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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao PROTEOMICSarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
PROTEOMICS
Article . 2009 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
PROTEOMICS
Article . 2009
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Requirements for the valid quantification of immunostains on tissue microarray materials using image analysis

Authors: Decaestecker, Christine; Moles Lopez, Xavier; D'Haene, Nicky; Roland, Isabelle; Guendouz, Saad; Duponchelle, Christophe; Berton, Alix; +2 Authors

Requirements for the valid quantification of immunostains on tissue microarray materials using image analysis

Abstract

AbstractAntibody‐based proteomics applied to tissue microarray (TMA) technology provides a very efficient means of visualizing and locating antigen expression in large collections of normal and pathological tissue samples. To characterize antigen expression on TMAs, the use of image analysis methods avoids the effects of human subjectivity evidenced in manual microscopical analysis. Thus, these methods have the potential to significantly enhance both precision and reproducibility. Although some commercial systems include tools for the quantitative evaluation of immunohistochemistry‐stained images, there exists no clear agreement on best practices to allow for correct and reproducible quantification results. Our study focuses on practical aspects regarding (i) image acquisition (ii) segmentation of staining and counterstaining areas and (iii) extraction of quantitative features. We illustrate our findings using a commercial system to quantify different immunohistochemistry markers targeting proteins with different expression patterns (cytoplasmic, nuclear or membranous) in colon cancer or brain tumor TMAs. Our investigations led us to identify several steps that we consider essential for standardizing computer‐assisted immunostaining quantification experiments. In addition, we propose a data normalization process based on reference materials to be able to compare measurements between studies involving different TMAs. In conclusion, we recommend certain critical prerequisites that commercial or in‐house systems should satisfy in order to permit valid immunostaining quantification.

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Keywords

Proteomics, Technology, Image Processing, CD8 Antigens, Galectin 3, Computer-Assisted -- methods, Sciences de l'ingénieur, Colonic Neoplasms -- pathology, Proteomics -- methods, Antibody proteomics, Biological Markers -- metabolism, Ki-67 Antigen -- metabolism, Image analysis, Tissue microarray, CD8 -- metabolism, Quantification, Image Interpretation, Computer-Assisted, Colonic Neoplasms -- metabolism, Image Processing, Computer-Assisted, Galectin 3 -- metabolism, Humans, Antigens, Tissue Array Analysis -- methods, Image Interpretation, Reproducibility of Results, Sciences bio-médicales et agricoles, Immunohistochemistry -- methods, Immunohistochemistry, Ki-67 Antigen, Tissue Array Analysis, Colonic Neoplasms, Biomarkers

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
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