Dataset Information

Percolation transition of cooperative mutational effects in colorectal tumorigenesis.

ABSTRACT: Cancer is caused by the accumulation of multiple genetic mutations, but their cooperative effects are poorly understood. Using a genome-wide analysis of all the somatic mutations in colorectal cancer patients in a large-scale molecular interaction network, here we find that a giant cluster of mutation-propagating modules in the network undergoes a percolation transition, a sudden critical transition from scattered small modules to a large connected cluster, during colorectal tumorigenesis. Such a large cluster ultimately results in a giant percolated cluster, which is accompanied by phenotypic changes corresponding to cancer hallmarks. Moreover, we find that the most commonly observed sequence of driver mutations in colorectal cancer has been optimized to maximize the giant percolated cluster. Our network-level percolation study shows that the cooperative effect rather than any single dominance of multiple somatic mutations is crucial in colorectal tumorigenesis.

SUBMITTER: Shin D

PROVIDER: S-EPMC5668266 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Percolation transition of cooperative mutational effects in colorectal tumorigenesis.

Shin Dongkwan D Lee Jonghoon J Gong Jeong-Ryeol JR Cho Kwang-Hyun KH

Nature communications 20171102 1

Cancer is caused by the accumulation of multiple genetic mutations, but their cooperative effects are poorly understood. Using a genome-wide analysis of all the somatic mutations in colorectal cancer patients in a large-scale molecular interaction network, here we find that a giant cluster of mutation-propagating modules in the network undergoes a percolation transition, a sudden critical transition from scattered small modules to a large connected cluster, during colorectal tumorigenesis. Such ...[more]

PMID: 29097710

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Project description:From the perspective of systems science, tumorigenesis can be hypothesized as a critical transition (an abrupt shift from one state to another) between proliferative and apoptotic attractors on the state space of a molecular interaction network, for which an attractor is defined as a stable state to which all initial states ultimately converge, and the region of convergence is called the basin of attraction. Before the critical transition, a cellular state might transit between the basin of attraction for an apoptotic attractor and that for a proliferative attractor due to the noise induced by the inherent stochasticity in molecular interactions. Such a flickering state transition (state transition between the basins of attraction for alternative attractors from the impact of noise) would become more frequent as the cellular state approaches near the boundary of the basin of attraction, which can increase the variation in the estimate of the respective basin size. To investigate this for colorectal tumorigenesis, we have constructed a stochastic Boolean network model of the molecular interaction network that contains an important set of proteins known to be involved in cancer. In particular, we considered 100 representative sequences of 20 gene mutations that drive colorectal tumorigenesis. We investigated the appearance of cancerous cells by examining the basin size of apoptotic, quiescent, and proliferative attractors along with the sequential accumulation of gene mutations during colorectal tumorigenesis. We introduced a measure to detect the flickering state transition as the variation in the estimate of the basin sizes for three-phenotype attractors from the impact of noise. Interestingly, we found that this measure abruptly increases before a cell becomes cancerous during colorectal tumorigenesis in most of the gene mutation sequences under a certain level of stochastic noise. This suggests that a frequent flickering state transition can be a precritical phenomenon of colorectal tumorigenesis.

Project description:Shortly after mixing cement grains with water, a cementitious fluid paste is formed that immediately transforms into a solid form by a phenomenon known as setting. Setting actually corresponds to the percolation of emergent network structures consisting of dissolving cement grains glued together by nanoscale hydration products, mainly calcium-silicate-hydrates. As happens in many percolation phenomena problems, the theoretical identification of the percolation threshold (i.e. the cement setting) is still challenging, since the length scale where percolation becomes apparent (typically the length of the cement grains, microns) is many times larger than the nanoscale hydrates forming the growing spanning network. Up to now, the long-lasting gap of knowledge on the establishment of a seamless handshake between both scales has been an unsurmountable obstacle for the development of a predictive theory of setting. Herein we present a true multi-scale model which concurrently provides information at the scale of cement grains (microns) and at the scale of the nano-hydrates that emerge during cement hydration. A key feature of the model is the recognition of cement setting as an off-lattice bond percolation process between cement grains. Inasmuch as this is so, the macroscopic probability of forming bonds between cement grains can be statistically analysed in smaller local observation windows containing fewer cement grains, where the nucleation and growth of the nano-hydrates can be explicitly described using a kinetic Monte Carlo Nucleation and Growth model. The most striking result of the model is the finding that only a few links (~12%) between cement grains are needed to reach setting. This directly unveils the importance of explicitly including nano-texture on the description of setting and explains why so low amount of nano-hydrates is needed for forming a spanning network. From the simulations, it becomes evident that this low amount is least affected by processing variables like the water-to-cement ratio and the presence of large quantities of nonreactive fillers. These counter-intuitive predictions were verified by ex-professo experiments that we have carried out to check the validity of our model.

Dataset Information

Percolation transition of cooperative mutational effects in colorectal tumorigenesis.

Publications

Percolation transition of cooperative mutational effects in colorectal tumorigenesis.

Similar Datasets

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