Meta-analysis of glioblastoma multiforme versus anaplastic astrocytoma identifies robust gene markers.
Meta-analysis of glioblastoma multiforme versus anaplastic astrocytoma identifies robust gene markers.
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DOI：
10.1186/1476-4598-8-71
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发表时间：
2009-09-04
期刊：
影响因子：
37.3
通讯作者：
Park PJ
中科院分区：
文献类型：
--
作者：
Dreyfuss JM;Johnson MD;Park PJ
间变性星形细胞瘤(AA)和其更具侵袭性的多形性胶质母细胞瘤(GBM)是成人最常见的固有脑肿瘤，几乎普遍致命。更深入地了解这些肿瘤类型的分子关系对于深入了解胶质瘤的诊断、预后和治疗是必要的。虽然利用微阵列对表达水平进行全基因组图谱分析可以用来识别这些肿瘤类型之间的差异表达基因，但到目前为止，比较研究的结果是基因列表几乎没有重叠。为了获得更准确和稳定的原发基底膜和再生障碍性贫血之间差异表达基因和途径的列表，我们使用公开可用的基因组规模的信使核糖核酸数据集进行了荟萃分析。有四个数据集具有足够大的GBM和AAS样本量，所有这些数据集都巧合地使用了Affymetrix的人类U133平台，从而允许更容易和更精确地整合数据。在对每个数据集中的基因和通路进行评分后，我们使用非参数秩和方法将研究中的统计数据结合在一起，以识别区分GBM和AAs的特征。在对22,000个被测试的>；多次测试进行校正后，我们发现了具有统计意义的>；900个探针组。我们还使用秩和方法选择了20个重要的BioCarta途径，在对所研究的>；175个途径进行多次检验后进行了校正。最重要的途径是低氧诱导因子(HIF)途径。我们的分析表明，与AA相比，许多最具统计学意义的基因在HIF1a/VEGF调节的网络中共同作用，增加了GBM中的血管生成和侵袭。我们对289个人类恶性胶质瘤的基因组规模的mRNA表达数据进行了荟萃分析，并确定了一系列在GBM和AA之间显著不同的>；900探针组和>；20条通路。这些特征列表可用于帮助高级别胶质瘤的诊断、预后和分级降低，并识别以前未被怀疑在胶质瘤生物学中发挥重要作用的基因。更广泛地说，这种方法表明，对现有数据集的联合分析可以揭示新的见解，并且应该以类似的方式进一步利用大量可公开获得的癌症数据集。
Anaplastic astrocytoma (AA) and its more aggressive counterpart, glioblastoma multiforme (GBM), are the most common intrinsic brain tumors in adults and are almost universally fatal. A deeper understanding of the molecular relationship of these tumor types is necessary to derive insights into the diagnosis, prognosis, and treatment of gliomas. Although genomewide profiling of expression levels with microarrays can be used to identify differentially expressed genes between these tumor types, comparative studies so far have resulted in gene lists that show little overlap. To achieve a more accurate and stable list of the differentially expressed genes and pathways between primary GBM and AA, we performed a meta-analysis using publicly available genome-scale mRNA data sets. There were four data sets with sufficiently large sample sizes of both GBMs and AAs, all of which coincidentally used human U133 platforms from Affymetrix, allowing for easier and more precise integration of data. After scoring genes and pathways within each data set, we combined the statistics across studies using the nonparametric rank sum method to identify the features that differentiate GBMs and AAs. We found >900 statistically significant probe sets after correction for multiple testing from the >22,000 tested. We also used the rank sum approach to select >20 significant Biocarta pathways after correction for multiple testing out of >175 pathways examined. The most significant pathway was the hypoxia-inducible factor (HIF) pathway. Our analysis suggests that many of the most statistically significant genes work together in a HIF1A/VEGF-regulated network to increase angiogenesis and invasion in GBM when compared to AA. We have performed a meta-analysis of genome-scale mRNA expression data for 289 human malignant gliomas and have identified a list of >900 probe sets and >20 pathways that are significantly different between GBM and AA. These feature lists could be utilized to aid in diagnosis, prognosis, and grade reduction of high-grade gliomas and to identify genes that were not previously suspected of playing an important role in glioma biology. More generally, this approach suggests that combined analysis of existing data sets can reveal new insights and that the large amount of publicly available cancer data sets should be further utilized in a similar manner.
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影响因子：
3
作者：
Hwang KB;Kong SW;Greenberg SA;Park PJ
通讯作者：
Park PJ
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
DOI：
10.1142/s0219720005001442
发表时间：
2005-10-01
影响因子：
1
作者：
Breitling, Rainer;Herzyk, Pawel
通讯作者：
Herzyk, Pawel
影响因子：
3
作者：
Jeffery, Ian B.;Higgins, Desmond G.;Culhane, Aedin C.
通讯作者：
Culhane, Aedin C.
影响因子：
1.5
作者：
Infanger, Manfred;Grosse, Jirka;Grimm, Daniela
通讯作者：
Grimm, Daniela