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Pancreatic High-Grade Neuroendocrine Neoplasms in the Korean Population: A Multicenter Study

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dc.contributor.authorKim, Haeryoung-
dc.contributor.authorAn, Soyeon-
dc.contributor.authorLee, Kyoungbun-
dc.contributor.authorAhn, Sangjeong-
dc.contributor.authorPark, Youn-
dc.contributor.authorKim, Jo-Heon-
dc.contributor.authorKang, Dong-Wook-
dc.contributor.authorKim, Min-Ju-
dc.contributor.authorChang, Mee Soo-
dc.contributor.authorJung, Eun Sun-
dc.contributor.authorKim, Joon Mee-
dc.contributor.authorChoi, Yoon Jung-
dc.contributor.authorJin, So-Young-
dc.contributor.authorChang, Hee Kyung-
dc.contributor.authorCho, Mee-Yon-
dc.contributor.authorKang, Yun Kyung-
dc.contributor.authorKang, Myunghee-
dc.contributor.authorAhn, Soomin-
dc.contributor.authorKim, Youn Wha-
dc.contributor.authorHong, Seung-Mo-
dc.date.available2020-03-03T06:43:32Z-
dc.date.created2020-02-24-
dc.date.issued2020-01-
dc.identifier.issn1598-2998-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17663-
dc.description.abstractPurpose The most recent 2017 World Health Organization (WHO) classification of pancreatic neuroendocrine neoplasms (PanNENs) has refined the three-tiered 2010 scheme by separating grade 3 pancreatic neuroendocrine tumors (G3 PanNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PanNECs). However, differentiating between G3 PanNETs and PanNECs is difficult in clinical practice. Materials and Methods Eighty-two surgically resected PanNENs were collected from 16 institutions and reclassified according to the 2017 WHO classification based on the histological features and proliferation index (mitosis and Ki-67). Immunohistochemical stains for ATRX, DAXX, retinoblastoma, p53, Smad4, p16, and MUC1 were performed for 15 high-grade PanNENs. Results Re-classification resulted in 20 G1 PanNETs (24%), 47 G2 PanNETs (57%), eight G3 well-differentiated PanNETs (10%), and seven poorly differentiated PanNECs (9%). PanNECs showed more frequent diffuse nuclear atypia, solid growth patterns and apoptosis, less frequent organoid growth and regular vascular patterns, and absence of low-grade PanNET components than PanNETs. The Ki-67 index was significantly higher in PanNEC (58.2%+/- 15.1%) compared to G3 PanNET (22.6%+/- 6.1%, p < 0.001). Abnormal expression of any two of p53, p16, MUC1, and Smad4 could discriminate PanNECs from G3 PanNETs with 100% specificity and 87.5% sensitivity. Conclusion Histological features supporting the diagnosis of PanNECs over G3 PanNETs were the absence of a low-grade PanNET component in the tumor, the presence of diffuse marked nuclear atypia, solid growth pattern, frequent apoptosis and markedly increased proliferative activity with homogeneous Ki-67 labeling. Immunohistochemical stains for p53, p16, MUC1, and Smad4 may be helpful in distinguishing PanNECs from G3 PanNETs in histologically ambiguous cases, especially in diagnostic practice when only small biopsied tissues are available.-
dc.language영어-
dc.language.isoen-
dc.publisherKOREAN CANCER ASSOCIATION-
dc.relation.isPartOfCANCER RESEARCH AND TREATMENT-
dc.subjectRECEPTOR EXPRESSION-
dc.subjectDISTINCT-
dc.subjectTUMORS-
dc.titlePancreatic High-Grade Neuroendocrine Neoplasms in the Korean Population: A Multicenter Study-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000507387500023-
dc.identifier.doi10.4143/crt.2019.192-
dc.identifier.bibliographicCitationCANCER RESEARCH AND TREATMENT, v.52, no.1, pp.263 - 276-
dc.identifier.kciidART002549148-
dc.identifier.scopusid2-s2.0-85075754461-
dc.citation.endPage276-
dc.citation.startPage263-
dc.citation.titleCANCER RESEARCH AND TREATMENT-
dc.citation.volume52-
dc.citation.number1-
dc.contributor.affiliatedAuthorKang, Myunghee-
dc.type.docTypeArticle-
dc.subject.keywordAuthorPancreas-
dc.subject.keywordAuthorNeuroendocrine tumors-
dc.subject.keywordAuthorNeuroendocrine carcinoma-
dc.subject.keywordAuthorImmunohistochemistry-
dc.subject.keywordPlusRECEPTOR EXPRESSION-
dc.subject.keywordPlusDISTINCT-
dc.subject.keywordPlusTUMORS-
dc.relation.journalResearchAreaOncology-
dc.relation.journalWebOfScienceCategoryOncology-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
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