Wojtas Bartosz, Pfeifer Aleksandra, Oczko-Wojciechowska Malgorzata, Krajewska Jolanta, Czarniecka Agnieszka, Kukulska Aleksandra, Eszlinger Markus, Musholt Thomas, Stokowy Tomasz, Swierniak Michal, Stobiecka Ewa, Chmielik Ewa, Rusinek Dagmara, Tyszkiewicz Tomasz, Halczok Monika, Hauptmann Steffen, Lange Dariusz, Jarzab Michal, Paschke Ralf, Jarzab Barbara
Department of Nuclear Medicine and Endocrine Oncology, Maria Sklodowska-Curie Institute-Oncology Center, Gliwice Branch, Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland.
Laboratory of Molecular Neurobiology, Neurobiology Center, Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland.
Int J Mol Sci. 2017 Jun 2;18(6):1184. doi: 10.3390/ijms18061184.
Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes (, , , , , , and ). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes (, , , ). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material.
区分滤泡状甲状腺癌(FTC)和滤泡状甲状腺腺瘤(FTA)一直是个诊断难题,导致组织病理学诊断模棱两可。因此,需要更多的分子标志物。为了确定FTC和FTA之间的分子差异,我们分析了52例滤泡性肿瘤的基因表达微阵列数据。我们还进行了一项荟萃分析,涉及14项采用高通量方法的研究(共分析了365例滤泡性肿瘤)。基于这两项分析,我们选择了18个在FTA和FTC之间差异表达的基因。我们通过定量实时聚合酶链反应(qRT-PCR)在一组独立的71例来自甲醛固定石蜡包埋(FFPE)组织材料的滤泡性肿瘤中对这些基因进行了验证。我们证实了7个基因(、、、、、和)的差异表达。最后,我们创建了一个分类器,基于4个基因(、、、) 的表达区分FTC和FTA,其准确率为78%,灵敏度为76%,特异性为80%。在我们的研究中,我们证明了荟萃分析是选择可能的分子标志物的一种有价值的方法。根据我们的结果,我们得出结论,当基于福尔马林固定的术后材料区分滤泡性肿瘤时,基因分类器的准确率可能存在一个合理的极限,约为80%。