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Spatial stochastic computer model of cancer invasion in the tumor microenvironment: the Warburg effect.

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Title: Spatial stochastic computer model of cancer invasion in the tumor microenvironment: the Warburg effect.
Authors: Neto, Maria1 (AUTHOR), Zhang, William1 (AUTHOR), Tiwary, Surabhi1 (AUTHOR), Nicolau Jr, Dan V.1 (AUTHOR) dan.nicolau@kcl.ac.uk
Source: International Journal of Parallel, Emergent & Distributed Systems. Aug2025, Vol. 40 Issue 4, p446-479. 34p.
Subjects: Warburg Effect (Oncology), Metabolism, Reaction-diffusion equations, Oncology, Metastasis, Metabolic models, Tumor microenvironment
Abstract: The Warburg effect, marked by elevated glucose uptake and aerobic glycolysis, drives metabolic heterogeneity in tumors, yet spatial organization of tumor cells remains poorly understood. In this study, we applied the Gray-Scott reaction-diffusion model to simulate metabolic pattern formation using two computational models. Despite added variability from introduced plasticity, initial diffusion states consistently shaped pattern emergence. Adjusting influx and depletion rates generated a range of intratumoral patterns, mirroring biological complexity. These findings emphasize the role of metabolism in tumor architecture and support phenotype-based treatment strategies. Future work will extend the model to include metastatic and temporal dynamics, informing precision oncology. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:The Warburg effect, marked by elevated glucose uptake and aerobic glycolysis, drives metabolic heterogeneity in tumors, yet spatial organization of tumor cells remains poorly understood. In this study, we applied the Gray-Scott reaction-diffusion model to simulate metabolic pattern formation using two computational models. Despite added variability from introduced plasticity, initial diffusion states consistently shaped pattern emergence. Adjusting influx and depletion rates generated a range of intratumoral patterns, mirroring biological complexity. These findings emphasize the role of metabolism in tumor architecture and support phenotype-based treatment strategies. Future work will extend the model to include metastatic and temporal dynamics, informing precision oncology. [ABSTRACT FROM AUTHOR]
ISSN:17445760
DOI:10.1080/17445760.2025.2508164