Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a...

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.