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MiR-192-Mediated Positive Feedback Loop Controls the Robustness of Stress-Induced p53 Oscillations in Breast Cancer Cells

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  • Richard Moore
  • Hsu Kiang Ooi
  • Taek Kang
  • Leonidas Bleris
  • Lan Ma

Abstract

The p53 tumor suppressor protein plays a critical role in cellular stress and cancer prevention. A number of post-transcriptional regulators, termed microRNAs, are closely connected with the p53-mediated cellular networks. While the molecular interactions among p53 and microRNAs have emerged, a systems-level understanding of the regulatory mechanism and the role of microRNAs-forming feedback loops with the p53 core remains elusive. Here we have identified from literature that there exist three classes of microRNA-mediated feedback loops revolving around p53, all with the nature of positive feedback coincidentally. To explore the relationship between the cellular performance of p53 with the microRNA feedback pathways, we developed a mathematical model of the core p53-MDM2 module coupled with three microRNA-mediated positive feedback loops involving miR-192, miR-34a, and miR-29a. Simulations and bifurcation analysis in relationship to extrinsic noise reproduce the oscillatory behavior of p53 under DNA damage in single cells, and notably show that specific microRNA abrogation can disrupt the wild-type cellular phenotype when the ubiquitous cell-to-cell variability is taken into account. To assess these in silico results we conducted microRNA-perturbation experiments in MCF7 breast cancer cells. Time-lapse microscopy of cell-population behavior in response to DNA double-strand breaks, together with image classification of single-cell phenotypes across a population, confirmed that the cellular p53 oscillations are compromised after miR-192 perturbations, matching well with the model predictions. Our study via modeling in combination with quantitative experiments provides new evidence on the role of microRNA-mediated positive feedback loops in conferring robustness to the system performance of stress-induced response of p53.Author Summary: DNA damage triggered activities of the tumor suppressor protein p53 could be significantly dynamical. The functional role of p53 oscillations in cellular decision making during cancer development has been appreciated. A set of recent studies have revealed extensive crosstalk between the p53 network and microRNAs, but the specifics of the participation of microRNAs in the regulation of the p53 signaling pathway remains largely elusive. Here we investigated microRNAs that form feedback regulation with p53. We enumerated the molecular interactions among these microRNAs and the p53 core and developed a mathematical model to reproduce the DNA damage induced p53 oscillations in single cells. We performed computer simulations and system analysis in combination with experimental assessment to probe the behavior of p53 under microRNA-inhibited conditions. We show that the robust cellular performance of the stress response of p53 in a breast cancer cell line is controlled by miR-192, which forms positive feedback loops with p53.

Suggested Citation

  • Richard Moore & Hsu Kiang Ooi & Taek Kang & Leonidas Bleris & Lan Ma, 2015. "MiR-192-Mediated Positive Feedback Loop Controls the Robustness of Stress-Induced p53 Oscillations in Breast Cancer Cells," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-17, December.
  • Handle: RePEc:plo:pcbi00:1004653
    DOI: 10.1371/journal.pcbi.1004653
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    References listed on IDEAS

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    1. Tingzhe Sun & Weiwei Yang & Jing Liu & Pingping Shen, 2011. "Modeling the Basal Dynamics of P53 System," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-9, November.
    2. Bharath Ananthasubramaniam & Hanspeter Herzel, 2014. "Positive Feedback Promotes Oscillations in Negative Feedback Loops," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-11, August.
    3. Jae Kyoung Kim & Trachette L Jackson, 2013. "Mechanisms That Enhance Sustainability of p53 Pulses," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
    4. Johan Paulsson, 2004. "Summing up the noise in gene networks," Nature, Nature, vol. 427(6973), pages 415-418, January.
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