Relevance of Network Hierarchy in Cancer Drug-Target Selection

Aritro Nath, Christina Chan

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

Targeted therapies aim to prevent cancer progression by inactivating tumor-specific signaling pathways. However, identifying a suitable drug target in the signaling network remains a major hurdle. Since signaling pathways can be considered as directional networks with hierarchical topology, we hypothesized that the hierarchical level of a candidate in the network impacts its efficiency as a drug-Target. This hypothesis was evaluated with three methods. First, Boolean modeling was applied to a hierarchical regulatory network to assess the impact of hierarchy on modulating the network output. Next, we analyzed the hierarchy of FDA-Approved drugs mapped onto pathways involved in prostate cancer. Finally, we converted a global transcriptional regulatory and signaling network into hierarchical networks to analyze the hierarchical distribution of cancer genes and the approved drug-Targets for cancer treatment.

Original languageEnglish (US)
Title of host publicationSystems Biology in Cancer Research and Drug Discovery
PublisherSpringer Netherlands
Pages339-362
Number of pages24
Volume9789400748194
ISBN (Electronic)9789400748194
ISBN (Print)9400748183, 9789400748187
DOIs
StatePublished - Aug 1 2012

Keywords

  • Boolean modeling
  • Hierarchical network
  • Prostate cancer
  • Targeted therapy

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  • Cite this

    Nath, A., & Chan, C. (2012). Relevance of Network Hierarchy in Cancer Drug-Target Selection. In Systems Biology in Cancer Research and Drug Discovery (Vol. 9789400748194, pp. 339-362). Springer Netherlands. https://doi.org/10.1007/978-94-007-4819-4_15