Attractor landscape analysis of colorectal tumorigenesis and its reversion.

Sung-Hwan Cho,Sang-Min Park,Ho-Sung Lee,Hwang-Yeol Lee,Kwang-Hyun Cho

doi:10.1186/s12918-016-0341-9

Sung-Hwan Cho, Sang-Min Park + Show 3 more

Open Access

https://doi.org/10.1186/s12918-016-0341-9

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Abstract

BackgroundColorectal cancer arises from the accumulation of genetic mutations that induce dysfunction of intracellular signaling. However, the underlying mechanism of colorectal tumorigenesis driven by genetic mutations remains yet to be elucidated.ResultsTo investigate colorectal tumorigenesis at a system-level, we have reconstructed a large-scale Boolean network model of the human signaling network by integrating previous experimental results on canonical signaling pathways related to proliferation, metastasis, and apoptosis. Throughout an extensive simulation analysis of the attractor landscape of the signaling network model, we found that the attractor landscape changes its shape by expanding the basin of attractors for abnormal proliferation and metastasis along with the accumulation of driver mutations. A further hypothetical study shows that restoration of a normal phenotype might be possible by reversely controlling the attractor landscape. Interestingly, the targets of approved anti-cancer drugs were highly enriched in the identified molecular targets for the reverse control.ConclusionsOur results show that the dynamical analysis of a signaling network based on attractor landscape is useful in acquiring a system-level understanding of tumorigenesis and developing a new therapeutic strategy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0341-9) contains supplementary material, which is available to authorized users.

Highlights

Colorectal cancer arises from the accumulation of genetic mutations that induce dysfunction of intracellular signaling
Boolean network model of the large-scale human signaling network To investigate the complex dynamics of intracellular signaling process, we have integrated all relevant information of key proteins and their interaction which are known to have a major role for biological processes from extensive manual curation of literatures and databases such as Kyoto Encyclopedia of Genes and Genomes (KEGG) and PID (Pathway Interaction Database) [16, 17]
The reconstructed human signaling network consists of 197 nodes and 688 directed links, and contains thirteen external-input nodes; extracellular matrix (ECM), epidermal growth factor (EGF), interleukin tumor necrosis factor (IL1_TNF), transforming growth factor-beta (TGFbeta), G protein-coupled receptors (GPCR) ligands, Stress, Wnt, Fas, calcuim pump (Extpump) and DNA damage (Fig. 1 and Additional file 1)

Summary

Introduction

Colorectal cancer arises from the accumulation of genetic mutations that induce dysfunction of intracellular signaling. Tumorigenesis cannot be explained by gene alterations themselves, but is rather becoming perceived as the resulting dysfunction of signaling pathways [1,2,3]. Malfunctioning of some crucial signaling pathway(s) due to genetic mutations can cause tumorigenesis [1, 4]. Continuous variable modeling based on a system of differential equations has often been used, but the estimation of kinetic parameter values limits its use for modeling a large-scale signaling network. To overcome such difficulty, we have employed in this study a Boolean

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