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肺类癌的表型分析和基于 Ki-67 的分级方法。

Phenotyping of pulmonary carcinoids and a Ki-67-based grading approach.

机构信息

Institute for Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 220/221, 69120 Heidelberg, Germany.

出版信息

Virchows Arch. 2012 Mar;460(3):299-308. doi: 10.1007/s00428-012-1194-2.

Abstract

Pulmonary carcinoids (PC) are separated into typical (TC) and atypical carcinoids (ATC). However, the biological behavior cannot be reliably predicted, and in small biopsies differential diagnosis can be challenging. To provide a basis for a grading approach, we analyzed mitoses and the proliferative index (PI; Ki-67) of 200 PC specimens (TC: n = 114; ATC: n = 86). To define suitable diagnostic and to screen for putative therapeutic markers, CD56, CD57, CD99, CD117, TTF-1, synaptophysin, chromogranin A, CK 18, KL-1, epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (Her-2/neu), somatostatin receptor subtype 2A (SSTR2A), thymidylate synthase (TS), and excision repair cross-complementation group 1 (ERCC-1) expression was analyzed. A combination of synaptophysin and cytokeratins is the most sensitive marker panel for PC with unclear histomorphology. Predictive phenotyping revealed that SSTR2A is expressed in >80% of all PC and may be used both, as a diagnostic marker for imaging approaches and as a predictive marker for octreotide-based therapies. We introduced a grading system distinguishing between PC with low and highly aggressive biological behavior similar to the grading system for gastrointestinal neuroendocrine tumors. The system is superior to the classical separation into TC and ATC. This study indicates that PI in addition to mitotic count may improve prediction of the biological behavior of PC and should be validated in prospective studies.

摘要

肺类癌(PC)分为典型类癌(TC)和非典型类癌(ATC)。然而,其生物学行为无法可靠预测,在小活检中鉴别诊断具有挑战性。为了提供分级方法的基础,我们分析了 200 个 PC 标本(TC:n=114;ATC:n=86)的有丝分裂和增殖指数(PI;Ki-67)。为了定义合适的诊断方法并筛选潜在的治疗标志物,我们分析了 CD56、CD57、CD99、CD117、TTF-1、突触素、嗜铬粒蛋白 A、CK18、KL-1、表皮生长因子受体(EGFR)、人表皮生长因子受体 2(Her-2/neu)、生长抑素受体亚型 2A(SSTR2A)、胸苷酸合成酶(TS)和切除修复交叉互补基因 1(ERCC-1)的表达。对于组织形态学不明确的 PC,突触素和细胞角蛋白的组合是最敏感的标志物组合。预测表型显示,SSTR2A 在所有 PC 中的表达>80%,可作为影像学方法的诊断标志物和奥曲肽治疗的预测标志物。我们引入了一种分级系统,可区分低和高侵袭性生物学行为的 PC,类似于胃肠道神经内分泌肿瘤的分级系统。该系统优于经典的 TC 和 ATC 分离。这项研究表明,PI 除了有丝分裂计数外,还可以改善对 PC 生物学行为的预测,应在前瞻性研究中验证。

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