[1998] Quantitative Evaluation of ER alpha Expression in Breast Cancer Using DAB Based Immunohistochemistry Versus Quantitative Immunofluorescence

Veronique M Neumeister, Elizabeth Zarrella, Madeline Coulter, Kurt Schalper, Daniel Carvajal, David G Hicks, David L Rimm. Yale University School of Medicine, New Haven, CT; University of Rochester, School of Medicine, Rochester, NY

Background: An accurate, sensitive, reproducible and reader independent method to measure ER expression is important for predicting outcome and guiding treatment options for patients. Here we compare quantification of DAB based immunohistochemistry with quantitative immunofluorescence (QIF) for assessment of ER alpha.
Design: Three different breast cancer cohorts consisting of 640, 93,and 235 patients, represented on tissue micro arrays (TMAs) were used for comparison of the two methods of ER quantification. Serial sections were stained for ER alpha. Staining procedures were optimized, standardized and automated. DAB/IHC staining was objectively quantified using the Aperio Image Analysis system. Tumor areas were annotated and 3 different algorithms were applied: the positive pixel count algorithm, the FDA cleared nuclear algorithm and a DAB concentration scoring algorithm, which assesses DAB concentration within a defined area. The algorithms were optimized according to Hematoxylin staining. Two pathologists performed semiquantitative scoring on the cohort of 235 patients. The serial sections stained with immunofluorescence were quantified using the Automated Quantitative Analysis (AQUA) method. Pixel intensity of ER expression is measured within the tumor area, defined by cytokeratin positivity. AQUA scores are calculated as ER intensity per tumor area.
Results: On the 3 cohorts the quantification of DAB based ER staining correlates with QIF as assessed by linear regression (r2 values between 0.5 and 0.85) with positive pixel count performing best. The nuclear algorithm and the DAB concentration scoring reveal the same limited dynamic range compared to QIF. The dynamic range (defined as the largest possible signal divided by lowest possible signal) is about 3 times larger for QIF than for DAB quantification. Based on the intensity of Hematoxylin staining several cases are misclassified and scored as false positive. In contrast, some cases showing low ER expression by QIF are negative by DAB methods, suggesting false negative results.
Conclusions: QIF of ER alpha outperforms quantification of DAB based IHC when using pathologist based scores as the criterion standard. QIF also shows broader dynamic range. With increasing demands for personalized medicine and tailoring therapy according to changes of biomarker expression, accuracy, objectivity, reproducibility and dynamic range are important considerations in assay selection.
Category: Quality Assurance

Tuesday, March 5, 2013 9:30 AM

Poster Session III # 275, Tuesday Morning


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