136IN - How to Quantify Immuohistochemical Slides

Abstract

ABSTRACT The quantitative interpretation of immunohistochemistry (IHC) is typically performed by a subjective evaluation based either on binary positive-negative or semi-quantitative assessments using intensity and percentage of positive cells. A typical example is the evaluation of HER2 expression in breast cancer, which considers also a third variable, i.e. the pattern of membrane staining. All these approaches do not provide true evaluation of the quantity of protein expression and are poorly reproducible. Assays for true protein quantification based on protein extraction, such as enzyme-linked immunosorbent assay, carry as a major drawback the loss of tissue morphology, therefore the protein expression heterogeneity cannot be evaluated. Computer-based automated analyses on classical IHC staining help eliminate the variability of pathologist-based scoring, but do not perform well in terms of quantification and are often time consuming. Some have explored the use of an automated scoring system to assess biomarker expression in tissue sections called the automated quantitative analysis (AQUA) system. This system exploits the pixel-based locale assignment for compartmentalization of expression and utilizes fluorescent tags to distinguish tumor cells from stroma, as well as to define subcellular compartments. The output variable (AQUA score) is a ‘‘pixel intensity/pixel area’’ value ranging from 0 to 255, based on the average intensity for all pixels evaluated, therefore the result is a quantitative score of immunofluorescence intensity for the tumor. It has been shown that AQUA scores are directly proportional to in situ protein concentrations. As an alternative, a technique with a high potential for better definition of protein expression is the Proximity Ligation Assay (PLA). PLA can detect single protein events such as protein protein interactions (e.g. protein dimerization) and modifications (e.g. protein phosphorylation) in tissue and cell samples prepared for microscopy. Each detected signal is visualized as an individual fluorescent dot, these signals can be quantified (counted) and assigned to a specific subcellular location based on microscopy images. Disclosure: All authors have declared no conflicts of interest.