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

  • Manuel Valdebran
  • Eric H. Kowalski
  • Diana Kneiber
  • Jing Li
  • Jeffrey Kim
  • Kyle T. AmberEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 2109)


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 to

thymic stromal lymphopoietin.


Colorimetric analysis Epidermis GIMP ImageJ Protein expression Quantitative immunohistochemistry 



This work was supported in part by the International Pemphigus and Pemphigoid Foundation (Identifying novel pharmacologic targets in bullous pemphigoid: Unraveling the mechanisms of eosinophils) and a departmental grant from the University of California Irvine Department of Dermatology both to KTA.


  1. 1.
    Hsu SM, Raine L, Fanger H (1981) Use of avidin-biotin-peroxidase complex (ABC) in immunoperoxidase techniques: a comparison between ABC and unlabeled antibody (PAP) procedures. J Histochem Cytochem 29(4):577–580CrossRefGoogle Scholar
  2. 2.
    Rizzardi AE, Johnson AT, Vogel RI, Pambuccian SE, Henriksen J, Skubitz AP et al (2012) Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring. Diagn Pathol 7:42CrossRefGoogle Scholar
  3. 3.
    Araki Y, Mizoguchi M, Yoshimoto K, Shono T, Amano T, Nakamizo A et al (2011) Quantitative digital assessment of MGMT immunohistochemical expression in glioblastoma tissue. Brain Tumor Pathol 28(1):25–31CrossRefGoogle Scholar
  4. 4.
    Berger AJ, Camp RL, Divito KA, Kluger HM, Halaban R, Rimm DL (2004) Automated quantitative analysis of HDM2 expression in malignant melanoma shows association with early-stage disease and improved outcome. Cancer Res 64(23):8767–8772CrossRefGoogle Scholar
  5. 5.
    Amber KT (2015) Considerations for the utilization of ‘comparative analysis of colorimetric staining in skin using open-source software’ in an experimental setting. Exp Dermatol 24(9):717–718CrossRefGoogle Scholar
  6. 6.
    Billings PC, Sanzari JK, Kennedy AR, Cengel KA, Seykora JT (2015) Comparative analysis of colorimetric staining in skin using open-source software. Exp Dermatol 24(2):157–159CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2019

Authors and Affiliations

  • Manuel Valdebran
    • 1
  • Eric H. Kowalski
    • 2
  • Diana Kneiber
    • 2
  • Jing Li
    • 1
  • Jeffrey Kim
    • 3
  • Kyle T. Amber
    • 2
    Email author
  1. 1.Department of DermatologyUniversity of California IrvineIrvineUSA
  2. 2.Department of DermatologyUniversity of Illinois at ChicagoChicagoUSA
  3. 3.Department of PathologyUniversity of California IrvineIrvineUSA

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