Antibody-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 dear 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.
机构:
Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
Univ Brescia, Dept Biomed Sci & Biotechnol, I-25121 Brescia, ItalyKarolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
Calza, Stefano
;
Valentini, Davide
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机构:
Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, SwedenKarolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
Valentini, Davide
;
Pawitan, Yudi
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机构:
Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, SwedenKarolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
机构:
Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
Univ Brescia, Dept Biomed Sci & Biotechnol, I-25121 Brescia, ItalyKarolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
Calza, Stefano
;
Valentini, Davide
论文数: 0引用数: 0
h-index: 0
机构:
Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, SwedenKarolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
Valentini, Davide
;
Pawitan, Yudi
论文数: 0引用数: 0
h-index: 0
机构:
Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, SwedenKarolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden