Abstract
This work explores the effects of excess nutrient in an agent-based lattice model of tumour growth. The Non-physiological Evolutionary Algorithm for Tumour Growth (NEATG) model is a platform that has previously been used to explore aspects of tumour regrowth following cytotoxic treatment and the impact of tissue-cell communicative breakdown (anakoinosis) [1]. The model has been shown to recapitulate real-world tumour growth dynamics and display emergent behaviours in line with in vitro tumour systems. This work is motivated by a chance observation during regression testing of the model after refactoring of the code. During this series of tests a number of model runs had shown excessive run-times due to unexpectedly high rates of tumour growth. On investigation it was ascertained that a single model parameter had been mistyped and that the nutrient supply had been set at a supra-physiological level. This study expands on this chance finding to explore the impact of over-feeding on tumour growth dynamics and its relation to response to cytotoxic treatment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pantziarka, P., Ghibelli, L., Reichle, A.: A computational model of tumor growth and anakoinosis. Front. Pharmacol. 10(March), 287 (2019)
Pantziarka, P.: Emergent properties of a computational model of tumour growth. PeerJ 4, e2176 (2016)
Heudobler, D., Rechenmacher, M., Lüke, F., Vogelhuber, M., et al.: Clinical efficacy of a novel therapeutic principle anakoinosis. Front. Pharmacol. 9(November), 1357 (2018)
Hart, C., Vogelhuber, M., Wolff, D., Klobuch, S., et al.: Anakoinosis: communicative reprogramming of tumor systems - for rescuing from chemorefractory neoplasia. Cancer Microenviron.: Off. J. Int. Cancer Microenviron. Soc. 8(2), 75–92 (2015)
Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. In: Soviet Physics Doklady, pp. 707–710 (1966)
Sakamoto, Y., Ishiguro, M., Kitagawa, G.: Akaike Information Criterion Statistics, vol. 81(10.5555), pp. 26853. D. Reidel, Dordrecht, The Netherlands (1986)
Salem, A.F., Whitaker-Menezes, D., Lin, Z., Martinez-Outschoorn, U.E., et al.: Two-compartment tumor metabolism: autophagy in the tumor microenvironment and oxidative mitochondrial metabolism (OXPHOS) in cancer cells. Cell cycle (Georgetown, Tex.) 11(13), 2545–56.
Martinez-Outschoorn, U.E., Balliet, R.M., Rivadeneira, D.B., Chiavarina, B., et al.: Oxidative stress in cancer associated fibroblasts drives tumor-stroma co-evolution: A new paradigm for understanding tumor metabolism, the field effect and genomic instability in cancer cells. Cell Cycle (Georgetown, Tex.) 9(16), 3256–3276 (2010)
Rezende, L.P., Galheigo, M.R.U., Landim, B.C., Cruz, A.R., et al.: Effect of glucose and palmitate environment on proliferation and migration of PC3-prostate cancer cells. Cell Biol. Int. 43(4), 373–383 (2019)
Filipova, E., Uzunova, K., Kalinov, K., Vekov, T.: Effects of pioglitazone therapy on blood parameters, weight and BMI: a meta-analysis. Diabetol. Metab. Syndr. 9, 90 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Pantziarka, P., Ghibelli, L., Reichle, A. (2022). The Effect of Over-Feeding in a Computational Model of Tumour Growth. In: Balaz, I., Adamatzky, A. (eds) Cancer, Complexity, Computation. Emergence, Complexity and Computation, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-031-04379-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-031-04379-6_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-04378-9
Online ISBN: 978-3-031-04379-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)