Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN

Abstract

BackgroundMYCN is an oncogenic transcription factor of the MYC family and plays an important role in the formation of tissues and organs during development before birth. Due to the difficulty in drugging MYCN directly, revealing the molecules in MYCN regulatory networks will help to identify effective therapeutic targets.MethodsWe utilized network controllability theory, a recent developed powerful tool, to identify the potential drug target around MYCN based on Protein-Protein interaction network of MYCN. First, we constructed a Protein-Protein interaction network of MYCN based on public databases. Second, network control analysis was applied on network to identify driver genes and indispensable genes of the MYCN regulatory network. Finally, we developed a novel integrated approach to identify potential drug targets for regulating the function of the MYCN regulatory network.ResultsWe constructed an MYCN regulatory network that has 79 genes and 129 interactions. Based on network controllability theory, we analyzed driver genes which capable to fully control the network. We found 10 indispensable genes whose alternation will significantly change the regulatory pathways of the MYCN network. We evaluated the stability and correlation analysis of these genes and found EGFR may be the potential drug target which closely associated with MYCN.ConclusionTogether, our findings indicate that EGFR plays an important role in the regulatory network and pathways of MYCN and therefore may represent an attractive therapeutic target for cancer treatment.

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“…However, MYCN itself has a short half-life and complex protein structure, so it is difficult to directly target. Fortunately, we can identify the molecules that directly interact with MYCN by monitoring the MYCN network and applying control signals to achieve indirect regulation, which is expected to improve the disease state [38].…”

Measuring criticality in control of complex biological networks

“…Recent works have shown that minimum driver nodes (controllers) are not only important to control the network but also that they have been associated to important biological functions 3 – 7 . In particular, network controllability has been applied to identify cancer-related genes 3 , 8 – 12 , drug-targets 8 , 13 , disease-related non-coding RNAs (ncRNAs) 14 , virus-targeted proteins 3 , 15 , 16 and has also been used to predict specific neuron functions 17 as well as to unveil the human brain functional structure 18 .…”

From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder

“…The fundamental goal of network controllability is to drive the network from any initial state to a desired target state via specific input nodes [19]. Currently, network control theory has been applied in various biological networks, such as protein interaction networks [20], virus-protein networks [21], cancer regulatory networks [22], and brain networks [18]. In various network controllability methods, average controllability is considered a significant approach in the context of mental disorders.…”