Identification of Genes Associated with Breast Cancer Metastasis to Bone on a Protein-Protein Interaction Network with a Shortest Path Algorithm

作     者：Cai, Yu-Dong Zhang, Qing Zhang, Yu-Hang Chen, Lei Huang, Tao 

作者机构：Shanghai Univ Sch Life Sci Shanghai 200111 Peoples R China Chinese Acad Sci Shanghai Inst Biol Sci Inst Hlth Sci Shanghai 200031 Peoples R China Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China 

出 版 物：《JOURNAL OF PROTEOME RESEARCH》 (蛋白质组研究杂志)

年 卷 期：2017年第16卷第2期

页      面：1027-1038页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 081704[工学-应用化学] 07[理学] 08[工学] 0817[工学-化学工程与技术] 

基　　金：National Natural Science Foundation of China Shanghai Sailing Program Youth Innovation Promotion Association of Chinese Academy of Sciences (CAS) 

主　　题：breast cancer metastasis to bone breast cancer bone cancer protein-protein interaction shortest path algorithm 

摘      要：Tumor metastasis is defined as the spread of tumor cells from one organ or part to another that is not directly connected to it, which significantly contributes to the progression and aggravation of tumorigenesis. Because it always involves multiple organs, the metastatic process is difficult to study in its entirety. Complete identification of the genes related to this process is an alternative way to study metastasis. In this study, we developed a computational method to identify such genes. To test our method, we selected breast cancer bone metastasis. A large network was constructed using human protein-protein interactions. On the basis of the validated genes related to breast and bone cancer, a shortest path algorithm was applied to the network to search for novel genes that may mediate breast cancer metastasis to bone. In addition, further rules constructed using the permutation FDR, the betweenness ratio, and the maxmin interaction score were also employed in the method to make the inferred genes more reliable. Eighteen putative genes were identified by the method and were extensively analyzed. The confirmation results indicate that these genes participate in metastasis.