Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates.
Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates.
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DOI：
10.1186/1752-0509-2-106
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发表时间：
2008-12-05
影响因子：
--
通讯作者：
Miyano S
中科院分区：
文献类型：
--
作者：
Fujita A;Gomes LR;Sato JR;Yamaguchi R;Thomaz CE;Sogayar MC;Miyano S
前列腺癌是男性死亡的主要原因之一，因此，有必要对前列腺肿瘤过程中涉及的基因和分子网络进行全面的研究。为了了解潜在生物标志物背后的生物学过程，我们分析了一组包含约25,000个基因的57个cDNA微阵列。采用主成分分析（PCA）和最大熵线性判别分析（MLDA）相结合的方法，对正常前列腺组织与肿瘤前列腺组织之间具有最大判别信息的基因进行鉴定。使用三种不同的方法进行数据分析，即：(i)从单变量角度来看正常和肿瘤条件下基因表达水平的差异；（ii）以多元方式使用MLDA；（三）采用依赖网络方法。我们的研究结果表明，前列腺组织的恶性转化更多地与它们依赖网络中的功能连通性变化有关，而不是与差异基因表达有关。MYLK、KLK2、KLK3、HAN11、LTF、CSRP1和TGM4基因在正常和肿瘤状态之间的功能连通性发生了显著变化，我们的判别分析也将这些基因列为前列腺癌发生过程中信息最多的前7个基因。此外，在鉴定的基因中，我们发现了经典已知的生物标志物和与前列腺肿瘤密切相关的基因，如KLK3和KLK2以及其他一些潜在的基因。我们已经证明，功能连接的变化可能隐含在生物学过程中，这使得一些基因更有信息来区分正常和肿瘤状况。利用所提出的方法，即MLDA，分析基因的多变量特征，可以捕捉到与细胞转化相关的依赖网络的变化。
Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.
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影响因子：
56.9
作者：
Golub, TR;Slonim, DK;Lander, ES
通讯作者：
Lander, ES
影响因子：
4.8
作者：
Chaib, H;Cockrell, EK;Macoska, JA
通讯作者：
Macoska, JA
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5.7
作者：
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通讯作者：
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4
作者：
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4.8
作者：
Gober, MD;Smith, CC;Aurelian, L
通讯作者：
Aurelian, L