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Metastable Regimes and Tipping Points of Biochemical Networks with Potential Applications in Precision Medicine

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Automated Reasoning for Systems Biology and Medicine

Part of the book series: Computational Biology ((COBO,volume 30))

Abstract

The concept of attractor of dynamic biochemical networks has been used to explain cell types and cell alterations in health and disease. We have recently proposed an extension of the notion of attractor to take into account metastable regimes, defined as long-lived dynamical states of the network. These regimes correspond to slow dynamics on low- dimensional invariant manifolds of the biochemical networks. Methods based on tropical geometry allow to compute the metastable regimes and represent them as polyhedra in the space of logarithms of the species concentrations. We are looking for sensitive parameters and tipping points of the networks by analyzing how these polyhedra depend on the model parameters. Using the coupled MAPK and PI3K/Akt signaling networks as an example, we test the idea that large changes of the metastable states can be associated with cancer-specific alterations of the network. In particular, we show that for model parameters representing protein concentrations, the protein differential level between tumors of different types is reasonably reflected in the sensitivity scores, with sensitive parameters corresponding to differential proteins.

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Acknowledgements

This work was supported by the ANR/DFG grant ANR-17-CE40-0036 (project SYMBIONT) and CompSE profile area, RWTH Aachen University. We thank R. Larive and D. Santamaria for their critical reading of the manuscript and for useful discussions.

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Authors and Affiliations

  1. Joint Research Center for Computational Biomedicine, RWTH Aachen University, Aachen, Germany

    Satya Swarup Samal & Ali Hadizadeh Esfahani

  2. BASF SE, Carl-Bosch-Straße 38, 67056, Ludwigshafen, Germany

    Satya Swarup Samal & Ali Hadizadeh Esfahani

  3. AICES Graduate School, RWTH Aachen University, Aachen, Germany

    Jeyashree Krishnan

  4. Department of Computer Science II, University of Bonn, Bonn, Germany

    Christoph Lüders & Andreas Weber

  5. DIMNP UMR CNRS 5235, University of Montpellier, Montpellier, France

    Ovidiu Radulescu

Authors
  1. Satya Swarup Samal
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  2. Jeyashree Krishnan
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  3. Ali Hadizadeh Esfahani
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  4. Christoph Lüders
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  5. Andreas Weber
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  6. Ovidiu Radulescu
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Correspondence to Ovidiu Radulescu .

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Editors and Affiliations

  1. Department of Computer Science and Technology, University of Cambridge, Cambridge, UK

    Pietro Liò

  2. School of Computing, Newcastle University, Newcastle, UK

    Paolo Zuliani

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Samal, S.S., Krishnan, J., Esfahani, A.H., Lüders, C., Weber, A., Radulescu, O. (2019). Metastable Regimes and Tipping Points of Biochemical Networks with Potential Applications in Precision Medicine. In: Liò, P., Zuliani, P. (eds) Automated Reasoning for Systems Biology and Medicine. Computational Biology, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-17297-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-17297-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17296-1

  • Online ISBN: 978-3-030-17297-8

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