Synaptophysin, CD117, and GATA3 as a Diagnostic Immunohistochemical Panel for Small Cell Neuroendocrine Carcinoma of the Urinary Tract.

Abstract

Simple SummaryWhile diagnosing a case of small cell neuroendocrine carcinoma (SCNEC) in the urinary tract, we found that the previous biopsy had been misdiagnosed as urothelial carcinoma (UC) because only chromogranin and synaptophysin were tested to define neuroendocrine differentiation and both tests were negative. This case led us to conduct this present study to define a panel of neuroendocrine markers to ensure the diagnosis of traditional neuroendocrine marker-negative SCNEC. We employed a decision tree classifier algorithm to analyze the expression of 17 immunohistochemical markers and found that the extent of synaptophysin (>5%) and CD117 (>20%) and the intensity of GATA3 (negative or weak) are major parameters. Since SCNEC is an aggressive tumor type and requires therapeutic approaches that differ from those used for UC, an accurate diagnosis of SCNEC is critical and this model may help pathologists accurately diagnose SCNEC in daily practice.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. To establish an 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. An external cohort of eight cases and transmission electron microscopy (TEM) were used to validate the model. 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. The decision tree model using synaptophysin, CD117, and GATA3 may help confirm NED of traditional marker-negative SCNEC.