Evolution of the open-access CIViC knowledgebase is driven by the needs of the cancer variant interpretation community

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. With nearly 300 contributors, CIViC contains peer-reviewed, published literature curated and expert-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 distributes clinically-relevant cancer variant data currently representing >2500 variants in >400 genes from >2800 publications.

[1]  Steven J. M. Jones,et al.  A platform for oncogenomic reporting and interpretation , 2021, Nature Communications.

[2]  S. Fröhling,et al.  Targeting rare and non-canonical driver variants in NSCLC - An uncharted clinical field. , 2021, Lung cancer.

[3]  Diane B. Zastrow,et al.  ClinGen Variant Curation Interface: a variant classification platform for the application of evidence criteria from ACMG/AMP guidelines , 2021, medRxiv.

[4]  Christopher G Chute,et al.  The Human Phenotype Ontology in 2021 , 2020, Nucleic Acids Res..

[5]  Peter McQuilton,et al.  Biocuration - mapping resources and needs. , 2020, F1000Research.

[6]  M. Griffith,et al.  Neoantigen prediction and computational perspectives towards clinical benefit: Recommendations from the ESMO Precision Medicine Working Group. , 2020, Annals of oncology : official journal of the European Society for Medical Oncology.

[7]  Steven J. M. Jones,et al.  Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes , 2020, Nature Cancer.

[8]  Alex H. Wagner,et al.  A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer , 2020, Nature Genetics.

[9]  Thomas Shafee,et al.  Wikidata as a knowledge graph for the life sciences , 2020, eLife.

[10]  R. Karchin,et al.  Integrated Informatics Analysis of Cancer-Related Variants , 2020, JCO clinical cancer informatics.

[11]  K. S. Weber,et al.  Genomics Education in the Era of Personal Genomics: Academic, Professional, and Public Considerations , 2020, International journal of molecular sciences.

[12]  Subha Madhavan,et al.  Standard operating procedure for curation and clinical interpretation of variants in cancer , 2019, Genome Medicine.

[13]  Malachi Griffith,et al.  CIViCpy: A Python Software Development and Analysis Toolkit for the CIViC Knowledgebase , 2019, bioRxiv.

[14]  Donna Neuberg,et al.  A dominant-negative effect drives selection of TP53 missense mutations in myeloid malignancies , 2019, Science.

[15]  David Luis Wiegandt,et al.  Comparative Analysis of Public Knowledge Bases for Precision Oncology. , 2019, JCO precision oncology.

[16]  R. Hopkin,et al.  Genomic education for the next generation of health-care providers , 2019, Genetics in Medicine.

[17]  R. Giles,et al.  The incidence of consecutive manifestations in Von Hippel-Lindau disease , 2019, Familial Cancer.

[18]  B. Taylor,et al.  Germline-focussed analysis of tumour-only sequencing: recommendations from the ESMO Precision Medicine Working Group , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.

[19]  M. Tempero.  NCCN Guidelines Updates: Pancreatic Cancer. , 2019, Journal of the National Comprehensive Cancer Network : JNCCN.

[20]  Vanessa L. Horner,et al.  27. ACMG/CGC technical laboratory standards for interpretation and reporting of acquired copy number abnormalities (CNAs) and copy-neutral loss of heterozygosity (CN-LOH) in neoplastic disorders , 2019, Cancer Genetics.

[21]  Steven J. M. Jones,et al.  Text-mining clinically relevant cancer biomarkers for curation into the CIViC database , 2018, Genome Medicine.

[22]  Michelle Giglio,et al.  Human Disease Ontology 2018 update: classification, content and workflow expansion , 2018, Nucleic Acids Res..

[23]  K. Offit,et al.  Integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes , 2018, Human mutation.

[24]  Aleksandar Milosavljevic,et al.  ClinGen Allele Registry links information about genetic variants , 2018, Human mutation.

[25]  Joshua F. McMichael,et al.  Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community‐driven standards , 2018, Human mutation.

[26]  N. Schultz,et al.  A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.

[27]  Eran Segal,et al.  A Systematic p53 Mutation Library Links Differential Functional Impact to Cancer Mutation Pattern and Evolutionary Conservation. , 2018, Molecular cell.

[28]  Cristina Has,et al.  Faculty of 1000 evaluation for Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. , 2018 .

[29]  Dexter Pratt,et al.  NDEx 2.0: A Clearinghouse for Research on Cancer Pathways. , 2017, Cancer research.

[30]  P. Kantoff,et al.  Mutation Detection in Patients With Advanced Cancer by Universal Sequencing of Cancer-Related Genes in Tumor and Normal DNA vs Guideline-Based Germline Testing , 2017, JAMA.

[31]  G. Mills,et al.  Neomorphic mutations create therapeutic challenges in cancer , 2017, Oncogene.

[32]  Steven J. M. Jones,et al.  CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer , 2017, Nature Genetics.

[33]  Reece K. Hart,et al.  Somatic cancer variant curation and harmonization through consensus minimum variant level data , 2016, Genome Medicine.

[34]  Mario Cazzola,et al.  The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. , 2016, Blood.

[35]  Obi L. Griffith,et al.  High-performance web services for querying gene and variant annotation , 2016, Genome Biology.

[36]  V. Prasad,et al.  Assessing the Eventual Publication of Clinical Trial Abstracts Submitted to a Large Annual Oncology Meeting. , 2016, The oncologist.

[37]  Jinghui Zhang,et al.  Reply to Artifacts in the data of Hu et al. , 2015, Nature Genetics.

[38]  Bale,et al.  Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology , 2015, Genetics in Medicine.

[39]  Benjamin M. Good,et al.  Organizing knowledge to enable personalization of medicine in cancer , 2014, Genome Biology.

[40]  S. Ng,et al.  Characterization of rare transforming KRAS mutations in sporadic colorectal cancer , 2014, Cancer biology & therapy.

[41]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[42]  A. Sparks,et al.  The Genomic Landscapes of Human Breast and Colorectal Cancers , 2007, Science.

[43]  Joon-Oh Park,et al.  Somatic VHL alteration and its impact on prognosis in patients with clear cell renal cell carcinoma. , 2005, Oncology reports.

[44]  Larry Wright,et al.  Overview and Utilization of the NCI Thesaurus , 2004, Comparative and functional genomics.

[45]  S. Kato,et al.  Understanding the function–structure and function–mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[46]  H. Kocher,et al.  Pancreatic Cancer , 2019, Methods in Molecular Biology.

[47]  Subha Madhavan,et al.  ClinGen Cancer Somatic Working Group - Standardizing and democratizing access to cancer molecular diagnostic data to drive translational research , 2018, PSB.

[48]  Marilyn M. Li,et al.  Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. , 2017, The Journal of molecular diagnostics : JMD.

[49]  G. Collins.  The next generation. , 2006, Scientific American.

[50]  A. Sakurai,et al.  [von Hippel-Lindau syndrome]. , 2001, Ryoikibetsu shokogun shirizu.

[51]  H. Muller.  Further studies on the nature and causes of gene mutations. , 1932 .