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Percolation transition of cooperative mutational effects in colorectal tumorigenesis

Author

Listed:
  • Dongkwan Shin

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Jonghoon Lee

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Jeong-Ryeol Gong

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Kwang-Hyun Cho

    (Korea Advanced Institute of Science and Technology (KAIST))

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.

Suggested Citation

  • Dongkwan Shin & Jonghoon Lee & Jeong-Ryeol Gong & Kwang-Hyun Cho, 2017. "Percolation transition of cooperative mutational effects in colorectal tumorigenesis," Nature Communications, Nature, vol. 8(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01171-6
    DOI: 10.1038/s41467-017-01171-6
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    Cited by:

    1. JungHo Kong & Doyeon Ha & Juhun Lee & Inhae Kim & Minhyuk Park & Sin-Hyeog Im & Kunyoo Shin & Sanguk Kim, 2022. "Network-based machine learning approach to predict immunotherapy response in cancer patients," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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