Signaling pathway networks mined from human pituitary adenoma proteomics data.
Signaling pathway networks mined from human pituitary adenoma proteomics data.
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DOI：
10.1186/1755-8794-3-13
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发表时间：
2010-04-28
影响因子：
2.7
通讯作者：
Desiderio DM
中科院分区：
文献类型：
--
作者：
Zhan X;Desiderio DM
我们获得了一系列垂体腺瘤蛋白质组表达数据，包括蛋白质图谱数据（111种蛋白质），比较蛋白质组数据（56种差异表达蛋白质）和硝基蛋白质组数据（17种硝基蛋白质）。有迫切需要澄清的重要信号通路网络，从这些蛋白质，以澄清和更好地了解垂体腺瘤发病机制的分子基础，并发现生物标志物。在这里，我们描述了重要的信号通路网络，从人类垂体腺瘤蛋白质组数据挖掘与Incidity通路分析系统。使用Incidity通路分析系统从蛋白质图谱数据、比较蛋白质组数据、腺瘤硝基蛋白质组数据和对照硝基蛋白质组数据分析信号通路网络和典型通路。使用Fisher精确检验检验统计学显著性，显著性水平为0.05。通过基于文献的生物信息学分析，在垂体腺瘤生物学系统中对统计学显著性结果进行了合理化。对于蛋白质图谱数据，顶级通路网络与癌症、细胞死亡和脂质代谢相关;顶级经典毒性通路包括急性期反应、氧化应激反应、氧化应激和细胞周期G2/M转换调节。对于比较蛋白质组学数据，顶级通路网络与癌症、内分泌系统发育和功能以及脂质代谢相关;顶级经典毒性通路包括线粒体功能障碍、氧化磷酸化、氧化应激反应和ERK/MAPK信号传导。来自垂体腺瘤的硝基蛋白质组学数据与癌症、细胞死亡、脂质代谢和生殖系统疾病相关，并且顶级典型毒性途径主要与p38 MAPK信号传导和细胞周期G2/M转换调节相关。来自垂体对照的氮蛋白与基因表达和细胞发育相关，未发现典型毒性途径。这个通路网络分析表明，线粒体功能障碍，氧化应激，细胞周期失调，和MAPK信号异常与垂体腺瘤显着相关。这些通路网络数据为垂体腺瘤发病机制的分子机制提供了新的见解，为垂体腺瘤的深入研究和生物标志物的发现提供了新的线索。
We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified. This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.
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