Overview of the 2022 WHO Classification of Neuroendocrine Neoplasms

神经内分泌肿瘤 神经内分泌分化 嗜铬粒蛋白A 分级(工程) 生物 门1 突触素 病理 生长抑素受体 生长抑素 激素 医学 内分泌系统 免疫组织化学 内科学 神经科学 内分泌学 癌症 前列腺癌 生态学
作者
Guido Rindi,Özgür Mete,Silvia Uccella,Olca Baştürk,Stefano La Rosa,Lodewijk A.A. Brosens,Shereen Ezzat,Wouter W. de Herder,David S. Klimstra,Mauro Papotti,L. Sylvia
出处
期刊:Endocrine Pathology [Springer Science+Business Media]
卷期号:33 (1): 115-154 被引量:1005
标识
DOI:10.1007/s12022-022-09708-2
摘要

In this review, we detail the changes and the relevant features that are applied to neuroendocrine neoplasms (NENs) in the 2022 WHO Classification of Endocrine and Neuroendocrine Tumors. Using a question-and-answer approach, we discuss the consolidation of the nomenclature that distinguishes neuronal paragangliomas from epithelial neoplasms, which are divided into well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). The criteria for these distinctions based on differentiation are outlined. NETs are generally (but not always) graded as G1, G2, and G3 based on proliferation, whereas NECs are by definition high grade; the importance of Ki67 as a tool for classification and grading is emphasized. The clinical relevance of proper classification is explained, and the importance of hormonal function is examined, including eutopic and ectopic hormone production. The tools available to pathologists for accurate classification include the conventional biomarkers of neuroendocrine lineage and differentiation, INSM1, synaptophysin, chromogranins, and somatostatin receptors (SSTRs), but also include transcription factors that can identify the site of origin of a metastatic lesion of unknown primary site, as well as hormones, enzymes, and keratins that play a role in functional and structural correlation. The recognition of highly proliferative, well-differentiated NETs has resulted in the need for biomarkers that can distinguish these G3 NETs from NECs, including stains to determine expression of SSTRs and those that can indicate the unique molecular pathogenetic alterations that underlie the distinction, for example, global loss of RB and aberrant p53 in pancreatic NECs compared with loss of ATRX, DAXX, and menin in pancreatic NETs. Other differential diagnoses are discussed with recommendations for biomarkers that can assist in correct classification, including the distinctions between epithelial and non-epithelial NENs that have allowed reclassification of epithelial NETs in the spine, in the duodenum, and in the middle ear; the first two may be composite tumors with neuronal and glial elements, and as this feature is integral to the duodenal lesion, it is now classified as composite gangliocytoma/neuroma and neuroendocrine tumor (CoGNET). The many other aspects of differential diagnosis are detailed with recommendations for biomarkers that can distinguish NENs from non-neuroendocrine lesions that can mimic their morphology. The concepts of mixed neuroendocrine and non-neuroendocrine (MiNEN) and amphicrine tumors are clarified with information about how to approach such lesions in routine practice. Theranostic biomarkers that assist patient management are reviewed. Given the significant proportion of NENs that are associated with germline mutations that predispose to this disease, we explain the role of the pathologist in identifying precursor lesions and applying molecular immunohistochemistry to guide genetic testing.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
破防怪发布了新的文献求助10
刚刚
wanci应助阔达星星采纳,获得10
刚刚
1秒前
SciGPT应助正直的靖荷采纳,获得10
1秒前
NexusExplorer应助东都哈士奇采纳,获得10
2秒前
Hwtttt完成签到,获得积分10
2秒前
Kelvin.Tsi发布了新的文献求助10
2秒前
4秒前
4秒前
乐空思应助RUI采纳,获得20
4秒前
cghfgbnvnvgx应助悠旷采纳,获得10
5秒前
俊逸盛男发布了新的文献求助10
5秒前
5秒前
徐徐徐徐完成签到 ,获得积分10
6秒前
7秒前
7秒前
2214发布了新的文献求助10
7秒前
7秒前
鹅鹅鹅发布了新的文献求助10
9秒前
9秒前
Jane发布了新的文献求助10
10秒前
Elias发布了新的文献求助10
10秒前
老流氓发布了新的文献求助10
10秒前
11秒前
11秒前
Miracle_wh完成签到 ,获得积分10
13秒前
14秒前
星辰大海应助沙枣花墙子采纳,获得10
14秒前
11213a发布了新的文献求助10
15秒前
慕许应助悠旷采纳,获得10
15秒前
丘比特应助啦啦不哭采纳,获得10
16秒前
16秒前
17秒前
科研通AI6.4应助你好采纳,获得10
17秒前
18秒前
bkagyin应助WN采纳,获得10
19秒前
19秒前
20秒前
20秒前
Orange应助Jane采纳,获得10
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
内視鏡的に摘除しえた十二指腸乳頭部腫瘍の2例 660
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Interpolation and Regression Models for the Chemical Engineer: Solving Numerical Problems 400
The Neuroscience of Language 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7686751
求助须知:如何正确求助?哪些是违规求助? 9249890
关于积分的说明 19959808
捐赠科研通 7259772
什么是DOI,文献DOI怎么找? 3289640
关于科研通互助平台的介绍 2446550
邀请新用户注册赠送积分活动 2294137