Prediction of Bone Metastasis in Breast Cancer Based on Minimal Driver Gene Set in Gene Dependency Network
Prediction of Bone Metastasis in Breast Cancer Based on Minimal Driver Gene Set in Gene Dependency Network
复制标题
基于基因依赖网络中最小驱动基因集的乳腺癌骨转移预测
DOI：
10.3390/genes10060466
复制
发表时间：
2019-06-01
期刊：
影响因子：
3.5
通讯作者：
Zhou, Xiong-Hui
中科院分区：
文献类型：
--
作者：
Li, Jia-Nuo;Zhong, Rui;Zhou, Xiong-Hui
骨是乳腺癌最常见的转移器官，因此预测乳腺癌的骨转移至关重要。在我们的工作中，我们构建了一个基因依赖网络的基础上的假设，一个基因和骨转移的风险之间的关系可能会受到另一个基因的影响。然后，基于结构可控性理论，在基因依赖网络中挖掘出能够控制整个网络的驱动基因集，并从中选择出签名基因。生存分析表明，该特征可以区分测试数据集和独立数据集中癌症患者的骨转移风险。此外，我们使用的签名基因，以构建一个质心分类器。结果表明，我们的方法是有效的，并且比已发表的方法表现得更好。
Bone is the most frequent organ for breast cancer metastasis, and thus it is essential to predict the bone metastasis of breast cancer. In our work, we constructed a gene dependency network based on the hypothesis that the relation between one gene and the risk of bone metastasis might be affected by another gene. Then, based on the structure controllability theory, we mined the driver gene set which can control the whole network in the gene dependency network, and the signature genes were selected from them. Survival analysis showed that the signature could distinguish the bone metastasis risks of cancer patients in the test data set and independent data set. Besides, we used the signature genes to construct a centroid classifier. The results showed that our method is effective and performed better than published methods.