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Mechanistic Insights into Astrocytes Dedifferentiation during Glioblastoma Tumorigenesis using Executable Modelling

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  • Full or part time
    Prof J Fisher
    Prof S Parrinello
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Glioblastoma multiforme (GBM) is both the most common and the most lethal adult brain tumour. GBM malignancy and recurrence are driven by a subpopulation of stem-like cells known as glioma stem cells (GSC). Yet the cellular origin of GSCs remains unknown. One possible origin is from differentiated glia such as astrocytes acquiring mutations which allow them to dedifferentiate to stem-like state. It had been thought that this would require multiple mutations [1], but recent results from the Parrinello lab show that a p53 mutation
alone in the context of inflammatory microenvironmental signalling, is sufficient to cause astrocyte dedifferentiation both in vitro and in vivo [2]. This presents a potential source of tumourigenesis in the adult brain. However, the precise mechanism by which p53 mutation causes this loss of cellular identity is still unknown.

Interestingly, emerging evidence indicates that radiotherapy, the standard of care for GBM patients, may also promote dedifferentiation [3,4]. This suggests that radiation may further enhance the plasticity of p53-mutant astrocytes and thereby support recurrence. Understanding the molecular basis of astrocyte dedifferentiation and its interplay with radiation is therefore essential for understanding GBM aetiology and mechanisms of resistance.

Cell behaviour, both healthy and diseased, can only rarely be reduced to the direct influence of one gene. Rather, it is the network of interactions between genes that determine the responses of a cell to internal and external stimuli. The Fisher lab applies concepts from Computer Science ‒ such as model checking [5] and model synthesis [6] ‒ to cope with this irreducible complexity through computational simulation and analysis of the large datasets involved. We model cell fate decisions as executable programs [7,8] using a computational tool called Bio Model Analyzer (BMA), which was designed specifically for modelling biological networks [9].

The aim of this PhD project, is to build, test, and analyse an executable model of the signalling pathways involved in astrocyte dedifferentiation in tumour initiation and following radiation. The model will include the RTK signalling, cell cycle machinery and DDR pathways. In parallel, the response of p53-/- astrocytes to radiation will be assessed in vitro and in vivo in the Parrinello lab. Together, this work will provide key insights into the
molecular basis of GBM initiation and recurrence and hopefully pave the way for improved and personalised treatments leading to better outcome for GBM patients. The computational work will be conducted in the Fisher lab in close collaboration with the Parrinello lab where the experimental validation work will be carried out. In addition, we will be collaborating closely with Dr Michael Kosmin who will provide the clinical lead.

The ideal candidate for this PhD project would have an enthusiasm for computational biology and a strong interest in cancer biology. They should have a background in mathematical, computational and statistical analysis, and a First or Upper Second undergraduate degree in a relevant field (e.g., Computer Science, Engineering, Physics, Biology). Experience in programming, such as R or Python, is desirable. Excellent communication skills and the ability to work in a multidisciplinary team are essential.

The successful candidate should have experience in cancer cell biology and a BSc in a relevant subject. For further details on how to apply please visit the CRUK CoL Centre RadNet studentships page:

Potential research placements

1. Computational modelling: Fisher lab, UCL Cancer Institute
2. Wet lab experience: Parrinello lab, UCL Cancer Institute
3. Clinical background on GBM: Dr Michael Kosmin, Consultant Clinical Oncologist, UCLH and Dr Rachel Lewis, Consultant Clinical Oncologist and Clinical Lead for Neuro-Oncology, St Bartholomew’s Hospital.

Funding Notes

Due to funding restrictions only UK / EU candidates are eligible to apply


1. Friedmann-Morvinski, D. et al. Dedifferentiation of Neurons and Astrocytes by Oncogenes Can Induce Gliomas in Mice, Science 338, 1080-1084, 2012.

2. Simpson Ragdale, H. et al. p53 Restricts Injury-Induced Plasticity in Cortical Astrocytes, in preparation.

3. Lee, G. et al. Dedifferentiation of Glioma Cells to Glioma Stem-like Cells By Therapeutic Stress-induced HIF Signaling in the Recurrent GBM Model. Mol Cancer Ther 15(12):3064-3076, 2016.

4. Dahan, P. et al. Ionizing Radiations Sustain Glioblastoma Cell Dedifferentiation to a Stem-like Phenotype through Survivin: Possible Involvement in Radioresistance, Cell Death Dis 27;5:e1543, 2014.

5. Silverbush, D. et al. Cell-Specific Computational Modelling of the PIM Pathway in Acute Myeloid Leukaemia, Cancer Research 77(4), 2017.

6. Moignard, V. et al., Decoding the Transcriptional Program for Blood Development from Whole Tissue Single Cell Gene Expression Measurements, Nature Biotechnology, 33:269-276, 2015.

7. J. Fisher and T. A. Henzinger, Executable Cell Biology, Nature Biotechnology, 25(11):1239-49, 2007.

8. Kreuzaler, P. et al. Heterogeneity of Myc expression in breast cancer exposes pharmacological
vulnerabilities revealed through executable mechanistic modelling, Proc. Natl. Acad. Sci. 116, 22399-22408, 2019.

9. Bio Model Analyzer tool:

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