Abstract 3207: Automated quantitative analysis of p53, cyclin D1 and pErk expression in breast carcinoma does not differ from expert pathologist scoring and correlates well with clinico-pathological characteristics
Authors: Jamaica Cass, Sonal Varma, Ashish Rajput, Miao Wang, Andrew Day, Waheed Sangrar, Leda Raptis, Jeremy Squire, Yolanda Madarnas, Sandip SenGupta, Bruce Elliott
Journal: Cancer Research (2011)

Abstract Prognosis and risk assessment of breast cancer patients are currently driven by TNM stage, ER/PR/HER2 expression, tumor grade and lymphovascular invasion (LVI). However there is critical need for improved biomarker assessment platforms to better predict systemic treatment response. One roadblock is the lack of semi-quantitative methods to reliably measure expression, activity and localization of biomarkers in formalin-fixed tumor specimens. The present study assesses reliability of automated IHC scoring compared to manual scoring of routine and non-routine biomarkers (HER2, cyclin D1, p53 and phospho(p)-ERK) on a human breast cancer tissue microarray according to REMARK guidelines, and correlates these markers with clinical-pathological data. Using a triplicate core TMA of formalin-fixed paraffin embedded tissues, we investigated 63 primary invasive breast cancers, for which ER/PR/HER2 status, LVI, grade and recurrence status were recorded. IHC was performed on the TMA for the above biomarkers (pH 6 citrate buffer conditions). Histologic (H) scores (% positive tumor area × staining intensity 0-3) were determined manually by two independent evaluators with resolution of discordant cases by a senior pathologist. Excellent replicability was observed between H scores for each marker compared on replicate slides, as determined by Spearman correlations (0.79-0.82). Each TMA slide was then scanned into the Ariol Imaging System, algorithms were trained for each marker, and H scores were calculated. Pearson correlation coefficients (with data left as continuous) and Kappa statistics (with dichotomized data) were used for inter-method comparisons. Associations between biomarker positivity and clinical data were assessed by Fisher's exact test. Excellent concordance between manual and automated Ariol scores was observed for all four markers based on Kappa statistics (0.667-0.813) and Pearson correlation coefficients (0.790-0.885). Distinct proportions of tumor cases showed any positive staining for membranous HER2 (19/63), nuclear p53 (16/56), cyclin D1 (26/57) and pERK (32/59). A statistically significant association of pERK positivity with absence of LVI (p=0.0025) and lymph node negativity (p=0.0006) was observed. In contrast, pERK positivity was associated with high-grade tumors (p=0.0040), consistent with a role of pERK in poorly differentiated high-grade primary tumors. p53 over-expression, characteristic of dysfunctional p53 in breast cancer, was also associated with high tumor grade (p=0.0074). Thus automated quantitation of immunostaining yields objective results that do not differ from pathologists’ scoring, and provide meaningful associations with clinico-pathological data. (Supported by CIHR, PSI, and Queen's Dept. Pathol. &amp; Mol. Med.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3207. doi:10.1158/1538-7445.AM2011-3207