Relevance of Network Hierarchy in Cancer Drug-Target Selection

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.