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Per Med. 2005 Nov;2(4):291-300. doi: 10.2217/17410541.2.4.291.

Quantitative in situ cancer proteomics: molecular pathology comes of age with automated tissue microarray analysis.

Author information

1
HistoRx, Inc., 300 George St.New Haven, CT 06511, USA. mdolled-filhart@historx.com; pstroobant@historx.com www.historx.com.
2
Yale University, School of Medicine, Department of Pathology, Brady Memorial Laboratory, Room 165, 310 Cedar St., PO Box 208023 New Haven, CT 06520-8023, USA. david.rimm@yale.edu.

Abstract

Tissue microarrays provide a high-throughput method for assessing a large number of samples by incorporating small cores of tissue into an array that can fit onto one microscope slide. Analyses of tissue microarrays were previously limited by semiquantitative protein expression analysis using brown stain (chromagen-based) methods. These methods are imperfect for protein expression analyses because of a smaller dynamic range and decreased ability for multiplexing many markers, as compared with objective in situ quantitation of protein expression in tumor samples with fluorescence microscopy by a new technology called Automated Quantitative Analysis (AQUA™). By using AQUA analysis, tissue microarrays can serve a unique role as both a discovery tool and as a validation tool for nucleic-acid expression profiling-based target discoveries with results equivalent to enzyme-linked immunosorbent assay quantitation. The identification of novel prognostic markers can identify subsets of patients at high or low risk upon diagnosis, as well as new targets for potential future therapeutic development or metastatic disease treatment decisions. Thus, AQUA provides an unparalleled opportunity to advance personalized medicine through its ability to multiplex, quantitate and localize in situ protein expression.

KEYWORDS:

automated microscopy; cancer; cancer proteomics; high-throughput; molecular diagnostics; quantitative immunofluorescence; quantitative immunohistochemistry; quantitative pathology; tissue microarrays; tumor biomarkers

PMID:
29788575
DOI:
10.2217/17410541.2.4.291

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