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在人群中检测具有反复发生的基因组改变特征的癌症基因网络。

Detecting cancer gene networks characterized by recurrent genomic alterations in a population.

机构信息

The Mina & Everard Faculty of Life Science, Bar Ilan University, Ramat Gan, Israel.

出版信息

PLoS One. 2011 Jan 4;6(1):e14437. doi: 10.1371/journal.pone.0014437.

Abstract

High resolution, system-wide characterizations have demonstrated the capacity to identify genomic regions that undergo genomic aberrations. Such research efforts often aim at associating these regions with disease etiology and outcome. Identifying the corresponding biologic processes that are responsible for disease and its outcome remains challenging. Using novel analytic methods that utilize the structure of biologic networks, we are able to identify the specific networks that are highly significantly, nonrandomly altered by regions of copy number amplification observed in a systems-wide analysis. We demonstrate this method in breast cancer, where the state of a subset of the pathways identified through these regions is shown to be highly associated with disease survival and recurrence.

摘要

高分辨率、系统范围的特征分析已证明其能够识别发生基因组异常的基因组区域。此类研究工作通常旨在将这些区域与疾病病因和结果联系起来。确定导致疾病及其结果的相应生物学过程仍然具有挑战性。使用利用生物学网络结构的新型分析方法,我们能够识别出在系统范围内分析中观察到的拷贝数扩增区域高度显著、非随机改变的特定网络。我们在乳腺癌中证明了这种方法,通过这些区域确定的部分途径的状态与疾病的生存和复发高度相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af4/3014942/98a24f34ce79/pone.0014437.g001.jpg

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