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一种算法免疫组化方法来定义肿瘤类型并确定起源部位。

An Algorithmic Immunohistochemical Approach to Define Tumor Type and Assign Site of Origin.

机构信息

Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa Carver College of Medicine, Iowa City, IA.

出版信息

Adv Anat Pathol. 2020 May;27(3):114-163. doi: 10.1097/PAP.0000000000000256.

Abstract

Immunohistochemistry represents an indispensable complement to an epidemiology and morphology-driven approach to tumor diagnosis and site of origin assignment. This review reflects the state of my current practice, based on 15-years' experience in Pathology and a deep-dive into the literature, always striving to be better equipped to answer the age old questions, "What is it, and where is it from?" The tables and figures in this manuscript are the ones I "pull up on the computer" when I am teaching at the microscope and turn to myself when I am (frequently) stuck. This field is so exciting because I firmly believe that, through the application of next-generation immunohistochemistry, we can provide better answers than ever before. Specific topics covered in this review include (1) broad tumor classification and associated screening markers; (2) the role of cancer epidemiology in determining pretest probability; (3) broad-spectrum epithelial markers; (4) noncanonical expression of broad tumor class screening markers; (5) a morphologic pattern-based approach to poorly to undifferentiated malignant neoplasms; (6) a morphologic and immunohistochemical approach to define 4 main carcinoma types; (7) CK7/CK20 coordinate expression; (8) added value of semiquantitative immunohistochemical stain assessment; algorithmic immunohistochemical approaches to (9) "garden variety" adenocarcinomas presenting in the liver, (10) large polygonal cell adenocarcinomas, (11) the distinction of primary surface ovarian epithelial tumors with mucinous features from metastasis, (12) tumors presenting at alternative anatomic sites, (13) squamous cell carcinoma versus urothelial carcinoma, and neuroendocrine neoplasms, including (14) the distinction of pheochromocytoma/paraganglioma from well-differentiated neuroendocrine tumor, site of origin assignment in (15) well-differentiated neuroendocrine tumor and (16) poorly differentiated neuroendocrine carcinoma, and (17) the distinction of well-differentiated neuroendocrine tumor G3 from poorly differentiated neuroendocrine carcinoma; it concludes with (18) a discussion of diagnostic considerations in the broad-spectrum keratin/CD45/S-100-"triple-negative" neoplasm.

摘要

免疫组织化学是肿瘤诊断和起源部位鉴定的一种不可或缺的补充方法,它基于流行病学和形态学驱动。本文反映了我目前的实践状态,基于我在病理学领域的 15 年经验和深入研究文献,始终努力更好地回答“它是什么,它来自哪里?”这个古老的问题。本文中的表格和图片是我在显微镜下教学时“在电脑上调出”的,也是我在(经常)遇到困难时参考的。这个领域如此令人兴奋,是因为我坚信,通过应用下一代免疫组织化学,我们可以提供比以往任何时候都更好的答案。本文综述涵盖了以下内容:(1)广泛的肿瘤分类和相关筛选标志物;(2)癌症流行病学在确定术前概率中的作用;(3)广谱上皮标志物;(4)广谱肿瘤筛选标志物的非典型表达;(5)基于形态学模式的方法来诊断低分化或未分化恶性肿瘤;(6)基于形态学和免疫组织化学的方法来定义 4 种主要的癌类型;(7)CK7/CK20 共表达;(8)半定量免疫组织化学染色评估的附加值;(9)“普通”肝内腺癌、(10)大多边形细胞腺癌、(11)原发于卵巢表面具有黏液特征的上皮性肿瘤与转移瘤的鉴别、(12)其他部位起源的肿瘤、(13)鳞状细胞癌与尿路上皮癌、(14)嗜铬细胞瘤/副神经节瘤与分化良好的神经内分泌肿瘤的鉴别、(15)分化良好的神经内分泌肿瘤的起源部位鉴定、(16)低分化神经内分泌癌的起源部位鉴定,以及(17)分化良好的神经内分泌瘤 G3 与低分化神经内分泌癌的鉴别诊断;最后(18)讨论了广谱角蛋白/CD45/S-100-“三阴性”肿瘤的诊断注意事项。

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