Detecting cancer outlier genes with potential rearrangement using gene expression data and biological networks.
Detecting cancer outlier genes with potential rearrangement using gene expression data and biological networks.
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DOI：
10.1155/2012/373506
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发表时间：
2012
影响因子：
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通讯作者：
Alhajj R
中科院分区：
文献类型：
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作者：
Alshalalfa M;Bismar TA;Alhajj R
基因改变是肿瘤基因组景观的主要组成部分。为了评估这些改变在前列腺癌发展中的意义，有必要识别这些改变并从系统生物学角度分析它们。在这里，我们提出了一种新的方法（EigFusion）预测离群基因与潜在的基因重排。EigFusion在识别具有潜在重排的离群基因方面表现出优异的性能，通过将其测试到合成和真实的数据来评估性能。EigFusion能够识别以前未识别的基因，如FABP5和KCNH8，并证实它们与原发性和转移性前列腺样本的相关性，同时证实了其他基因如PAH，TOP2A和SPINK1的转移特异性。我们进行了基于蛋白质网络的方法来分析潜在重排基因的网络背景。通过整合功能蛋白质网络构建功能基因重排模块。重排的基因显示与癌症中众所周知的改变基因高度相关，如AR，RB1，MYC和BRCA1。最后，使用前列腺癌患者的临床结果数据，潜在的重排基因与前列腺癌特异性死亡显着相关。
Gene alterations are a major component of the landscape of tumor genomes. To assess the significance of these alterations in the development of prostate cancer, it is necessary to identify these alterations and analyze them from systems biology perspective. Here, we present a new method (EigFusion) for predicting outlier genes with potential gene rearrangement. EigFusion demonstrated excellent performance in identifying outlier genes with potential rearrangement by testing it to synthetic and real data to evaluate performance. EigFusion was able to identify previously unrecognized genes such as FABP5 and KCNH8 and confirmed their association with primary and metastatic prostate samples while confirmed the metastatic specificity for other genes such as PAH, TOP2A, and SPINK1. We performed protein network based approaches to analyze the network context of potential rearranged genes. Functional gene rearrangement Modules are constructed by integrating functional protein networks. Rearranged genes showed to be highly connected to well-known altered genes in cancer such as AR, RB1, MYC, and BRCA1. Finally, using clinical outcome data of prostate cancer patients, potential rearranged genes demonstrated significant association with prostate cancer specific death.