Abstract
Analysis of the evolution and growth dynamics of tumors is crucial for understanding cancer and the development of individually optimized therapies. During tumor growth, a hypoxic microenvironment around cancer cells caused by excessive non-vascular tumor growth induces tumor angiogenesis that plays a key role in the ensuing tumor growth and its progression into higher stages. Various mathematical simulation models have been introduced to simulate these biologically and physically complex hallmarks of cancer. Here, we developed a hybrid two-dimensional computational model that integrates spatiotemporally different components of the tumor system to investigate both angiogenesis and tumor growth/proliferation. This spatiotemporal evolution is based on partial diffusion equations, the cellular automation method, transition and probabilistic rules, and biological assumptions. The new vascular network provided by angiogenesis affects tumor microenvironmental conditions and drives individual cells to adapt themselves to spatiotemporal conditions. Furthermore, some stochastic rules are involved besides microenvironmental conditions. Overall, the conditions promote some commonly observed cellular states, i.e., proliferative, migrative, quiescent, and cell death, depending on the condition of each cell. Altogether, our results offer a theoretical basis for the biological evidence that regions of the tumor tissue near blood vessels are densely populated by proliferative phenotypic variants, while poorly oxygenated regions are sparsely populated by hypoxic phenotypic variants.
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We would like to thank all individuals who cooperated in this study.
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This research is supported in part by Shahrekord University.
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M.B. and M.M. and M.E.B. and H.R. conceived of the presented idea. M.B. developed the theory and performed the computations. M.M. and M.E.B. and H.R. verified the analytical methods. M.M. and M.E.B. supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.
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Borzouei, M., Mardaani, M., Emadi-Baygi, M. et al. Development of a coupled modeling for tumor growth, angiogenesis, oxygen delivery, and phenotypic heterogeneity. Biomech Model Mechanobiol 22, 1067–1081 (2023). https://doi.org/10.1007/s10237-023-01701-w
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DOI: https://doi.org/10.1007/s10237-023-01701-w