Towards an Ontology for Representing Malignant Neoplasms

Oncology research produces data about a wide variety of entities such as tumor types, locations, pathology, and staging, patient treatments and outcomes, and experimental systems such as mouse models and cell lines. In order to conduct effective cancer research, terminologies, classification systems, and ontologies are needed that can integrate these various datasets and provide standards for consistently representing entities. In this paper, we discuss our ongoing efforts to address these difficulties by developing a realism-based ontology for representing instances of malignant neoplasms, disease progression, treatments, and outcomes. This ontology is being built using the principles of the OBO Foundry, and makes use of other OBO Foundry ontologies, such as the Ontology for General Medical Sciences, Uberon, and the Cell Ontology. As a result of our efforts, we have made worthwhile progress towards developing a robust ontological framework for representing malignant neoplasms.