Reverse engineering of modified genes by Bayesian network analysis defines molecular determinants critical to the development of glioblastoma.
Reverse engineering of modified genes by Bayesian network analysis defines molecular determinants critical to the development of glioblastoma.
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DOI：
10.1371/journal.pone.0064140
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Roy D
中科院分区：
文献类型：
--
作者：
Kunkle BW;Yoo C;Roy D
在这项研究中，我们已经确定了在星形细胞肿瘤的发展中至关重要的关键基因。将正常组织与星形细胞瘤进行比较的微阵列研究的荟萃分析揭示了大多数星形细胞瘤中的646个差异表达基因。使用贝叶斯网络分析对这646个基因进行逆向工程，为每个级别的星形细胞瘤（I-IV级）产生了一个基因网络，并确定了每个级别内的“关键基因”。发现对最高级别星形细胞瘤（多形性胶质母细胞瘤）的发展最具影响力的基因是：COL4A1、EGFR、BTF 3、MPP 2、RAB 31、CDK 4、CD99、ANXA 2、TOP2A和SERBP 1。除MPP2（下调）外，所有这些基因均上调。当使用逻辑回归、交叉验证和支持向量机分析时，这10个基因能够以96 - 100%的置信度预测肿瘤状态。马尔可夫基因与NFk β、ERK、MAPK、VEGF、生长激素和胶原蛋白相互作用，产生一个网络，其主要生物学功能是癌症、神经疾病和细胞运动。10个基因中的3个-EGFR、COL4A1和CDK4，尤其是，似乎是潜在的“活性中心”。与正常人群相比，这10个马尔可夫毯基因的修饰表达增加了发生胶质母细胞瘤的终生风险。胶质母细胞瘤风险估计值在4个或4个以上Markov Blanket基因的联合作用下显著增加。与正常人群相比，4、5、6、7、8、9或10个马尔可夫毯基因的联合相互作用效应分别使发生胶质母细胞瘤的终生风险增加9、13、20.9、26.7、52.8、53.2、78.1或85.9%。总之，似乎几个“关键基因”的修饰表达可能是胶质母细胞瘤发展所必需的。需要进一步的研究来验证这些“关键基因”作为早期检测和这些肿瘤的新治疗选择的有用工具。
In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors.
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