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The tissue microarray object model: a data model for storage, analysis, and exchange of tissue microarray

Hye Won Lee1, Yu Rang Park, Jaehyun Sim

  • 1Seoul National University Biomedical Informatics, Seoul, Korea.

Archives of Pathology & Laboratory Medicine
|July 13, 2006
PubMed
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A new tissue microarray object model (TMA-OM) standardizes data for hundreds of tissue samples. This facilitates the handling, exchange, and dissemination of vital TMA data for cancer research.

Area of Science:

  • Biomedical Informatics
  • Pathology
  • Genomics

Background:

  • Tissue microarray (TMA) technology enables high-throughput analysis of numerous tissue samples on a single slide.
  • Standardized data representation is crucial for managing, exchanging, and disseminating TMA data, including methods, generated data, and clinical/histopathologic information.
  • Existing data models and specifications lack comprehensive support for diverse TMA experimental designs and evolving data elements.

Purpose of the Study:

  • To develop a flexible, expressive, and extensible data model for tissue microarrays.
  • To ensure the model adequately describes new clinical and histopathologic data elements.
  • To support diverse experimental designs in TMA analysis.

Main Methods:

  • Designed the tissue microarray object model (TMA-OM) by referencing existing models like the microarray gene expression object model and minimum information specifications.

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  • Incorporated clinical and histopathologic information using standards from the College of American Pathologists and National Cancer Institute.
  • Utilized controlled vocabularies from established ontologies and NCI common data elements for unambiguous data annotation.

    • Main Results:

    • The TMA-OM comprises 111 classes across 17 packages, covering clinical, histopathologic, and experimental data for all cancer types.
    • A web-based application was developed to support the TMA-OM, enabling data export in XML format.
    • The exported data conforms to TMA data exchange specifications or document type definitions derived from the TMA-OM.

    Conclusions:

    • The TMA-OM offers a robust framework for storing, analyzing, and exchanging TMA data.
    • This standardized model enhances the integration of TMA data with other biological models.
    • Facilitates more efficient and comprehensive TMA data management in cancer research.