Synaptophysin 및 CD117, GATA3를 이용한 요로의 소세포신경내분비암종의 면역조직화학진단 패널에 관한 연구

Abstract

Background Small cell neuroendocrine carcinoma (SCNEC) of the urinary tract is a highly aggressive tumor and requires therapeutic approaches that differ from those used for urothelial carcinoma (UC). Although SCNEC is based on its characteristic histology, immunohistochemistry (IHC) is commonly employed to confirm neuroendocrine differentiation (NED). The challenge here is that SCNEC may yield negative results for traditional neuroendocrine markers. Methods The definition of NED was based on histologic features only or IHC expression analysis of neuronal markers. To establish a diagnostic IHC panel for NED, 17 neuronal, basal, and luminal markers were examined on a tissue microarray construct generated from 47 cases of 34 patients with SCNEC as a discovery cohort. A decision tree algorithm was employed to analyze the extent and intensity of immunoreactivity and to develop a diagnostic model. Transmission electron microscopy (TEM) was used to confirm the NED and external cohort of eight cases was used to validate the model. Results Among the 17 markers, the decision tree diagnostic model selected 3 markers to classify NED with 98.4% accuracy in classification. The extent of synaptophysin (>5%) was selected as the initial parameter, the extent of CD117 (>20%) as the second, and then the intensity of GATA3 (≤1.5, negative or weak immunoreactivity) as the third for NED. The importance of each variable was 0.758, 0.213, and 0.029, respectively. The model was validated by the TEM and using the external cohort. Conclusions Our study demonstrated that the decision tree model using synaptophysin, CD117, and GATA3 may help confirm NED of not only NE marker-positive SCNEC but also traditional marker-negative SCNEC.