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Crosstalk Between Plk1, P53, Cell Cycle, and G2/M Dna Damage Checkpoint Regulation in Cancer: Computational Modeling and Analysis Publisher Pubmed



Jung Y1 ; Kraikivski P2 ; Shafiekhani S3 ; Terhune SS4, 5 ; Dash RK1, 5, 6
Authors
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Authors Affiliations
  1. 1. Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, 53226, WI, United States
  2. 2. Academy of Integrated Science, Division of Systems Biology, Virginia Tech, Blacksburg, 24061, VA, United States
  3. 3. Department of Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Departments of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, 53226, WI, United States
  5. 5. Center of Systems and Molecular Medicine, Medical College of Wisconsin, Milwaukee, 53226, WI, United States
  6. 6. Department of Physiology, Medical College of Wisconsin, Milwaukee, 53226, WI, United States

Source: npj Systems Biology and Applications Published:2021


Abstract

Different cancer cell lines can have varying responses to the same perturbations or stressful conditions. Cancer cells that have DNA damage checkpoint-related mutations are often more sensitive to gene perturbations including altered Plk1 and p53 activities than cancer cells without these mutations. The perturbations often induce a cell cycle arrest in the former cancer, whereas they only delay the cell cycle progression in the latter cancer. To study crosstalk between Plk1, p53, and G2/M DNA damage checkpoint leading to differential cell cycle regulations, we developed a computational model by extending our recently developed model of mitotic cell cycle and including these key interactions. We have used the model to analyze the cancer cell cycle progression under various gene perturbations including Plk1-depletion conditions. We also analyzed mutations and perturbations in approximately 1800 different cell lines available in the Cancer Dependency Map and grouped lines by genes that are represented in our model. Our model successfully explained phenotypes of various cancer cell lines under different gene perturbations. Several sensitivity analysis approaches were used to identify the range of key parameter values that lead to the cell cycle arrest in cancer cells. Our resulting model can be used to predict the effect of potential treatments targeting key mitotic and DNA damage checkpoint regulators on cell cycle progression of different types of cancer cells. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.