1st International Workshop on Oncology and Ontology

New Castle, UK September 13, 2017

in conjunction with the

International Conference on Biological Ontology (2017)

** Submission Deadline: Extended to July 9th, 2017  **


Wednesday 13th September 2017, 9:00 – 12:30

9:00                 Introduction


Tailoring the NCI Thesaurus for use in the OBO Library

        James Balhoff, Matthew Brush, Laura Christopherson, Sherri de Coronado, Gilberto Fragoso, 

        Melissa Haendel, Christopher Mungall, Kimberly Robasky, Nicole Vasilevsky and Lawrence Wright

The amount and diversity of knowledge and data being generated by the cancer research community is unprecedented in biomedicine, with data being collected on human samples, animals, and in vitro model systems. The data range from health records, to RNAseq, genomics, clinical trials, pathway analytics, modifier variant discovery, exposures, and pathology. To assist in standardizing these data, the National Cancer Institute (NCI) Thesaurus (NCIt) has been developed as a reference terminology and ontology that provides definitions, synonyms, and other information on nearly 10,000 cancers and related diseases, 8,000 single agents and combination therapies, and a wide range of other entities related to cancer and biomedical research. The NCIt is richly axiomatized with knowledge about tissues and cells of origin, causality, cancer grade, and much more.


Towards an Ontology for Representing Malignant Neoplasm

William Duncan, Carmelo Gaudioso and Alexander Diehl

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.

10:10                   Discussion

10:30 - 11:00       Break


Ontology of cancer related social-ecological variables

Dharani K Balasubramanian, Jamillah Khan, Jiang Bian, Yi Guo, William Hogan and Amanda Hicks

Several social-ecological (SE) factors affect human behavior. Analysis of these factors is an integral part of behavior research. An efficient method of scrutinizing these predictors is multilevel analysis. Social Ecological Model (SEM) is a multilevel framework that helps to capture all the variables at five levels: individual, interpersonal, organizational, community, and policy. This work aims to develop a reference ontology with classes that correspond to SE predictors that influence cancer diagnosis, beginning with the individual level of SEM. This ontology is built with an aim to aid data integration in order to carry out multilevel analysis of the integrated data. The broad hypothesis is that, if all the variables gathered from various sources and at different levels of the SEM are configured in an ontology, there will be enough information to identify and visualize association between these variables and health outcomes. This work is focused on 13 SE variables which were first identified by performing a scoping literature review. Manually curated terms corresponding to these variables were aligned with existing ontology classes. The ontology of cancer related socialecological variables (OCRSEV) is built upon the Basic Formal Ontology 2.0 (BFO 2.0) and conforms to Open Biomedical Ontologies (OBO) Foundry’s best practices. Future work is planned to extend the ontology for variables in other levels of SEM and map the PCORnet Common Data Model (PCORnet CDM) data and other relevant data with these variables in the ontology.

11:30                   Late Breaking Work Discussion

Workshop Theme and Topics

To effectively treat and prevent cancer, we need to bring together data from multiple domains, such as electronic medical records, genomic data, tissue data, epidemiological data, and clinical trial data. Personalized medicine requires the integration of clinical and research findings from multiple disciplines, and cancer strikes each affected individual in a unique and specific way from the molecular, cellular, anatomical, genetic, and emotional perspectives. We aim to convene an interdisciplinary group of ontologists and cancer researchers through the ONCONTO (oncology and ontology) workshop in order to advance the ontological representation of cancer and related entities to support both broader research in the domain and personalized treatment approaches. 

Topics to include: 

  • Revision and expansion of existing ontological resources for representing cancer and related biomedical entities creation of new ontologies for the oncology domain that address gaps in representation.
  • Ontology-based data analysis of cancer patient or basic research data related to epidemiology, etiology, genomics, diagnosis, and treatment of cancer.
  • Use of ontologies for translational research related to cancer; and exploratory research or position papers related to ontologies and cancer.

We will organize our workshop into different sections based on the topics of presentations. Presentation time allocation will be determined after the number of each submission type is finalized. Panel discussions at the end of each section will be arranged based on the time availability.


For the paper submission, we will allow three submission formats:

  • Full research papers (6-10 pages) format
  • Work in progress / late breaking results (2-4 pages)
  • A one page statement of interest or current work for podium presentation; if accepted you have the option of preparing a poster for presentation at the main conference poster session as well

  • Relevant posters submitted to the main conference (you need to inform us) if arrangements are made with organizers ahead of time.

The paper format will be the same as the format used in ICBO.

All the papers will be submitted and handled through Easy Chair:


Workshop Schedule/Important Dates

  • Individual Workshop Papers Due: Extended to July 9th2017
  • Notification of Acceptance: July 28, 2017

Workshop Organizers

Alexander D. Diehl, PhD

Assistant Professor of Biomedical Informatics

Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 

The State University of New York

New York State Center of Excellence in Bioinformatics & Life Sciences


William D. Duncan, PhD

Assistant Professor of Oncology

Associate Director of the Clinical Data Network

Roswell Park Cancer Institute


Carmelo Gaudioso, MD, PhD

Assistant Member, Clinical Research

Roswell Park Cancer Institute


Program Committee (PC) Members  
  • To be announced