The role of stochastic gene switching in determining the pharmacodynamics of certain drugs: basic mechanisms View Full Text


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Article Info

DATE

2016-06-28

AUTHORS

Krzysztof Puszynski, Alberto Gandolfi, Alberto d’Onofrio

ABSTRACT

In this paper we analyze the impact of the stochastic fluctuation of genes between their ON and OFF states on the pharmacodynamics of a potentially large class of drugs. We focus on basic mechanisms underlying the onset of in vitro experimental dose-response curves, by investigating two elementary molecular circuits. Both circuits consist in the transcription of a gene and in the successive translation into the corresponding protein. Whereas in the first the activation/deactivation rates of the single gene copy are constant, in the second the protein, now a transcription factor, amplifies the deactivation rate, so introducing a negative feedback. The drug is assumed to enhance the elimination of the protein, and in both cases the success of therapy is assured by keeping the level of the given protein under a threshold for a fixed time. Our numerical simulations suggests that the gene switching plays a primary role in determining the sigmoidal shape of dose-response curves. Moreover, the simulations show interesting phenomena related to the magnitude of the average gene switching time and to the drug concentration. In particular, for slow gene switching a significant fraction of cells can respond also in the absence of drug or with drug concentrations insufficient for the response in a deterministic setting. For higher drug concentrations, the non-responding fraction exhibits a maximum at intermediate values of the gene switching rates. For fast gene switching, instead, the stochastic prediction follows the prediction of the deterministic approximation, with all the cells responding or non-responding according to the drug dose. More... »

PAGES

395-410

References to SciGraph publications

  • 2008-07-17. Quantification of mRNA in single cells and modelling of RT-qPCR induced noise in BMC MOLECULAR AND CELL BIOLOGY
  • 2000-11. Surfing the p53 network in NATURE
  • 2014-11-21. Piecewise Deterministic Markov Processes in Biological Models in SEMIGROUPS OF OPERATORS -THEORY AND APPLICATIONS
  • 2005-02. Using Stochastic Differential Equations for PK/PD Model Development in JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS
  • 2008-06-02. Activation of p53 by nutlin leads to rapid differentiation of human embryonic stem cells in ONCOGENE
  • 2005-05-10. Stochasticity in gene expression: from theories to phenotypes in NATURE REVIEWS GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10928-016-9480-2

    DOI

    http://dx.doi.org/10.1007/s10928-016-9480-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1009961091

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27352096


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