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Updated: May 14, 2026
Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
Published on: April 8, 2016
Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a
Martin Braun1, Robert Kirsten, Niels J Rupp
1Institute of Pathology, and Department of Prostate Cancer Research, University Hospital of Bonn, Bonn, Germany.
Insights
New image analysis software accurately quantifies protein expression in immunohistochemistry (IHC) staining. This digital approach offers a precise and reproducible alternative to manual scoring, reducing observer variability in translational research and clinical settings.
Area of Science:
- Biomedical imaging
- Pathology
- Translational research
Background:
- Immunohistochemistry (IHC) is crucial for quantifying protein expression in research and clinical settings.
- Manual scoring of IHC is subjective, time-consuming, and prone to significant observer variability.
- Objective and reproducible methods are needed to enhance the reliability of IHC-based protein assessment.
Purpose of the Study:
- To evaluate the efficacy of new image analysis software as an alternative tool for quantifying protein expression in IHC.
- To compare digital quantification results with manual scoring by a pathologist.
- To assess the software's potential to overcome limitations of manual IHC assessment.
Main Methods:
- IHC staining was performed on tissue microarrays (TMAs) from 630 prostate cancer patients using three antibodies: ERG (nuclear), SLC45A3 (cytoplasmic), and TMPRSS2 (nuclear/cytoplasmic).
- Manual quantification was conducted by a pathologist using a four-step scoring system.
- Digital quantification was performed using Tissue Studio v.2.1 image analysis software to obtain average staining intensity.
- Spearman's rank correlation was used to compare manual and digital scores.
Main Results:
- Strong correlations were observed between manual and digital quantification scores for all three antibodies.
- Spearman's rank correlation coefficients were 0.94 for ERG, 0.92 for SLC45A3, and 0.90 for TMPRSS2 (p<0.01).
- The image analysis software provided a continuous spectrum of average staining intensity.
Conclusions:
- The image analysis software Tissue Studio is a powerful and accurate tool for quantifying protein expression in IHC.
- Digital quantification using this software demonstrates high precision and reproducibility.
- Computer-assisted protein quantification can significantly reduce intra- and interobserver variability, increasing objectivity in IHC analysis.
Abstract:
Quantification of protein expression based on immunohistochemistry (IHC) is an important step for translational research and clinical routine. Several manual ('eyeballing') scoring systems are used in order to semi-quantify protein expression based on chromogenic intensities and distribution patterns. However, manual scoring systems are time-consuming and subject to significant intra- and interobserver variability. The aim of our study was to explore, whether new image analysis software proves to be sufficient as an alternative tool to quantify protein expression. For IHC experiments, one nucleus specific marker (i.e., ERG antibody), one cytoplasmic specific marker (i.e., SLC45A3 antibody), and one marker expressed in both compartments (i.e., TMPRSS2 antibody) were chosen. Stainings were applied on TMAs, containing tumor material of 630 prostate cancer patients. A pathologist visually quantified all IHC stainings in a blinded manner, applying a four-step scoring system. For digital quantification, image analysis software (Tissue Studio v.2.1, Definiens AG, Munich, Germany) was applied to obtain a continuous spectrum of average staining intensity. For each of the three antibodies we found a strong correlation of the manual protein expression score and the score of the image analysis software. Spearman's rank correlation coefficient was 0.94, 0.92, and 0.90 for ERG, SLC45A3, and TMPRSS2, respectively (p⟨0.01). Our data suggest that the image analysis software Tissue Studio is a powerful tool for quantification of protein expression in IHC stainings. Further, since the digital analysis is precise and reproducible, computer supported protein quantification might help to overcome intra- and interobserver variability and increase objectivity of IHC based protein assessment.
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