Software tools for high-throughput analysis and archiving of immunohistochemistry staining data obtained with tissue microarrays

Am J Pathol. 2002 Nov;161(5):1557-65. doi: 10.1016/S0002-9440(10)64434-3.

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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Cluster Analysis
  • Data Interpretation, Statistical
  • Humans
  • Immunohistochemistry / methods*
  • Information Storage and Retrieval
  • Internet
  • Neoplasm Proteins / immunology
  • Neoplasm Proteins / metabolism
  • Neoplasms / classification
  • Neoplasms / metabolism*
  • Software*

Substances

  • Neoplasm Proteins