Revealing the role of the dynamics of transcriptional regulators on radiotherapy-induced cell state transitions in glioblastoma

Primary supervisor: Jamie Dean, University College London 
Secondary supervisor: Silvia Marino, Queen Mary University of London

Project

Glioblastoma is the most common and aggressive primary malignant brain tumour in adults with a median overall survival of 15 months. Glioblastomas exhibit marked intra-tumour heterogeneity, with tumours consisting of cells in different transcriptional states resembling different brain cell states in development and injury response. However, unlike in normal brain development, glioblastoma cells are highly plastic, readily transitioning between states in response to stimuli, including radiotherapy, a standard-of-care therapy for glioblastoma. Current treatment strategies fail to account for this heterogeneity and plasticity. Understanding the molecular mechanisms governing radiotherapy-induced cell state transitions in glioblastoma would enable the design of novel treatment strategies, pharmacologically manipulating cell state transitions [1] to steer cells into more radiotherapy-sensitive states, thus representing an opportunity to improve patient outcome.

In normal brain development, cell state transitions are regulated by changes in the dynamics of lineage specifying transcription factors and epigenetic regulators, such as HES1, ASCL1, OLIG2 [2] and the PRC2 complex. Oscillations in the levels of these factors maintain cells in a multipotent progenitor state, while sustained activation or inactivation of these factors induces differentiation. Given that glioblastoma co-opts normal brain development programmes, we hypothesise that the dynamics of these transcriptional regulators underlie glioma cell state plasticity, including radiotherapy-induced transitions of cells into treatment resistant states.

In this project, we will reveal how the dynamics of transcriptional regulators control cell state transitions in glioblastoma and use this knowledge to propose new drug-radiotherapy combinations that modulate these transitions to steer cells into radiosensitive states:

Reveal transcription factor dynamics associated with cell state transitions in patient-matched glioblastoma and normal brain cells

To understand cell state transitions, their association with radiotherapy resistance and their transcriptional regulation in human glioblastoma, we will employ the SYNGLICO [3] system, a 3D co-culture model of glioblastoma cells within a syngeneic cerebral organoid [4], developed by the Marino Lab, to perform single cell transcriptomics in response to radiotherapy. We will use computational algorithms to infer cell state transitions and differences in the expression levels and dynamics of genes (including oscillatory dynamics) and their transcriptional regulators, comparing between glioma and patient-matched normal brain cells in untreated and radiotherapy-treated conditions.

Quantitatively characterise the dynamics of key transcriptional regulators controlling transition of cells into radiotherapy resistant states

To visualise the dynamics of key transcriptional regulators associated with the transition of cells into radiotherapy resistant states, we will develop fluorescent reporter lines and image them with timelapse microscopy. Machine learning-based cell segmentation and tracking will be performed to extract quantitative data of the transcriptional regulator dynamics. We will use the data to develop mathematical models [5] quantitatively characterising the transcriptional regulator dynamics.

Manipulate the dynamics of key transcriptional regulators to steer cells into radiosensitive states

Finally, we will use our mathematical models to perform in silico perturbation, proposing molecular targets for pharmacological manipulation of the dynamics of the transcriptional regulators to steer cells into radiosensitive states. We will evaluate the efficacy of these novel drug-radiotherapy combinations in the SYNGLICO system.

Candidate background

This multidisciplinary project would suit candidates with a background in experimental and computational biology and an interest in neuro-oncology

Potential Research Placements

1. Samuel Marguerat, University College London
2. Kurt Anderson,  The Francis Crick Institute
3. Karen Page, University College London

References

1. Dean, J.A., Tanguturi, S.K., Cagney, D., Shin, K.-Y., Youssef, G., Aizer, A., Rahman, R., Hammoudeh, L., Reardon, D., Lee, E., et al. (2023). Phase I study of a novel glioblastoma radiation therapy schedule exploiting cell-state plasticity. Neuro-Oncol. 25, 1100–1112. https://doi.org/10.1093/neuonc/noac253.
2. Imayoshi, I., Isomura, A., Harima, Y., and Kawaguchi, K. (2013). Oscillatory control of determination factors for multipotency versus fate choice in mouse neural progenitors. Science 342, 1203–1208. https://doi.org/10.1126/science.1242366.
3. Vinel, C., Rosser, G., Guglielmi, L., Constantinou, M., Pomella, N., Zhang, X., Boot, J.R., Jones, T.A., Millner, T.O., Dumas, A.A., et al. (2021). Comparative epigenetic analysis of tumour initiating cells and syngeneic EPSC-derived neural stem cells in glioblastoma. Nat. Commun. 12, 1–20. https://doi.org/10.1038/s41467-021-26297-6.
4. Millner, T., Panday, P., Xiao, Y., Boot, J., Nicholson, J., Arpe, Z., Stevens, P., Rahman, N., Zhang, X., Mein, C., et al. (2024). The inflammatory micro-environment induced by targeted CNS radiotherapy is underpinned by disruption of DNA methylation. bioRxiv. https://doi.org/10.1101/2024.03.04.581366.
5. Dean, J.A., Reyes, J., Tsabar, M., Jambhekar, A., Lahav, G., and Michor, F. (2024). Functional consequences of a p53-MDM2-p21 incoherent feedforward loop. bioRxiv. https://doi.org/10.1101/2024.06.25.600070