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Phenotypic selection through cell death: Stochastic modelling of O-6-methylguanine-DNA methyltransferase dynamics:

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posted on 21.01.2022, 17:58 authored by Ayoub Lasri DoukkaliAyoub Lasri Doukkali, Viktorija Juric, Maité Verreault, Franck Bielle, Ahmed Idbaih, Alexander Kel, Brona MurphyBrona Murphy, Marc SturrockMarc Sturrock
Glioblastoma (GBM) is the most aggressive malignant primary brain tumour with a median overall survival of 15 months. To treat GBM, patients currently undergo a surgical resection followed by exposure to radiotherapy and concurrent and adjuvant temozolomide (TMZ) chemotherapy. However, this protocol often leads to treatment failure, with drug resistance being the main reason behind this. To date, many studies highlight the role of O-6-methylguanine-DNA methyltransferase (MGMT) in conferring drug resistance. The mechanism through which MGMT confers resistance is not well studied - particularly in terms of computational models. With only a few reasonable biological assumptions, we were able to show that even a minimal model of MGMT expression could robustly explain TMZ-mediated drug resistance. In particular, we showed that for a wide range of parameter values constrained by novel cell growth and viability assays, a model accounting for only stochastic gene expression of MGMT coupled with cell growth, division, partitioning and death was able to exhibit phenotypic selection of GBM cells expressing MGMT in response to TMZ. Furthermore, we found this selection allowed the cells to pass their acquired phenotypic resistance onto daughter cells in a stable manner (as long as TMZ is provided). This suggests that stochastic gene expression alone is enough to explain the development of chemotherapeutic resistance.


European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ITN initiative (grant no. 766069)



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Published Citation

Lasri A. et al. Phenotypic selection through cell death: stochastic modelling of O-6-methylguanine-DNA methyltransferase dynamics. R Soc Open Sci. 2020;7(7):191243

Publication Date

8 July 2020

PubMed ID



  • Physiology and Medical Physics

Research Area

  • Cancer


Royal Society Publishing


  • Published Version (Version of Record)