Network-based integration method for potential breast cancer gene identification |
| |
| Authors: | Yue Zhang Wan Li Yihua Zhang Erqiang Hu Zherou Rong Luanfeng Ge Gui Deng Yuehan He Junjie Lv Lina Chen Weiming He |
| |
| Affiliation: | 1. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China;2. Institute of Opto-Electronics, Harbin Institute of Technology, Harbin, Heilongjiang, China |
| |
| Abstract: | Breast cancer is the most common female death-causing cancer worldwide. A network-based integration method was proposed to identify potential breast cancer genes. First, genes were prioritized using a gene prioritization algorithm by the strategy of disease risks transferred between genes in a network with weighted vertexes and edges. Our prioritization algorithm was effectives and robust for top-ranked seed gene number and higher area under the curve values compared to ToppGene and ToppNet. Then, 20 potential breast cancer genes were identified as common genes of the top 50 candidate genes for their robustness in multiple prioritizations. These genes could accurately classify tumor and normal samples of all and paired sample sets and three independent datasets. Of potential breast cancer genes, 18 were verified by literature and 2 were novel genes that need further study. This study would contribute to the understanding of the genetic architecture for the diagnosis and treatment of breast cancer. |
| |
| Keywords: | breast cancer gene prioritization algorithm network with weighted vertexes and edges network-based integration method potential breast cancer genes |
|
|
