Neubauer Elisa, Wirtz Ralph M, Kaemmerer Daniel, Athelogou Maria, Schmidt Lydia, Sänger Jörg, Lupp Amelie
Institute of Pharmacology and Toxicology, Jena University Hospital, Friedrich Schiller University, Jena, Germany.
STRATIFYER Molecular Pathology GmbH Köln, Köln, Germany.
Oncotarget. 2016 Jul 5;7(27):41959-41973. doi: 10.18632/oncotarget.9747.
The classification of bronchopulmonary neuroendocrine neoplasms (BP-NEN) into four tumor entities (typical carcinoids (TC), atypical carcinoids (AC), small cell lung cancers (SCLC), large cell neuroendocrine lung carcinomas (LCNEC)) is difficult to perform accurately, but important for prognostic statements and therapeutic management decisions. In this regard, we compared the expression of three proliferation markers, Ki-67, Topoisomerase II alpha (TOP2A), and RacGAP1, in a series of tumor samples from 104 BP-NEN patients (24 TC, 21 AC, 52 SCLC, 7 LCNEC) using different evaluation methods (immunohistochemistry (IHC): Average evaluation, Hotspot evaluation, digital image analysis; RT-qPCR).The results indicated that all three markers had increased protein and mRNA expression with poorer differentiation and correlated well with each other, as well as with grading, staging, and poor survival. Compared with Ki-67 and TOP2A, RacGAP1 allowed for a clearer prognostic statement. The cut-off limits obtained for Ki-67-Average (IHC) were TC-AC 1.5, AC-SCLC 19, and AC-LCNEC 23.5. The Hotspot evaluation generated equal to higher, the digital image analysis generally lower between-entity cut-off limits.All three markers enabled a clear-cut differentiation between the BP-NEN entities, and all methods evaluated were suitable for marker assessment. However, to define optimal cut-off limits, the Ki-67 evaluation methods should be standardized. RacGAP1 appeared to be a new marker with great potential.
将支气管肺神经内分泌肿瘤(BP-NEN)分为四种肿瘤实体(典型类癌(TC)、非典型类癌(AC)、小细胞肺癌(SCLC)、大细胞神经内分泌肺癌(LCNEC))很难准确进行,但对预后判断和治疗管理决策很重要。在这方面,我们使用不同评估方法(免疫组织化学(IHC):平均评估、热点评估、数字图像分析;RT-qPCR)比较了104例BP-NEN患者(24例TC、21例AC、52例SCLC、7例LCNEC)的一系列肿瘤样本中三种增殖标志物Ki-67、拓扑异构酶IIα(TOP2A)和RacGAP1的表达。结果表明,随着分化程度降低,所有三种标志物的蛋白质和mRNA表达均增加,且彼此之间以及与分级、分期和不良生存密切相关。与Ki-67和TOP2A相比,RacGAP1能做出更清晰的预后判断。Ki-67平均(IHC)的临界值为TC-AC 1.5、AC-SCLC 19和AC-LCNEC 23.5。热点评估产生的实体间临界值相等或更高,数字图像分析通常更低。所有三种标志物都能明确区分BP-NEN实体,且所有评估方法都适用于标志物评估。然而,为了确定最佳临界值,Ki-67评估方法应标准化。RacGAP1似乎是一种具有巨大潜力的新标志物。