong S
Kesserwan C
Lamping M
Shen H
Marr AR
Hoang MH
Singhal K
Khanfar M
Li BV
Lin WH
Terraf P
Corson LB
Salama Y
Campbell KM
Farncombe KM
Ji J
Zhao X
Xu X
Kanagal-Shamanna R
King I
Cotto KC
Skidmore ZL
Walker JR
Zhang J
Milosavljevic A
Patel RY
Giles RH
Kim RH
Schriml LM
Mardis ER
Jones SJM
Raca G
Rao S
Madhavan S
Wagner AH
Griffith M
Griffith OL
Source :
Nucleic acids research [Nucleic Acids Res] 2023 Jan 06; Vol. 51 (D1), pp. D1230-D1241.
Publication Year :
2023

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.<br /> (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Details

Language :
English
ISSN :
1362-4962
Volume :
51
Issue :
D1
Database :
MEDLINE
Journal :
Nucleic acids research
Publication Type :
Academic Journal
Accession number :
36373660
Full Text :
https://doi.org/10.1093/nar/gkac979