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Computational Modeling of Signaling Networks pp 87–108Cite as

Modeling miRNA Regulation in Cancer Signaling Systems: miR-34a Regulation of the p53/Sirt1 Signaling Module

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 880))

Abstract

MicroRNAs (miRNAs) are a family of small regulatory RNAs whose function is to regulate the activity and stability of specific messenger RNA targets through posttranscriptional regulatory mechanisms. Most of the times signaling systems involving miRNA modulation are not linear pathways in which a certain transcription factor activate the expression of miRNAs that posttranscriptionally represses targeting proteins, but complex regulatory structures involving a variety of feedback-loop architectures.

In this book chapter, we define, discuss, and apply a Systems Biology approach to investigate dynamical features of miRNA regulation, based on the integration of experimental evidences, hypotheses, and quantitative data through mathematical modeling. We further illustrate the approach using as case study the signaling module composed by the proteins p53, Sirt1, and the regulatory miRNA miR-34a. The model was used not only to investigate different possible designs of the silencing mechanism exerted by miR-34a on Sirt1 but also to simulate the dynamics of the system under conditions of (pathological) deregulation of its compounds.

Olaf Wolkenhauer and Julio Vera contributed equally.

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Acknowledgments

J.V. and X.L. are funded by the German Federal Ministry of Education and Research (BMBF) as part of the project CALSYS-FORSYS under contract 0315264 (www.sbi.uni-rostock.de/calsys). O.W. was supported by the Helmholtz Foundation as part of the Systems Biology Network.

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Authors and Affiliations

  1. Systems Biology and Bioinformatics Group, Department of Computer Science, University of Rostock, Rostock, Germany

    Xin Lai, Olaf Wolkenhauer & Julio Vera

Authors
  1. Xin Lai
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  2. Olaf Wolkenhauer
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  3. Julio Vera
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Corresponding authors

Correspondence to Olaf Wolkenhauer or Julio Vera .

Editor information

Editors and Affiliations

  1. Dept. Chemistry & Biochemistry, University of Colorado, Boulder, Boulder, 80309-0215, Colorado, USA

    Xuedong Liu

  2. Dept. Physics, University of Colorado, Boulder, Boulder, 80309, Colorado, USA

    Meredith D. Betterton

Appendix

Appendix

Table A1 Parameter intervals and values. Top: Estimation intervals for corresponding parameters. Bottom: The parameter values used in the model. The values of kinetic orders (g i ) are fixed and other parameters are estimated. Values and intervals with stars: they are characterized by using biological protein half life. Others are estimated from the published experimental data (22, 34, 35)
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Table A2 Expanded equations of four hypothetical miR-34a silencing mechanisms
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Fig. A1.
figure 1

Interpolation fitting plot of the experimental data regarding the dynamics of DNA damage. Solid line: Model simulation. Square marker: Experimental data.

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Fig. A2.
figure 2

The predictions of different miRNA silencing mechanism. Here we only illustrate the plots of mode 1 and mode 4. Solid lines: The model predictions for the protein (upper line) and mRNA (lower line) of Sirt1. Square markers: Experimental data for the protein (upper square) and mRNA (lower square) of Sirt1.

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Lai, X., Wolkenhauer, O., Vera, J. (2012). Modeling miRNA Regulation in Cancer Signaling Systems: miR-34a Regulation of the p53/Sirt1 Signaling Module. In: Liu, X., Betterton, M. (eds) Computational Modeling of Signaling Networks. Methods in Molecular Biology, vol 880. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-833-7_6

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  • DOI: https://doi.org/10.1007/978-1-61779-833-7_6

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  • Publisher Name: Humana Press, Totowa, NJ

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