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Updated: Aug 7, 2026
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Production of Tissue Microarrays, Immunohistochemistry Staining and Digitalization Within the Human Protein Atlas
Published on: May 31, 2012
Tissue microarrays in cancer diagnosis
Ronald Simon1, Martina Mirlacher, Guido Sauter
1Institute of Pathology, Division of Molecular Pathology, University of Basel, Switzerland. Ronald.Simon@unibas.ch
Expert Review of Molecular Diagnostics
|July 25, 2003
Summary
New molecular techniques identify disease markers but are costly. Tissue microarray technology enables large-scale validation of these markers for cancer research and therapeutic applications.
Area of Science:
- Biotechnology
- Molecular Biology
- Cancer Research
Background:
- High-throughput molecular techniques (cDNA, protein, antibody arrays) identify numerous disease-related markers.
- Limitations include high costs and the need for unfixed tissues, hindering large-scale studies.
- Validation studies with well-defined tissue samples are crucial for identifying impactful markers.
Purpose of the Study:
- To discuss the applications and future potential of tissue microarray technology.
- To highlight how tissue microarrays address limitations in traditional tissue analysis.
- To emphasize the role of tissue microarrays in advancing cancer research and diagnosis.
Main Methods:
- Tissue microarray (TMA) technology is presented as a solution to traditional tissue analysis bottlenecks.
- TMA enables parallel analysis of numerous tissue samples.
- This facilitates comprehensive molecular profiling and biomarker discovery.
Main Results:
- TMA technology allows for efficient and cost-effective validation of molecular markers.
- It supports the identification of genes and proteins with significant impact on disease progression.
- Facilitates the transition from lead discovery to therapeutic applications.
Conclusions:
- Tissue microarray technology is essential for validating findings from high-throughput molecular studies.
- It accelerates cancer research and improves diagnostic capabilities.
- TMA bridges the gap between molecular discovery and clinical application.
