Giordano Thomas J, Thomas Dafydd G, Kuick Rork, Lizyness Michelle, Misek David E, Smith Angela L, Sanders Donita, Aljundi Rima T, Gauger Paul G, Thompson Norman W, Taylor Jeremy M G, Hanash Samir M
Departments of Pathology, Pediatrics, Surgery, and Biostatistics, University of Michigan Health System, Ann Arbor, Michigan 48109-0054, USA.
Am J Pathol. 2003 Feb;162(2):521-31. doi: 10.1016/S0002-9440(10)63846-1.
Comprehensive expression profiling of tumors using DNA microarrays has been used recently for molecular classification and biomarker discovery, as well as a tool to identify and investigate genes involved in tumorigenesis. Application of this approach to a cohort of benign and malignant adrenocortical tissues would be potentially informative in all of these aspects. In this study, we generated transcriptional profiles of 11 adrenocortical carcinomas (ACCs), 4 adrenocortical adenomas (ACAs), 3 normal adrenal cortices (NCs), and 1 macronodular hyperplasia (MNH) using Affymetrix HG_U95Av2 oligonucleotide arrays representing approximately 10,500 unique genes. The expression data set was used for unsupervised hierarchical cluster analysis as well as principal component analysis to visually represent the expression data. An analysis of variance on the three classes (NC, ACA plus MNH, and ACC) revealed 91 genes that displayed at least threefold differential expression between the ACC cohort and both the NC and ACA cohorts at a significance level of P < 0.01. Included in these 91 genes were those known to be up-regulated in adrenocortical tumors, such as insulin-like growth factor (IGF2), as well as novel differentially expressed genes such as osteopontin (SPP) and serine threonine kinase 15 (STK15). Increased expression of IGF2 was identified in 10 of 11 ACCs (90.9%) and was verified by quantitative reverse transcriptase-polymerase chain reaction. Select proliferation-related genes (TOP2A and Ki-67) were validated at the protein level using immunohistochemistry and adrenocortical tissue microarrays. Our results demonstrated significant and consistent gene expression changes in ACCs compared to benign adrenocortical lesions. Moreover, we identified several genes that represent potential diagnostic markers and may play a role in the pathogenesis of ACC.
近期,利用DNA微阵列对肿瘤进行全面的表达谱分析已用于分子分类和生物标志物发现,同时也是一种识别和研究参与肿瘤发生的基因的工具。将该方法应用于一组良性和恶性肾上腺皮质组织,在所有这些方面可能都具有参考价值。在本研究中,我们使用代表约10,500个独特基因的Affymetrix HG_U95Av2寡核苷酸阵列,生成了11例肾上腺皮质癌(ACC)、4例肾上腺皮质腺瘤(ACA)、3例正常肾上腺皮质(NC)和1例大结节性增生(MNH)的转录谱。该表达数据集用于无监督层次聚类分析以及主成分分析,以直观呈现表达数据。对三个类别(NC、ACA加MNH和ACC)进行方差分析,结果显示有91个基因在ACC组与NC组和ACA组之间表现出至少三倍的差异表达,显著性水平为P < 0.01。这91个基因中包括那些已知在肾上腺皮质肿瘤中上调的基因,如胰岛素样生长因子(IGF2),以及新的差异表达基因,如骨桥蛋白(SPP)和丝氨酸苏氨酸激酶15(STK15)。在11例ACC中的10例(90.9%)中发现IGF2表达增加,并通过定量逆转录聚合酶链反应进行了验证。使用免疫组织化学和肾上腺皮质组织微阵列在蛋白质水平验证了选定的增殖相关基因(TOP2A和Ki-67)。我们的结果表明,与良性肾上腺皮质病变相比,ACC中存在显著且一致的基因表达变化。此外,我们鉴定出了几个代表潜在诊断标志物的基因,它们可能在ACC的发病机制中发挥作用。