Abstract
The creation of tissue microarrays (TMAs) allows for the rapid immunohistochemical analysis of thousands of tissue samples, with numerous different antibodies per sample. This technical development has created a need for tools to aid in the analysis and archival storage of the large amounts of data generated. We have developed a comprehensive system for high-throughput analysis and storage of TMA immunostaining data, using a combination of commercially available systems and novel software applications developed in our laboratory specifically for this purpose. Staining results are recorded directly into an Excel worksheet and are reformatted by a novel program (TMA-Deconvoluter) into a format suitable for hierarchical clustering analysis or other statistical analysis. Hierarchical clustering analysis is a powerful means of assessing relatedness within groups of tumors, based on their immunostaining with a panel of antibodies. Other analyses, such as generation of survival curves, construction of Cox regression models, or assessment of intra- or interobserver variation, can also be done readily on the reformatted data. Finally, the immunoprofile of a specific case can be rapidly retrieved from the archives and reviewed through the use of Stainfinder, a novel web-based program that creates a direct link between the clustered data and a digital image database. An on-line demonstration of this system is available at http://genome-www.stanford.edu/TMA/explore.shtml.
MeSH Terms
Cluster Analysis
Data Interpretation, Statistical
Humans
Immunohistochemistry/methods
Information Storage and Retrieval
Internet
Neoplasm Proteins/immunology,metabolism
Neoplasms/classification,metabolism
Software
Chemicals
Neoplasm Proteins
Authors & Affiliations
7 authors, click to expand affiliations / ORCID
Liu Chih Long
Department of Biochemistry, Stanford University Medical Center, California 94305, USA.
Prapong Wijan
Natkunam Yasodha
Alizadeh Ash
Montgomery Kelli
Gilks C Blake
van de Rijn Matt
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