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Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
Published on: April 8, 2016
From the protein to the graph: how to quantify immunohistochemistry staining of the skin using digital imaging
Georgios Kokolakis1, Lambros Panagis, Efstathios Stathopoulos
1Department of Dermatology, University of Crete, GR-71110 Heraklion, Greece.
Insights
Digital image analysis accurately quantifies protein expression in psoriatic skin. This method reveals significant changes in p53 and bcl-2 levels after anti-tumor necrosis factor-alpha therapy.
Area of Science:
- Dermatology
- Pathology
- Biomedical Imaging
Background:
- Quantitative immunohistochemistry is crucial for assessing cellular protein expression in tissues.
- Skin's complex structure presents challenges for automated image analysis.
- Psoriatic skin models offer a relevant system for studying treatment effects.
Purpose of the Study:
- To compare p53 and bcl-2 expression in psoriatic skin before and after anti-tumor necrosis factor-alpha treatment.
- To evaluate the efficacy of digital image analysis for quantifying protein expression in skin.
- To establish a reproducible and unbiased method for assessing cellular protein levels in challenging tissues.
Main Methods:
- Utilized a psoriatic skin model for comparative analysis.
- Employed digital image analysis with Scion image software to quantify protein expression.
- Acquired digital photomicrographs for detailed assessment.
- Performed statistical analysis using ANOVA to determine significance.
Main Results:
- Demonstrated a significant increase in p53 expression across all epidermal layers post-treatment (p<0.001).
- Observed a significant decrease in bcl-2 expression in all epidermal layers post-treatment (p<0.001).
- Results correlated with conventional histopathological evaluations.
Conclusions:
- Digital image analysis provides an easy, rapid, and reproducible method for quantifying immunohistochemically labeled cells in skin tissue.
- This technique yields unbiased numerical estimations of cell labeling, aiding in treatment assessment.
- The findings support the use of digital image analysis for reliable protein expression assessment in dermatological research.
Abstract:
Quantitative immunohistochemistry is needed in order to reliably and accurately assess the expression of cellular proteins in tissue. Skin is a difficult tissue for automated image analysis due to its heterogeneous composition and its architecture. In the present study we used a psoriatic skin model to compare the expression of p53 and bcl-2 before and after treatment with anti-tumor necrosis factor-alpha using digital image analysis. Digital photomicrographs were acquired and analyzed with Scion image software in order to obtain the fraction of p53 and bcl-2 immunoreactive cells' area out of the total area investigated. Statistical analysis with ANOVA revealed a significant increase of p53 expression and a decrease of bcl-2 expression in all 3 epidermal layers during the course of therapy (p<0.001). The results were in line with the conventional histopathological evaluation using an arbitrary scale to grade the extent and intensity of the staining. So, the estimation of volume fraction of immunohistochemically labelled cells in skin tissue can be performed easily and rapidly using commonly available image analysis software and provides reproducible and unbiased numerical estimations of the amount of cell labelling.
