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A Theoretical Study of the MYCN Enigma in Neuroblastoma
The MYCN gene is frequently amplified in neuroblastoma cells: a strong predictor of adverse outcomes. However, high MYCN expression is associated with both favourable and adverse outcomes, perhaps because of its interactions with the ARF/MDM2/p53 axis.
While working on PRIMAGE, I conceived this project to find an explanation for MYCN's enigmatic behaviour in neuroblastoma cells. In order to fund it, I secured two Insigneo research grants.
Mathematical Modelling
In the summer of 2019, I recruited Daniel Jordan, a mechatronics and robotics engineering undergraduate student, to work on the project at the University of Sheffield. Together, we used a set of ordinary differential equations to model the crosstalk between MYCN and the ARF/MDM2/p53 axis, and performed basic analysis on the fixed points.
In the academic year 2019–2020, Melody Parker, an MSc computational medicine student at the University of Sheffield, joined the project for her dissertation research. Under the supervision of Doctor Dawn Walker and myself, she picked up where Dan had left off, enriching the model with mechanistic details about different points in the flow of genetic information, including gene amplification, transcription, mRNA degradation, translation, and protein degradation. Using equations containing highly nonlinear terms such as the Hill function, she modelled the dynamics within and between these layers of regulation.
Phase Space Analysis
In the summer of 2021, Rory Deignan, an undergraduate (theoretical physics) at the University of Sheffield, built computational tools for a large-scale stability analysis of the model. He combined Latin hypercube sampling with the Newton-Raphson algorithm to find physical and well-scaled fixed points. He developed a heuristic to classify each fixed point by stability and phenotype (p53 and MYCN expression levels). He also explored spectral and fractal analysis.
In 2023, I recruited Matteo Italia, Dr Fabio Dercole's PhD candidate at the Polytechnic University of Milan. We hypothesised that the abundance of p53 (tumour suppressor gene) relative to that of MYCN (oncogene) is the determinant of a neuroblastoma cell's fate. We parameterised the model with literature values before conducting a global sensitivity analysis to match the hypothesis with experimental findings. We applied the Apriori algorithm to find association rules in the resulting data.
