Abstract and Introduction
The use of tissue microarrays (TMAs) in the preclinical and translational research settings has become ubiquitous as they allow for high-throughput in situ biomarker analysis of hundreds of patient samples, with time and cost efficiency. Coupled with advanced imaging and image-analysis technologies that allow for objective and standardized biomarker expression assessment, TMAs have become critical tools for the development and validation of clinically meaningful biomarker diagnostic assays. However, their diagnostic use in the clinical laboratory setting is limited due to the need for conventional whole-section tissue assessment used for routine diagnostic purposes. In this article, after reviewing TMA basics and their translational and clinical research applications, we will focus on the use of TMAs for robust assay development and quality control in the clinical laboratory setting, as well as provide insights into how TMAs may serve well in the clinical setting as assay performance and quantification controls.
Tissue microarrays (TMAs) have become a mainstay in preclinical and translational research, especially for the development of biomarker assays for characterization of disease. They allow for analysis of extremely small amounts of tissue, thus preserving valuable tissue blocks. At the same time, they dramatically increase the efficiency and cost–effectiveness of performing tissue-based studies[1,2] by enabling the examination of 10s to 100s of different patient samples on the same slide. This approach also leads to greater reproducibility and comparability of patient samples since all samples are exposed to identical processing conditions. By linking patient sample data to pathological and clinical data, including disease follow-up and treatment response, TMAs have expanded translational research, enabling large-scale biomarker and disease progression studies, leading to more informed and improved clinical hypotheses. Coupling TMAs with high-throughput and objective biomarker expression analysis with robust imaging technologies has led to further improvement in biomarker data that will ensure the continued use of TMAs, especially in the translational setting.
Personalized Medicine. 2013;10(5):441-451. © 2013 Future Medicine Ltd.