Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.

BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity of cancer vaccine data significantly impedes effective integration and analysis. While CanVaxKB serves as a pioneering database for over 670 manually annotated cancer vaccines, it is important to distinguish that a database, on its own, does not offer the structured relationships and standardized definitions found in an ontology. Recognizing this, we expanded the Vaccine Ontology (VO) to include those cancer vaccines present in CanVaxKB that were not initially covered, enhancing VO's capacity to systematically define and interrelate cancer vaccines. RESULTS: An ontology design pattern (ODP) was first developed and applied to semantically represent various cancer vaccines, capturing their associated entities and relations. By applying the ODP, we generated a cancer vaccine template in a tabular format and converted it into the RDF/OWL format for generation of cancer vaccine terms in the VO. '12MP vaccine' was used as an example of cancer vaccines to demonstrate the application of the ODP. VO also reuses reference ontology terms to represent entities such as cancer diseases and vaccine hosts. Description Logic (DL) and SPARQL query scripts were developed and used to query for cancer vaccines based on different vaccine's features and to demonstrate the versatility of the VO representation. Additionally, ontological modeling was applied to illustrate cancer vaccine related concepts and studies for in-depth cancer vaccine analysis. A cancer vaccine-specific VO view, referred to as "CVO," was generated, and it contains 928 classes including 704 cancer vaccines. The CVO OWL file is publicly available on: http://purl.obolibrary.org/obo/vo/cvo.owl , for sharing and applications. CONCLUSION: To facilitate the standardization, integration, and analysis of cancer vaccine data, we expanded the Vaccine Ontology (VO) to systematically model and represent cancer vaccines. We also developed a pipeline to automate the inclusion of cancer vaccines and associated terms in the VO. This not only enriches the data's standardization and integration, but also leverages ontological modeling to deepen the analysis of cancer vaccine information, maximizing benefits for researchers and clinicians. AVAILABILITY: The VO-cancer GitHub website is: https://github.com/vaccineontology/VO/tree/master/CVO .

NASCI case of the month: "Unroofed coronary sinus without persistent left-sided superior vena cava".

Unroofed sinus is categorized into four subtypes. Types I and II represent complete unroofing with or without an LSVC, respectively [1]. Types III and IV are partial unroofing involving the mid-CS (type III) or near the LA appendage and left superior pulmonary vein (type IV) [1]. CT has advantages over echocardiography in detection of this anomaly (illustrated in this case) as well as in precise delineation of defect and associated findings (presence or absence of LSVC). Short axis reconstructions at the level of CS are helpful in diagnosis. Considerations for repair include location of CS defect, presence of LSVC and other abnormalities as well as comorbidity risks [2].

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.

Students' Perspectives: How Will COVID-19 Shape the Social Determinants of Health and Our Future as Public Health Practitioners?

We are the next generation of public health practitioners. As public health students, we acknowledge that the COVID-19 (coronavirus disease 2019) pandemic will continue to fundamentally alter the field that we are preparing to enter. We will be the first wave of public health professionals whose education is being shaped by this pandemic. For decades to come, we will be working to address the impacts of this pandemic. In this commentary, we are lending our voice to discuss and highlight the importance of considering the intersections of various determinants of health and COVID-19, including education, food insecurity, housing instability, and economic hardship. We provide a discussion on what is being done across the United States in attempts to reduce the growing health inequities. As the next generation of public health leaders, we believe that only by investing in these issues can we begin to address the social and economic impact of the COVID-19 pandemic.