ArticleCancers2022
Synaptophysin, CD117, and GATA3 as a Diagnostic Immunohistochemical Panel for Small Cell Neuroendocrine Carcinoma of the Urinary Tract.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 citations in OpenAlex.
- Case Report: Clinicopathological features of bladder neuroendocrine neoplasm: a retrospective case series of nine cases and literature review.Frontiers in oncology · 2026Article
- Molecular and immune characteristics of neuroendocrine bladder carcinoma - Implications for diagnosis, prognosis, and therapy: A review.Biomolecules & biomedicine · 2025Review
- Unlocking Precise Lung Cancer Detection Through Minimal Panel Immunostaining in Small Biopsy Samples.Cureus · 2024Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
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.
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Registered trials
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