Cell cycle-dependent gene networks relevant to cancer  

作　　者：Yun Xiao Xia Li Yueying Yang Yadong Wang Shaoqi Rao 

机构地区：[1]College of Bioinformatics Science and Technology, and Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State, Harbin Medical University, Harbin 150086, China [2]Biomedical Engineering Institute of Capital Medical University, Beijing 10004, China [3]Department of Computer Science, Harbin Institute of Technology, Harbin 150080, China

出　　处：《Progress in Natural Science:Materials International》2008年第8期945-952,共8页自然科学进展·国际材料（英文版）

基　　金：the National High-Tech Development Project of China (Grant No.2007AA02Z329);National Natural Science Foundation of China (Grant Nos. 30170515, 30370798, 30571034,30570424 and 60601010);Outstanding Overseas Scientist Grant of the Heilongjiang Province (Grant No.1055HG009);National Science Foundation of Heilongjiang Province (Grant Nos. ZJG0501, GB03C602-4 and F2004-02);Health Department of Heilongjiang Province Key Project (2005-39).

摘　　要：The analysis of sophisticated interplays between cell cycle-dependent genes in a disease condition is one of the largely unexplored areas in modern tumor biology research. Many cell cycle-dependent genes are either oncogenes or suppressor genes, or are closely associated with the transition of a cell cycle. However, it is unclear how the complicated relationships between these cell cycle-dependent genes are, especially in cancers. Here, we sought to identify significant expression relationships between cell cycle-dependent genes by analyzing a HeLa microarray dataset using a local alignment algorithm and constructed a gene transcriptional network specific to the cancer by assembling these newly identified gene-gene relationships. We further characterized this global network by partitioning the whole network into several cell cycle phase-specific sub-networks. All generated networks exhibited the power-law node-degree distribution, and the average clustering coefficients of these networks were remarkably higher than those of pure scale-free networks, indicating a property of hierarchical modularity. Based on the known protein-protein interactions and Gene Ontology annotation data, the proteins encoded by cell cycle-dependent interacting genes tended to share the same biological functions or to be involved in the same biological processes, rather than interacting by physical means. Finally, we identified the hub genes related to cancer based on the topological importance that maintain the basic structure of cell cycle-dependent gene networks.The analysis of sophisticated interplays between cell cycle-dependent genes in a disease condition is one of the largely unexplored areas in modern tumor biology research. Many cell cycle-dependent genes are either oncogenes or suppressor genes, or are closely associated with the transition of a cell cycle. However, it is unclear how the complicated relationships between these cell cycle-dependent genes are, especially in cancers. Here, we sought to identify significant expression relationships between cell cycle-dependent genes by analyzing a HeLa microarray dataset using a local alignment algorithm and constructed a gene transcriptional network specific to the cancer by assembling these newly identified gene-gene relationships. We further characterized this global network by partitioning the whole network into several cell cycle phase-specific sub-networks. All generated networks exhibited the power-law node-degree distribution, and the average clustering coefficients of these networks were remarkably higher than those of pure scale-free networks, indicating a property of hierarchical modularity. Based on the known protein-protein interactions and Gene Ontology annotation data, the proteins encoded by cell cycle-dependent interacting genes tended to share the same biological functions or to be involved in the same biological processes, rather than interacting by physical means. Finally, we identified the hub genes related to cancer based on the topological importance that maintain the basic structure of cell cycle-dependent gene networks.

关 键 词：Cell cycle MICROARRAY HeLa cell Gene network 

分 类 号：R730[医药卫生—肿瘤]