Innovative computational approaches to understand and counteract mechanisms of radiation-induced DNA damage response

As cancer therapy becomes more targeted, patient responses become more diverse. We therefore require deeper understanding of the gene regulatory mechanisms underlying cancer in order to assess treatment effectiveness and personalise therapy. 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 formal verification to cope with this irreducible complexity through computational integration, simulation and analysis of the large datasets involved. We are currently building a computational model of the gene regulatory network underpinning the DNA damage response (DDR) in healthy and cancerous cells.We are using a computational tool called BioModelAnalyzer, which was designed specifically for modelling biological networks,to better model individual responses to treatment and better tailor therapy to individual patients. Our computational modelling will allow us to both learn from, and predict the response to radiotherapy, chemotherapy, targeted drugs and their combinations; not only at the level of overall response, but also in terms of the changes in the signalling pathways that determine the response. This will allow us to shed light on the mechanisms that dictate the difference between successful and unsuccessful interventions,as well as to find better signatures of sensitive versus resistant tumours. Such signatures can inform clinicians whether a therapy is working or not, much faster than existing methods that rely on detectable changes in tumour volume. Furthermore, we can computationally screen for the most effective combinations of therapies as well as for those which have the largest difference in their effect on healthy vs cancerous cells; the largest therapeutic window.Finally, we can search for resistance mutations to such therapies to predict the evolution of the tumour and how therapy can be adapted to pre-empt resistance.

The collaboration with Dr O’Connor’s DDR group at AstraZeneca will allow access to data already generated on the radiation response of a number of lung cancer models where pre and post radiation gene expression analysis will be assessed as well as access to multiple DDR inhibitors that cover all the main DNA response pathways to radiation-induced DNA damage. These data would be extended in the project to both increase the number of lung models as well as generating data for both a breast cancer and glioblastoma cohort of models. All data can be used to build the computational model for radiation response, particularly resistance. In addition, the Cambridge RadNet consortium,that includes both Drs Fisher and O’Connor,will be generating data on CRISPR knockout induction of radiation resistance in KRAS mutant lung cancer models which will compliment and be used to extend our understanding of DDR-related radiation resistance in this disease setting.

The aim of this PhD project is therefore to develop, train, and analyse a computational model of the signalling pathways involved in DDR, and to extend and enhance this model to be able to give mechanistic insights into the unique aspects of different tumour types such as lung, breast and glioblastoma. The ideal candidate for this PhD project would have an enthusiasm for computational biology and a strong interest in cancer biology. Background in mathematical, computational and statistical analysis is an advantage. Experience in programming, such as R or Python, is desirable. Excellent communication skills and the ability to work in a multidisciplinary team across academia and industry are essential.

For details on how to apply please visit: https://www.colcc.ac.uk/crtf-recruitment-process/

For any informal enquiries on the project please contact Prof Jasmin Fisher: [Email Address Removed]

For any enquiries on the CRUK CoL Centre programme please contact Annabelle Scott: [Email Address Removed]