PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data.

Journal: Briefings in bioinformatics
PMID: 38557678

Abstract

Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO, http://pcaontology.net/ and http://pcaontology.net/mobile/.

Authors

  • Chunjiang Yu
    Center for Systems Biology, Soochow University, Suzhou, China; School of Biotechnology, Suzhou Industrial Park Institute of Services Outsourcing, China.
  • Hui Zong
    Research Center for Translational Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China.
  • Yalan Chen
    Center for Systems Biology, Soochow University, Suzhou 215006, China.
  • Yibin Zhou
    Department of Urology, The Second Affiliated Hospital of Soochow University, Suzhou, 215011, China.
  • Xingyun Liu
    Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
  • Yuxin Lin
    School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.
  • Jiakun Li
    Department of Urology and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610212, China.
  • Xiaonan Zheng
    Department of Urology and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China.
  • Hua Min
    Hua Min, Department of Health Administration and Policy, College of Health and Human Services, George Mason University, MS: 1J3, 4400 University Drive, Fairfax, VA 22030-4444, USA, E-mail: hmin3@gmu.edu.
  • Bairong Shen
    Institute of Systems Genetics, Department of Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610000, China.

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