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A Theoretical Study of Evolutionary Therapy for Neuroblastoma
Evolutionary therapy exploits the evolutionary dynamics within a tumour comprising subpopulations with different combinations of mutations. An example is adaptive therapy, which uses treatment-sensitive cancer cells to suppress their resistant peers. This project aims to investigate evolutionary therapy in the context of neuroblastoma.
Together with Dr Matishalin Patel, an expert in evolutionary biology and a departmental colleague at the University of Hull, I applied for and secured a DAIM PhD studentship after a competitive process. In January 2024, Francesca Covell became our first PhD candidate (AI and Data Science). An international collaboration with Dr Sabine Taschner-Mandl from St. Anna Children's Cancer Research Institute was established.
Neuroblastoma's phenotypic plasticity is an important factor in the context of evolutionary therapy. In her first year as a PhD candidate, Fran built and validated a dynamic model describing neuroblastoma cells' interconversion between the noradrenergic, intermediate, and mesenchymal cell states. Noradrenergic neuroblastoma cells are typically more sensitive to treatment (like ALK inhibitors), but Dr Taschner-Mandl has experimented with mesenchymal phenotype–specific inhibitors.
Fran is now investigating the effects of all 64 interconversion patterns on both types of inhibitors. She has generated a comprehensive dataset by solving initial value problems and conducting stability analysis numerically. Based on it, she is designing strategies to steer a tumour's evolution towards vulnerable states by altering its interconversion dynamics.
