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

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.

Large scale genotype- and phenotype-driven machine learning in Von Hippel-Lindau disease.

Von Hippel-Lindau (VHL) disease is a hereditary cancer syndrome where individuals are predisposed to tumor development in the brain, adrenal gland, kidney, and other organs. It is caused by pathogenic variants in the VHL tumor suppressor gene. Standardized disease information has been difficult to collect due to the rarity and diversity of VHL patients. Over 4100 unique articles published until October 2019 were screened for germline genotype-phenotype data. Patient data were translated into standardized descriptions using Human Genome Variation Society gene variant nomenclature and Human Phenotype Ontology terms and has been manually curated into an open-access knowledgebase called Clinical Interpretation of Variants in Cancer. In total, 634 unique VHL variants, 2882 patients, and 1991 families from 427 papers were captured. We identified relationship trends between phenotype and genotype data using classic statistical methods and spectral clustering unsupervised learning. Our analyses reveal earlier onset of pheochromocytoma/paraganglioma and retinal angiomas, phenotype co-occurrences and genotype-phenotype correlations including hotspots. It confirms existing VHL associations and can be used to identify new patterns and associations in VHL disease. Our database serves as an aggregate knowledge translation tool to facilitate sharing information about the pathogenicity of VHL variants.

Comprehensive characterization of a Canadian cohort of von Hippel-Lindau disease patients.

Von Hippel-Lindau disease (VHL) is a heritable condition caused by pathogenic variants in VHL and is characterized by benign and malignant lesions in the central nervous system (CNS) and abdominal viscera. Due to its variable expressivity, existing efforts to collate VHL patient data do not adequately capture all VHL manifestations. We developed a comprehensive and standardized VHL database in the web-based application, REDCap, that thoroughly captures all VHL manifestation data. As an initial trial, information from 86 VHL patients from the University Health Network/Hospital for Sick Children was populated into the database. Analysis of this cohort showed missense variants occurring with the greatest frequency, with all variants localizing to the α- or ß-domains of VHL. The most prevalent manifestations were central nervous system (CNS), renal, and retinal neoplasms, which were associated with frameshift variants and large deletions. We observed greater age-related penetrance for CNS hemangioblastomas with truncating variants compared to missense, while the reverse was true for pheochromocytomas. We demonstrate the utility of a comprehensive VHL database, which supports the standardized collection of clinical and genetic data specific to this patient population. Importantly, we expect that its web-based design will facilitate broader international collaboration and lead to a better understanding of VHL.