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Tissue microarray analysis of neuroendocrine differentiation and its prognostic significance in breast cancer
Authors:Makretsov Nikita  Gilks C Blake  Coldman Andrew J  Hayes Malcolm  Huntsman David
Institution:Genetic Pathology Evaluatoin Centre of the Department of Pathology, Vancouver General Hospital, British Columbia, Canada.
Abstract:The aim of this study was to detect neuroendocrine differentiation (NE), to determine its association with major clinicopathological parameters of breast cancer, and to study the prognostic significance of NE differentiation in a group of breast carcinomas by using tissue microarray (TMA) methodology. NE differentiation was studied by using 3 markers, synaptophysin (Syn), chromogranin A (ChA), and neuron-specific enolase (NSE) in a group of 334 patients with breast carcinoma. TMA blocks were made by using duplicate 0.6-mm-diameter tissue cores from each paraffin block. Results of immunostaining were scored on a 4-point scale, that is, as negative, weak, intermediate, and strong immunoreactivity. Positive staining of breast cancers for any of the 3 NE markers was detected in 19.5% of cases. Expression of a single marker was present in 16.2% of cases, and expression of 2 or 3 markers in combination was detected in 3.3% of cases. There was no statistically significant correlation of NE phenotype with tumor morphology, except mucinous carcinoma (3 of 6 cases positive), estrogen receptor, progesterone receptor, or nodal status. A weak correlation was noted between synaptophysin staining and higher tumor grade (P = 0.029). Analysis of disease-specific and overall survival based on up to 20 years of follow-up data showed a correlation between NSE expression and improved disease-specific (P = 0.043) and overall survival (P = 0.03) in univariate but not in multivariate analysis. The expression of Syn and ChA, as well as coexpression of multiple NE markers, had no prognostic significance.
Keywords:breast carcinoma  neuroendocrine differentiation  tissue microarray  immunohistochemistry  clustering analysis
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