Detecting cancer gene networks characterized by recurrent genomic alterations in a population.
Detecting cancer gene networks characterized by recurrent genomic alterations in a population.
复制标题
DOI：
10.1371/journal.pone.0014437
复制
发表时间：
2011-01-04
期刊：
影响因子：
3.7
通讯作者：
Buetow KH
中科院分区：
文献类型：
--
作者：
Efroni S;Ben-Hamo R;Edmonson M;Greenblum S;Schaefer CF;Buetow KH
高分辨率，全系统的表征已经证明了鉴定经历基因组畸变的基因组区域的能力。这些研究工作往往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过程仍然具有挑战性。使用新的分析方法，利用生物网络的结构，我们能够识别特定的网络是高度显着的，非随机改变的拷贝数扩增区域中观察到的系统范围内的分析。我们在乳腺癌中证明了这种方法，其中通过这些区域确定的通路子集的状态与疾病生存和复发高度相关。
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.
登录
查看更多内容
影响因子：
30.8
作者：
Hodgson, G;Hager, JH;Gray, JW
通讯作者：
Gray, JW
影响因子：
4.8
作者：
Isaacs, JS;Jung, YJ;Neckers, LM
通讯作者：
Neckers, LM
影响因子：
4.8
作者：
Graves, PR;Yu, LJ;Piwnica-Worms, H
通讯作者：
Piwnica-Worms, H
影响因子：
50.3
作者：
Chin, Koei;DeVries, Sandy;Gray, Joe W.
通讯作者：
Gray, Joe W.
影响因子：
82.9
作者：
Cheng, KW;Lahad, JP;Mills, GB
通讯作者：
Mills, GB