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Abstract B2-29: The reverse control of colorectal tumorigenesis based on Boolean network modeling of human signaling network

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Abstract The intracellular processes are governed by a signal transduction network composed of complex interactions of a number of signaling proteins and various human diseases including cancer are known to be caused by the rewiring of the complex signaling network owing to the individual genetic mutations. There have been many studies on the dynamical analysis of the human signaling network to investigate the progression mechanism of human diseases, but most of the results were limited to small-scale signaling pathways. In this study, we have reconstructed a large-scale signaling network model composed of 197 nodes and 745 relations based on Boolean modeling and performed attractor landscape analysis to uncover the mechanism of colorectal tumorigenesis caused by driver mutations. In addition, we have investigated the reverse control of tumorigenesis by changing the attractor landscape of colorectal cancer state that has been deformed by the driver mutations. Our results show that colorectal tumorigenesis can occur by the expansion of the cancer attractor basin due to the accumulation of driver mutations. We found a minimal control set of network components that can reverse the cancerous state into a normal state. Together, these results suggest a new therapeutic strategy for the treatment of colorectal cancer and provide a new insight into the drug target excavation. Acknowledgement: This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea Government, the Ministry of Science, ICT & Future Planning (2014R1A2A1A10052404, 2013M3A9A7046303, and 2010-0017662). Citation Format: Cho Sung-Hwan, Park Sang-Min, Lee Ho-Sung, Lee Hwang-Yeol, Cho Kwang-Hyun. The reverse control of colorectal tumorigenesis based on Boolean network modeling of human signaling network. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-29.
Title: Abstract B2-29: The reverse control of colorectal tumorigenesis based on Boolean network modeling of human signaling network
Description:
Abstract The intracellular processes are governed by a signal transduction network composed of complex interactions of a number of signaling proteins and various human diseases including cancer are known to be caused by the rewiring of the complex signaling network owing to the individual genetic mutations.
There have been many studies on the dynamical analysis of the human signaling network to investigate the progression mechanism of human diseases, but most of the results were limited to small-scale signaling pathways.
In this study, we have reconstructed a large-scale signaling network model composed of 197 nodes and 745 relations based on Boolean modeling and performed attractor landscape analysis to uncover the mechanism of colorectal tumorigenesis caused by driver mutations.
In addition, we have investigated the reverse control of tumorigenesis by changing the attractor landscape of colorectal cancer state that has been deformed by the driver mutations.
Our results show that colorectal tumorigenesis can occur by the expansion of the cancer attractor basin due to the accumulation of driver mutations.
We found a minimal control set of network components that can reverse the cancerous state into a normal state.
Together, these results suggest a new therapeutic strategy for the treatment of colorectal cancer and provide a new insight into the drug target excavation.
Acknowledgement: This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea Government, the Ministry of Science, ICT & Future Planning (2014R1A2A1A10052404, 2013M3A9A7046303, and 2010-0017662).
Citation Format: Cho Sung-Hwan, Park Sang-Min, Lee Ho-Sung, Lee Hwang-Yeol, Cho Kwang-Hyun.
The reverse control of colorectal tumorigenesis based on Boolean network modeling of human signaling network.
[abstract].
In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA.
Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-29.

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