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Digital Quantification of Epidermal Protein Expression in Paraffin-Embedded Tissue Using Immunohistochemistry.

Abstract

Current methods of assessing immunohistochemistry center on semiquantitative visual grading scales. More objective methods utilizing digital quantification offer superior precision and, presumably, higher confidence with image comparison. However, their cost often remains prohibitive, and there is little customizability to separate subsections of interest in the tissue. Here we describe a method using two open-source software programs to analyze the intensity and density of signals in immunohistochemistry-stained tissue sections that account for tissue heterogeneity and allow for direct comparison between two samples. This method allows for quantitative assessment of epidermal protein expression. We herein demonstrate this workflow using an epidermal stain tothymic stromal lymphopoietin.

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  • Authors+Show Affiliations

    ,

    Department of Dermatology, University of California Irvine, Irvine, CA, USA.

    ,

    Department of Dermatology, University of Illinois at Chicago, Chicago, IL, USA.

    ,

    Department of Dermatology, University of Illinois at Chicago, Chicago, IL, USA.

    ,

    Department of Dermatology, University of California Irvine, Irvine, CA, USA.

    ,

    Department of Pathology, University of California Irvine, Irvine, CA, USA.

    Department of Dermatology, University of Illinois at Chicago, Chicago, IL, USA. ktamber@uic.edu.

    Source

    Pub Type(s)

    Journal Article

    Language

    eng

    PubMed ID

    31190272

    Citation

    Valdebran, Manuel, et al. "Digital Quantification of Epidermal Protein Expression in Paraffin-Embedded Tissue Using Immunohistochemistry." Methods in Molecular Biology (Clifton, N.J.), 2019.
    Valdebran M, Kowalski EH, Kneiber D, et al. Digital Quantification of Epidermal Protein Expression in Paraffin-Embedded Tissue Using Immunohistochemistry. Methods Mol Biol. 2019.
    Valdebran, M., Kowalski, E. H., Kneiber, D., Li, J., Kim, J., & Amber, K. T. (2019). Digital Quantification of Epidermal Protein Expression in Paraffin-Embedded Tissue Using Immunohistochemistry. Methods in Molecular Biology (Clifton, N.J.), doi:10.1007/7651_2019_244.
    Valdebran M, et al. Digital Quantification of Epidermal Protein Expression in Paraffin-Embedded Tissue Using Immunohistochemistry. Methods Mol Biol. 2019 Jun 14; PubMed PMID: 31190272.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Digital Quantification of Epidermal Protein Expression in Paraffin-Embedded Tissue Using Immunohistochemistry. AU - Valdebran,Manuel, AU - Kowalski,Eric H, AU - Kneiber,Diana, AU - Li,Jing, AU - Kim,Jeffrey, AU - Amber,Kyle T, Y1 - 2019/06/14/ PY - 2019/6/14/entrez PY - 2019/6/14/pubmed PY - 2019/6/14/medline KW - Colorimetric analysis KW - Epidermis KW - GIMP KW - ImageJ KW - Protein expression KW - Quantitative immunohistochemistry JF - Methods in molecular biology (Clifton, N.J.) JO - Methods Mol. Biol. N2 - Current methods of assessing immunohistochemistry center on semiquantitative visual grading scales. More objective methods utilizing digital quantification offer superior precision and, presumably, higher confidence with image comparison. However, their cost often remains prohibitive, and there is little customizability to separate subsections of interest in the tissue. Here we describe a method using two open-source software programs to analyze the intensity and density of signals in immunohistochemistry-stained tissue sections that account for tissue heterogeneity and allow for direct comparison between two samples. This method allows for quantitative assessment of epidermal protein expression. We herein demonstrate this workflow using an epidermal stain tothymic stromal lymphopoietin. SN - 1940-6029 UR - https://www.unboundmedicine.com/medline/citation/31190272/Digital_Quantification_of_Epidermal_Protein_Expression_in_Paraffin-Embedded_Tissue_Using_Immunohistochemistry L2 - https://dx.doi.org/10.1007/7651_2019_244 DB - PRIME DP - Unbound Medicine ER -