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韩国人群胰腺高级别神经内分泌肿瘤:一项多中心研究。

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

机构信息

Department of Pathology, Seoul National University Hospital, Seoul, Korea.

Department of Pathology, Seoul National University College of Medicine, Seoul, Korea.

出版信息

Cancer Res Treat. 2020 Jan;52(1):263-276. doi: 10.4143/crt.2019.192. Epub 2019 Jul 12.

Abstract

PURPOSE

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 Pan- NETs 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.

摘要

目的

最近的 2017 年世界卫生组织(WHO)胰腺神经内分泌肿瘤(PanNENs)分类通过将 3 级胰腺神经内分泌肿瘤(G3 PanNETs)与低分化胰腺神经内分泌癌(PanNECs)分开,对 2010 年的三层次方案进行了细化。然而,在临床实践中区分 G3 PanNETs 和 PanNECs 具有一定难度。

材料与方法

从 16 个机构收集了 82 例手术切除的 PanNENs,并根据 2017 年 WHO 分类,基于组织学特征和增殖指数(有丝分裂和 Ki-67)进行重新分类。对 15 例高级别 PanNENs 进行了 ATRX、DAXX、视网膜母细胞瘤、p53、Smad4、p16 和 MUC1 的免疫组织化学染色。

结果

重新分类后,20 例为 G1 PanNETs(24%)、47 例为 G2 PanNETs(57%)、8 例为 G3 分化良好的 PanNETs(10%)和 7 例低分化 PanNECs(9%)。与 PanNETs 相比,PanNECs 更常出现弥漫性核异型性、实性生长模式和凋亡,较少出现器官样生长和规则的血管模式,并且缺乏低级别 PanNET 成分。Ki-67 指数在 PanNEC(58.2%±15.1%)中显著高于 G3 PanNET(22.6%±6.1%,p<0.001)。任何两种 p53、p16、MUC1 和 Smad4 的异常表达都可以以 100%的特异性和 87.5%的灵敏度将 PanNECs 与 G3 PanNETs 区分开来。

结论

支持 PanNECs 诊断而非 G3 PanNETs 的组织学特征是肿瘤中缺乏低级别 PanNET 成分、弥漫性明显核异型性、实性生长模式、频繁凋亡以及 Ki-67 标记均匀的高增殖活性。在组织学不明确的情况下,p53、p16、MUC1 和 Smad4 的免疫组织化学染色可能有助于将 PanNECs 与 G3 PanNETs 区分开来,尤其是在仅获得小活检组织的诊断实践中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bac9/6962471/4dfcbf2b9748/crt-2019-192f1.jpg

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