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Modelling of tissue level carcinogenesis through hybrid, biophysical, and executable approaches

Funder: UK Research and InnovationProject code: MC_UU_12022/9
Funded under: MRC Funder Contribution: 869,000 GBP

Modelling of tissue level carcinogenesis through hybrid, biophysical, and executable approaches

Description

Cancer is a major health concern, with one in three adults developing the disease over their lifetime. However, on a cellular level, the probability of a cell developing into a tumour is very low. Cells prevent the development of tumours through a combination of mechanisms, which operate over different scales. Within a single cell, proteins and genes form signalling pathways which reliably interpret and respond to both the cell state and the cell environment, including specific signals passed from other cells. At the same time, within a tissue, the movements and locations of cells can add a further layer of control, by limiting the communication between cells and mixing populations of cells. I will build mathematical representations (a “model”) of the early stages of tumour formation in cancer which bridges these two phenomena. By running simulations using this model, I will learn more about how the signalling and physical components combine to control cell growth and death in the oesophageal epithelium. I will further mutate and wound my model, to explore how these events can cause a breakdown of the controlling mechanisms and lead to tumour growth.

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