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Related Experiment Videos

Validation of tissue microarray technology in ovarian carcinoma.

Daniel G Rosen1, Xuelin Huang, Michael T Deavers

  • 1Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030-4095, USA.

Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc
|April 10, 2004
PubMed
Summary

Tissue microarray analysis of ovarian carcinoma is reliable. A single core sample accurately represents whole sections over 90% of the time, with two cores increasing accuracy to over 95%.

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Area of Science:

  • Oncology
  • Pathology
  • Biotechnology

Background:

  • Tissue microarray (TMA) enables high-throughput analysis of clinical specimens.
  • Tumor heterogeneity necessitates validation studies for accurate representation in TMAs.
  • Ovarian carcinoma presents unique challenges due to its heterogeneity.

Purpose of the Study:

  • To evaluate the reliability of TMA in representing whole-section immunostaining for high-grade serous ovarian carcinoma.
  • To determine the optimal number of tissue cores for accurate biomarker analysis.

Main Methods:

  • Immunostaining for Ki-67, estrogen receptors, and p53 was performed on whole sections and six-core samples from 45 ovarian carcinoma cases.
  • Automated image analysis and a 0-3 scoring scale were used for staining evaluation.

Related Experiment Videos

  • Correlation coefficients and probability of accurate representation were calculated.

    • Main Results:

    • Correlation coefficients for whole-section vs. core stains were 0.86 (Ki-67), 0.93 (estrogen receptors), and 0.82 (p53).
    • Only 6.6% of cores were inadequate for scoring.
    • One core accurately represented whole-section staining in 91% of cases; two cores increased accuracy to 96%.

    Conclusions:

    • Ovarian carcinoma TMA is a reliable technique for marker expression analysis.
    • A single readable core can represent whole-section staining patterns in over 90% of cases.
    • Using two cores further enhances the reliability of TMA in ovarian cancer studies.