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Hum Pathol. 2008 Oct;39(10):1527-34. doi: 10.1016/j.humpath.2008.03.001. Epub 2008 Jul 11.

Is immunohistochemical epidermal growth factor receptor expression overestimated as a prognostic factor in head-neck squamous cell carcinoma? A retrospective analysis based on a tissue microarray of 365 carcinomas.

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  • 1Department of Otolaryngology, Head and Neck Surgery, University Hospital, 4031 Basel, Switzerland. cfischer@uhbs.ch

Abstract

Epidermal growth factor receptor is overexpressed in more than 80% of head-neck squamous cell carcinoma. Its role as an independent prognostic marker is discussed controversially. No standardized evaluation methods are reported. The aim of our study was to analyze the prognostic relevance of epidermal growth factor receptor expression, using a tissue microarray with more than 300 tumor samples. Epidermal growth factor receptor expression was analyzed by immunohistochemistry and fluorescence in situ hybridization based on a tissue microarray of 365 head-neck squamous cell carcinomas with complete clinicopathologic and follow-up data. Multiple independent observers blinded for clinical data evaluated epidermal growth factor receptor immunostaining semiquantitatively. Cut-off scores for positivity were determined systematically by receiver operating characteristic curve analysis and validated by resampling of the data. Epidermal growth factor receptor expression cut-off scores for loco-regional relapse and overall survival were determined to be 60%. No significant correlation with clinicopathologic data was found. Independent significant differences in loco-regional control and overall survival could not be distinguished by epidermal growth factor receptor expression. Epidermal growth factor receptor expression could not be confirmed as a significant independent prognostic marker in head-neck squamous cell carcinoma using a large tissue microarray with 365 head-neck squamous cell carcinomas with complete clinical data, an evaluation based on immunohistochemistry and fluorescence in situ hybridization by multiple independent observers and systematic determination of cut-off scores.

PMID:
18620726
[PubMed - indexed for MEDLINE]
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