In-Silico Modelling of Phenotypic Switching in Tumours: Investigating Potentials for Non-invasive Therapies

摘要

We developed an in-silico model of cancer growth to investigate the extent to which metabolic switching occurs in tumour masses. Cancer therapies based on glycoconjugation, the linking of a drug to glucose or another sugar, allow improved selectivity and targeting, thus reducing harmful side effects. This mechanism exploits the over-expression of glucose membrane transporters, a phenotypic alteration in cancer cells included in an array of metabolic alterations known as the Warburg effect. However, the extent to which tumour masses adopt the Warburg phenotype is unclear, potentially limiting the efficacy of therapies based on glycoconjugation. We simulated multiple “what-if” scenarios, each modelling increasing proportions of tumour populations that adopted the Warburg phenotype, and compared the results to the expected growth curves derived from laboratory studies. Our results suggest that the Warburg phenotype is prevalent in tumours, with the population of cancer cells adopting this phenotype significantly outnumbering that of cells that do not.