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三项荟萃分析从星形细胞瘤的基因芯片数据集定义了一组常见的过度表达基因。

Three meta-analyses define a set of commonly overexpressed genes from microarray datasets on astrocytomas.

机构信息

Anal-Colorectal Surgery Institute, 150th Central Hospital of PLA, Luoyang, Henan, China.

出版信息

Mol Neurobiol. 2013 Feb;47(1):325-36. doi: 10.1007/s12035-012-8367-5. Epub 2012 Nov 8.

Abstract

Glioma is one of the most common tumors of the central nervous system, and one of its main types is astrocytoma. Microarray technology has been widely used to explore the molecular mechanism of cancer. It is universally accepted that meta-analysis considerably improves the statistical robustness of results, particularly in clinical research. To obtain the maximum reliability, we used three different meta-analyses to integrate the four microarray datasets, GSE16011, GSE4290, GSE2223, and GSE19728 (local), and defined the common differentially expressed genes (DEGs) in astrocytomas compared with normal brain tissue. Four DEGs, PCNA, CDC2, CDK2 and CCNB2, which are components of the cell cycle pathway, were chosen for Real-Time Polymerase Chain Reaction (RT-PCR) and immunohistochemistry validation. PCNA is similar to the P53 gene and has been widely implicated in various cancers including gliomas. Therefore, the expression status of PCNA in our study was considered as a reference to test our whole experimental scheme, and the results indicate that our methodology is valid. Although a few studies have reported the overexpression of the CDC2, CDK2 and CCNB2 genes in glioma cell lines, we are the first to identify the statuses of these genes in human astrocytoma tissues at the mRNA and protein levels. The results of the gene validations strongly suggested that the genes play an important role in astrocytomas and could potentially be valuable in the diagnosis and treatment of astrocytoma.

摘要

神经胶质瘤是中枢神经系统最常见的肿瘤之一,其中主要类型之一是星形细胞瘤。微阵列技术已被广泛用于探索癌症的分子机制。荟萃分析极大地提高了结果的统计稳健性,这在临床研究中尤为普遍。为了获得最大的可靠性,我们使用了三种不同的荟萃分析方法来整合四个微阵列数据集 GSE16011、GSE4290、GSE2223 和 GSE19728(本地),并定义了星形细胞瘤与正常脑组织相比的常见差异表达基因(DEG)。选择了四个细胞周期途径的组成部分的 DEG,PCNA、CDC2、CDK2 和 CCNB2,用于实时聚合酶链反应(RT-PCR)和免疫组织化学验证。PCNA 与 P53 基因相似,已广泛涉及包括神经胶质瘤在内的各种癌症。因此,我们研究中 PCNA 的表达状态被认为是测试我们整个实验方案的参考,结果表明我们的方法是有效的。尽管有一些研究报道了 CDC2、CDK2 和 CCNB2 基因在神经胶质瘤细胞系中的过表达,但我们是第一个在人类星形细胞瘤组织中鉴定这些基因在 mRNA 和蛋白质水平上的状态的人。基因验证的结果强烈表明这些基因在星形细胞瘤中发挥着重要作用,并且可能对星形细胞瘤的诊断和治疗有价值。

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