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利用光纤珠阵列和通路分析研究垂体腺瘤中的差异基因表达。

Analysis of differential gene expression using fiber-optic bead array and pathway analyses in pituitary adenomas.

机构信息

Neurosurgical Department, Capital Medical University, 100069 Beijing, China.

出版信息

J Clin Neurosci. 2011 Oct;18(10):1386-91. doi: 10.1016/j.jocn.2010.10.021. Epub 2011 Jul 28.

Abstract

Pituitary adenomas are commonly occurring, benign neoplasms that account for 15% of intracranial neoplasms but their pathogenesis remains elusive. To explore the possible pathogenesis of pituitary adenomas, we used fiber-optic bead arrays to compare the gene expression profiles in five major pituitary adenoma subtypes to normal pituitary gland from three recently deceased males. We used reverse transcriptase-real time quantitative polymerase chain reaction (RT-qPCR) to randomly validate the expression of four differentially expressed genes in the five pituitary adenoma subtypes and three normal pituitary glands. We then analyzed the profiles of the differentially expressed genes using the Kyoto Encyclopedia of Genes and Genomes pathways. Array analysis showed that 129 genes and two expressed sequence tags were differentially co-expressed in all pituitary adenomas. Pathway analyses showed that the extracellular matrix-receptor interaction pathway and the transforming growth factor-beta signaling pathway may have an important role in tumorigenesis of the five pituitary adenoma subtypes. Thus, we suggest the presence of a common mode of pathogenesis in pituitary adenoma subtypes. Fiber-optic bead array analysis combined with pathway analysis of differentially expressed genes appears to be a valid method of investigating the pathogenesis of different tumors.

摘要

垂体腺瘤是常见的良性肿瘤,占颅内肿瘤的 15%,但其发病机制仍不清楚。为了探讨垂体腺瘤的可能发病机制,我们使用光纤珠阵列比较了五个主要的垂体腺瘤亚型与三个最近死亡的男性的正常垂体中的基因表达谱。我们使用逆转录实时定量聚合酶链反应(RT-qPCR)随机验证了五个垂体腺瘤亚型和三个正常垂体中四个差异表达基因的表达。然后,我们使用京都基因与基因组百科全书(KEGG)途径分析了差异表达基因的图谱。阵列分析显示,所有垂体腺瘤中有 129 个基因和两个表达序列标签差异共表达。途径分析表明,细胞外基质-受体相互作用途径和转化生长因子-β信号通路可能在五种垂体腺瘤亚型的肿瘤发生中起重要作用。因此,我们认为垂体腺瘤亚型存在共同的发病机制模式。光纤珠阵列分析结合差异表达基因的途径分析似乎是研究不同肿瘤发病机制的有效方法。

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