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Published on: May 31, 2015
Tissue microarrays: one size does not fit all.
Jeanette E Eckel-Passow1, Christine M Lohse, Yuri Sheinin
1Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. eckelpassow.jeanette@mayo.edu
Diagnostic Pathology
|July 9, 2010
Summary
The number of tissue microarray (TMA) cores needed to accurately represent biomarker expression varies by biomarker and tumor type. Optimizing TMA core number is crucial to avoid false-negative findings in research, particularly for biomarkers like B7-H1 in clear cell renal cell carcinoma.
Area of Science:
- Oncology
- Pathology
- Biomarker Research
Background:
- Tissue microarrays (TMAs) are widely used in research but lack standardized guidelines for evaluating their suitability for specific biomarkers and tumor types.
- The performance consistency of TMAs across different biomarkers has not been thoroughly investigated.
Purpose of the Study:
- To determine the optimal number of tissue microarray (TMA) cores required to accurately represent biomarker expression in whole tissue sections for clear cell renal cell carcinoma (RCC).
- To assess the impact of TMA core number on the detection of associations between biomarker expression and RCC-specific mortality.
Main Methods:
- A simulated TMA approach was used, varying from 1 to 10 cores, to analyze the expression of six biomarkers (B7-H1, B7-H3, survivin, Ki-67, CAIX, IMP3) in 100 clear cell RCC patient samples.
- Immunohistochemical quantification was performed on both whole tissue sections and simulated TMAs to evaluate agreement and determine the necessary number of cores for reliable biomarker representation.
- Associations between biomarker expression (from whole tissue sections and TMAs) and RCC-specific death were analyzed.
Main Results:
- The required number of TMA cores for adequate representation of biomarker quantification varied significantly by biomarker.
- 2-3 cores were sufficient for B7-H3, Ki-67, CAIX, and IMP3, but even 10 cores showed poor agreement for B7-H1 and survivin compared to whole tissue sections.
- Whole tissue section B7-H1 expression was linked to RCC-specific death, whereas this association was not detected with up to 10 TMA cores, indicating potential false-negative results due to suboptimal TMA design.
Conclusions:
- Establishing the appropriate number of TMA cores is essential before analysis to ensure accurate representation of biomarker expression, as a universal standard does not exist.
- Simulated TMAs offer a cost-effective method for determining the optimal core number for specific biomarker and tumor type investigations.
