CanVaxKB: a web-based cancer vaccine knowledgebase.

Cancer vaccines have been increasingly studied and developed to prevent or treat various types of cancers. To systematically survey and analyze different reported cancer vaccines, we developed CanVaxKB (https://violinet.org/canvaxkb), the first web-based cancer vaccine knowledgebase that compiles over 670 therapeutic or preventive cancer vaccines that have been experimentally verified to be effective at various stages. Vaccine construction and host response data are also included. These cancer vaccines are developed against various cancer types such as melanoma, hematological cancer, and prostate cancer. CanVaxKB has stored 263 genes or proteins that serve as cancer vaccine antigen genes, which we have collectively termed 'canvaxgens'. Top three mostly used canvaxgens are PMEL, MLANA and CTAG1B, often targeting multiple cancer types. A total of 193 canvaxgens are also reported in cancer-related ONGene, Network of Cancer Genes and/or Sanger Cancer Gene Consensus databases. Enriched functional annotations and clusters of canvaxgens were identified and analyzed. User-friendly web interfaces are searchable for querying and comparing cancer vaccines. CanVaxKB cancer vaccines are also semantically represented by the community-based Vaccine Ontology to support data exchange. Overall, CanVaxKB is a timely and vital cancer vaccine source that facilitates efficient collection and analysis, further helping researchers and physicians to better understand cancer mechanisms.

Ontology-Based Classification and Analysis of Adverse Events Associated With the Usage of Chloroquine and Hydroxychloroquine.

Multiple methodologies have been developed to identify and predict adverse events (AEs); however, many of these methods do not consider how patient population characteristics, such as diseases, age, and gender, affect AEs seen. In this study, we evaluated the utility of collecting and analyzing AE data related to hydroxychloroquine (HCQ) and chloroquine (CQ) from US Prescribing Information (USPIs, also called drug product labels or package inserts), the FDA Adverse Event Reporting System (FAERS), and peer-reviewed literature from PubMed/EMBASE, followed by AE classification and modeling using the Ontology of Adverse Events (OAE). Our USPI analysis showed that CQ and HCQ AE profiles were similar, although HCQ was reported to be associated with fewer types of cardiovascular, nervous system, and musculoskeletal AEs. According to EMBASE literature mining, CQ and HCQ were associated with QT prolongation (primarily when treating COVID-19), heart arrhythmias, development of Torsade des Pointes, and retinopathy (primarily when treating lupus). The FAERS data was analyzed by proportional ratio reporting, Chi-square test, and minimal case number filtering, followed by OAE classification. HCQ was associated with 63 significant AEs (including 21 cardiovascular AEs) for COVID-19 patients and 120 significant AEs (including 12 cardiovascular AEs) for lupus patients, supporting the hypothesis that the disease being treated affects the type and number of certain CQ/HCQ AEs that are manifested. Using an HCQ AE patient example reported in the literature, we also ontologically modeled how an AE occurs and what factors (e.g., age, biological sex, and medical history) are involved in the AE formation. The methodology developed in this study can be used for other drugs and indications to better identify patient populations that are particularly vulnerable to AEs.