19. Developing a generalized model for variants in CIViC

Increased clinical use of next generation sequencing has generated a variant interpretation bottleneck. CIViC (Clinical Interpretations of Variants in Cancer; civicdb.org) addresses this problem by leveraging crowdsourced literature and abstract curation with expert moderation in a completely free and open worldwide resource. The CIViC data model incorporates established and emerging guidelines for classification, and associates evidence to single or multi-variant Molecular Profiles (MPs). Large-scale alterations involving multiple genes and non-genic regions are clinically important in multiple cancers. For instance, haploinsufficiency of multiple genes in 5q31.2 have been implicated in de novo myelodysplastic syndromes (MDS), and deletions of this region are used in risk-stratification in this disease. HPV positive oropharyngeal and MSI high colorectal cancer are associated with better outcome, demonstrating non-gene biomarker clinical relevance. Most cancer variant knowledgebases focus on either large-scale or small SNVs and indels related to genes. Modifications to the CIViC data model are needed to incorporate this breadth of evidence into CIViC curation. Currently, variants are strictly associated to Genes, and multiple variants constitute an MP. We will introduce `Regions' which describe generalized areas of the genome not associated with a specific gene. `Factors' will describe non-gene entities not associated to a specific area of the genome, such as MSI, HPV infection, tumor mutational burden, or chromosomal abnormalities. Incorporation of these entities into CIViC alongside the use of multi variant MPs will grant CIViC exceptional flexibility in representing forms of cancer variation essential to modern clinical care in a single interface. Increased clinical use of next generation sequencing has generated a variant interpretation bottleneck. CIViC (Clinical Interpretations of Variants in Cancer; civicdb.org) addresses this problem by leveraging crowdsourced literature and abstract curation with expert moderation in a completely free and open worldwide resource. The CIViC data model incorporates established and emerging guidelines for classification, and associates evidence to single or multi-variant Molecular Profiles (MPs). Large-scale alterations involving multiple genes and non-genic regions are clinically important in multiple cancers. For instance, haploinsufficiency of multiple genes in 5q31.2 have been implicated in de novo myelodysplastic syndromes (MDS), and deletions of this region are used in risk-stratification in this disease. HPV positive oropharyngeal and MSI high colorectal cancer are associated with better outcome, demonstrating non-gene biomarker clinical relevance. Most cancer variant knowledgebases focus on either large-scale or small SNVs and indels related to genes. Modifications to the CIViC data model are needed to incorporate this breadth of evidence into CIViC curation. Currently, variants are strictly associated to Genes, and multiple variants constitute an MP. We will introduce `Regions' which describe generalized areas of the genome not associated with a specific gene. `Factors' will describe non-gene entities not associated to a specific area of the genome, such as MSI, HPV infection, tumor mutational burden, or chromosomal abnormalities. Incorporation of these entities into CIViC alongside the use of multi variant MPs will grant CIViC exceptional flexibility in representing forms of cancer variation essential to modern clinical care in a single interface.