• DocumentCode
    2039361
  • Title

    Comprehensive analyses of tumor suppressor genes in protein-protein interaction networks: A topological perspective

  • Author

    Min Zhao ; Jingchun Sun ; Zhongming Zhao

  • Author_Institution
    Dept. of Biomed. Inf., Vanderbilt Univ., Nashville, TN, USA
  • fYear
    2012
  • fDate
    2-4 Dec. 2012
  • Firstpage
    101
  • Lastpage
    102
  • Abstract
    Tumor suppressor genes (TSGs) are a class of genes that play key roles in cancer induction and development. A comprehensive investigation of TSGs in protein-protein interaction (PPI) networks may expand our understanding on their roles in cancer development. In this study, we first collected reliable human TSG lists from tumor suppressor gene database. To provide an unbiased network view, we mapped human TSGs to four model organisms with different evolutionary distances to human (mouse, fly, worm, and yeast) using homology relationship. Using human TSGs and their homologs, we overlapped TSGs to their corresponding PPI networks. To explore the network properties of TSGs we examined their degree, betweenness, and closeness centralities by uniquely comparing them with three other sets of genes. We found that TSGs tend to interact more strongly than other non-cancer disease genes in human, mouse, fly, and worm, which confirmed previous global topological property studies on cancer genes. This demonstrates that TSGs are important to initiate interaction with other molecular during cancer development. This study represents the first statistical evaluation of TSGs in PPI networks. In addition, the data presented in this study will be valuable for the study of TSGs and their interaction partners.
  • Keywords
    bioinformatics; cancer; evolution (biological); genetics; molecular biophysics; proteins; statistical analysis; topology; tumours; PPI networks; and closeness centrality; betweenness centrality; cancer development; cancer induction; evolutionary distances; fly; homology relationship; model organisms; mouse; noncancer disease genes; protein-protein interaction networks; statistical evaluation; tumor suppressor genes; worm; yeast; Global network characteristics; Network topology; Protein-protein interaction; Tumor suppressor gene;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genomic Signal Processing and Statistics, (GENSIPS), 2012 IEEE International Workshop on
  • Conference_Location
    Washington, DC
  • ISSN
    2150-3001
  • Print_ISBN
    978-1-4673-5234-5
  • Type

    conf

  • DOI
    10.1109/GENSIPS.2012.6507738
  • Filename
    6507738