SciFest National Final 2023

Stand 6

Metastasis in Silico: Computational Models and Targeted Approaches

Student Vedh Ramalingam Kannan
School Sutton Park School, St Fintan's Road, Sutton, Dublin 13
Teacher Joanne Hanratty
Venue TU Dublin Grangegorman

This project aimed to investigate two potential strategies for combating cancer metastasis. Firstly, the project assessed the feasibility of utilising arginase, an enzyme, to metabolise arginine as a potential treatment, with a specific focus on pancreatic cancer. This was achieved by fitting the Michaelis-Menten model to arginase, using published experimental data to confirm its potential as a therapeutic agent.

Secondly, the project conducted a comprehensive study of the Epidermal Growth Factor Receptor (EGFR) signalling pathway, exploring solutions such as ligand removal and tyrosine kinase (TK) inhibition. A biological model of EGFR dimerisation was developed using the BioNetGen Language (BNGL), and simulation data was analysed using Python. These simulations provided insights into how dimerisation dynamics change under varying ligand concentrations. Additionally, the project identified phosphohistidine as a potential candidate for inhibiting DNA transcription in cancer cells, given its ability to prevent tyrosine phosphorylation.

Furthermore, the project delved into the potential of novel delivery methods, including extracellular contractile injection systems (eCIS) and DNA origami, assessing their effectiveness through computational analysis.

Overall, this project aims to contribute valuable insights into cancer metastasis and potential treatment strategies, with applications in advancing precision cancer therapies.


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SciFest National Final 2023
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