Validation of Tissue Microarray Technology in Ovarian Cancer: Results from the Nurses' Health Study

Abstract

Tissue microarrays (TMAs) allow high-throughput evaluation of protein expression from archived tissue samples. We identified characteristics specific to ovarian cancer that may influence TMA interpretation. TMAs were constructed using triplicate core samples from 174 epithelial ovarian cancers. Stains for p53, Ki-67, estrogen receptor-alpha, progesterone receptor, Her-2, WT-1, cytokeratin 7, and cytokeratin 20 were evaluated by intraclass correlation coefficients, Spearman correlation coefficients, the effect of sample age, and tumor histology on the ability to score the cores, and inter-rater reliability. The interclass correlation coefficient and the mean Spearman correlation coefficients among 3 cores were > or = 0.91 and 0.87, respectively. Tissue age and tumor histology were not predictive of an inability to evaluate stains, but borderline tumors had a 2 to 4-fold increase in the risk of having uninterpretable cores over invasive tumors. There was moderate to substantial concordance between the two pathologists for estrogen receptor-alpha [Cohen's Kappa (kappa), 0.79] and Ki-67 (kappa, 0.52). The prevalence of positive staining cells by histologic type was comparable with previous studies. TMA is a valid method for evaluating antigen expression in invasive ovarian cancer but should be used with caution for borderline tumors. We suggest several methods of quality control based on intercore comparisons and show that some antigens may be affected by age of the samples.