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一种用于在调控网络中寻找去调控子图的整数线性规划方法。

An integer linear programming approach for finding deregulated subgraphs in regulatory networks.

机构信息

Department of Human Genetics, Saarland University, 66421 Homburg/Saar, Germany.

出版信息

Nucleic Acids Res. 2012 Mar;40(6):e43. doi: 10.1093/nar/gkr1227. Epub 2011 Dec 30.

DOI:10.1093/nar/gkr1227
PMID:22210863
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3315310/
Abstract

Deregulation of cell signaling pathways plays a crucial role in the development of tumors. The identification of such pathways requires effective analysis tools that facilitate the interpretation of expression differences. Here, we present a novel and highly efficient method for identifying deregulated subnetworks in a regulatory network. Given a score for each node that measures the degree of deregulation of the corresponding gene or protein, the algorithm computes the heaviest connected subnetwork of a specified size reachable from a designated root node. This root node can be interpreted as a molecular key player responsible for the observed deregulation. To demonstrate the potential of our approach, we analyzed three gene expression data sets. In one scenario, we compared expression profiles of non-malignant primary mammary epithelial cells derived from BRCA1 mutation carriers and of epithelial cells without BRCA1 mutation. Our results suggest that oxidative stress plays an important role in epithelial cells of BRCA1 mutation carriers and that the activation of stress proteins may result in avoidance of apoptosis leading to an increased overall survival of cells with genetic alterations. In summary, our approach opens new avenues for the elucidation of pathogenic mechanisms and for the detection of molecular key players.

摘要

细胞信号通路的失调在肿瘤的发生发展中起着至关重要的作用。识别这些通路需要有效的分析工具来帮助解释表达差异。在这里,我们提出了一种新颖而高效的方法,用于识别调控网络中失调的子网络。给定每个节点的分数,该分数衡量相应基因或蛋白质失调的程度,该算法计算从指定根节点可达的指定大小的最重连通子网络。该根节点可以解释为负责观察到的失调的分子关键参与者。为了展示我们方法的潜力,我们分析了三个基因表达数据集。在一种情况下,我们比较了来自 BRCA1 突变携带者的非恶性原发性乳腺上皮细胞和没有 BRCA1 突变的上皮细胞的表达谱。我们的结果表明,氧化应激在 BRCA1 突变携带者的上皮细胞中起着重要作用,应激蛋白的激活可能导致细胞避免凋亡,从而导致具有遗传改变的细胞的整体存活率增加。总之,我们的方法为阐明发病机制和检测分子关键参与者开辟了新的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/281595d72d76/gkr1227f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/e05662b88d8d/gkr1227f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/a720355d090e/gkr1227f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/c5711f51d7c4/gkr1227f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/281595d72d76/gkr1227f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/e05662b88d8d/gkr1227f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/a720355d090e/gkr1227f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/c5711f51d7c4/gkr1227f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbbc/3315310/281595d72d76/gkr1227f4.jpg

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