Relevance of Network Hierarchy in Cancer Drug-Target Selection

Aritro Nath, Christina Chan

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations


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
Number of pages24
ISBN (Electronic)9789400748194
ISBN (Print)9400748183, 9789400748187
StatePublished - Aug 1 2012

Bibliographical note

Publisher Copyright:
© 2012 Springer Science+Business Media Dordrecht. All rights reserved.


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


Dive into the research topics of 'Relevance of Network Hierarchy in Cancer Drug-Target Selection'. Together they form a unique fingerprint.

Cite this