Abstract
The recent development of tissue microarrays—composed of hundreds of tissue sections from different tumors arrayed on a single glass slide—facilitates rapid evaluation of large-scale outcome studies. Realization of this potential depends on the ability to rapidly and precisely quantify the protein expression within each tissue spot. We have developed a set of algorithms that allow the rapid, automated, continuous and quantitative analysis of tissue microarrays, including the separation of tumor from stromal elements and the sub-cellular localization of signals. Validation studies using estrogen receptor in breast carcinoma show that automated analysis matches or exceeds the results of conventional pathologist-based scoring. Automated analysis and sub-cellular localization of beta-catenin in colon cancer identifies two novel, prognostically significant tumor subsets, not detected by traditional pathologist-based scoring. Development of automated analysis technology empowers tissue microarrays for use in discovery-type experiments (more typical of cDNA microarrays), with the added advantage of inclusion of long-term demographic and patient outcome information.
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Acknowledgements
We thank T. D'Aquila, M. Helie, L. Charette, D. Fischer, E. Rimm and P. Lizardi for their help in this effort; and J. Costa, V. Marchesi, A. Reynolds, R. Levenson and E. Fearon for review of the manuscript. This work was supported by grants from the Patrick and Catherine Weldon Donaghue Foundation for Medical Research and grants from the NIH including: K0-8 ES11571, NIEHS (to R.L.C.), RO-1 GM57604 NCI (to D.L.R.) and US Army DAMD grant 01-000436.
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R.L.C. and D.L.R. are involved in a Yale-based effort to commercialize the AQUA technology though a company called Histometrix.
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Camp, R., Chung, G. & Rimm, D. Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat Med 8, 1323–1328 (2002). https://doi.org/10.1038/nm791
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DOI: https://doi.org/10.1038/nm791
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