Abstract
The intratumor heterogeneity has been recognized to characterize cancer cells impairing the efficacy of cancer treatments. We here propose an extension of constraint-based modeling approach in order to simulate metabolism of cell populations with the aim to provide a more complete characterization of these systems, especially focusing on the relationships among their components. We tested our methodology by using a toy-model and taking into account the main metabolic pathways involved in cancer metabolic rewiring. This toy-model is used as “individual” to construct a “population model” characterized by multiple interacting individuals, all having the same topology and stoichiometry, and sharing the same nutrients supply. We observed that, in our population, cancer cells cooperate with each other to reach a common objective, but without necessarily having the same metabolic traits. We also noticed that the heterogeneity emerging from the population model is due to the mismatch between the objective of the individual members and the objective of the entire population.
M. Di Filippo and C. Damiani—Equal contributors.
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Acknowledgement
The institutional financial support to SYSBIO Center of Systems Biology - within the Italian Roadmap for ESFRI Research Infrastructures - is gratefully acknowledged. M.D. is supported by SYSBIO fellowship.
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Di Filippo, M., Damiani, C., Colombo, R., Pescini, D., Mauri, G. (2017). Constraint-Based Modeling and Simulation of Cell Populations. In: Rossi, F., Piotto, S., Concilio, S. (eds) Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry. WIVACE 2016. Communications in Computer and Information Science, vol 708. Springer, Cham. https://doi.org/10.1007/978-3-319-57711-1_11
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