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Immunophenotype analysis using CLDN18, CDH17, and PAX8 for the subcategorization of endocervical adenocarcinomas in situ: gastric-type, intestinal-type, gastrointestinal-type, and Müllerian-type.

. 2020 Apr;476(4):499-510. Epub 2020 Jan 13
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摘要


A classification system for invasive endocervical adenocarcinoma (ECA) focusing on high-risk human papillomavirus (HPV) detection has been recently developed. However, precursor lesions of each ECA subtype and immunohistochemical markers that effectively subcategorize ECAs with gastric and intestinal differentiation have not been fully described. Here, we aimed to subcategorize endocervical adenocarcinoma in situ (AIS) by immunophenotype and to characterize the histopathology of each AIS subtype. We immunohistochemically analyzed 36 AIS and 25 lobular endocervical glandular hyperplasia (LEGH) samples using three cell lineage-specific markers (CLDN18, gastric epithelial cells; CDH17, intestinal epithelial cells; and PAX8, Müllerian epithelial cells). The AISs were immunophenotypically classified as gastric-type (G-AIS; n = 2), intestinal-type (I-AIS; n = 10), gastrointestinal-type (GI-AIS; n = 3), Müllerian-type (M-AIS; n = 18), and AIS, not otherwise specified (AIS-NOS; n = 3). All 25 LEGHs were categorized as gastric-type. G-AIS had pale eosinophilic or clear cytoplasm with a small amount of apical mucin and fewer mitotic bodies. I-AIS comprised various numbers of goblet cell-type tumor cells. GI-AIS showed intermediate or mixed features of G-AIS and I-AIS. M-AIS, as with the usual-type ECA, was typically characterized by mucin depletion; however, several lesions had abundant cytoplasmic mucin. High-risk HPV was detected in most AISs but was negative in 100% (2/2) of G-AIS, 10% (1/10) of I-AIS, and 6% (1/18) of M-AIS lesions. In summary, the AIS subtypes defined by immunophenotype had distinct histopathological and etiological characteristics. Thus, immunophenotyping with CLDN18, CDH17, and PAX8 might improve the diagnostic accuracy of histopathological classifications of ECAs.

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原始数据


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