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Published on: December 1, 2023
Metastasis Models: Thermodynamics and Complexity.
A Guerra1, J A Betancourt-Mar2, J A Llanos-Pérez2
1Department of Chemical-Physics, A. Alzola Group of Thermodynamics of Complex Systems M.V. Lomonosov Chair, Faculty of Chemistry, University of Havana, Havana, Cuba.
Thermodynamic and complex systems theories provide a framework for understanding cancer's emergence and evolution as a dynamic, self-organized process. This approach aids in developing models for cancer metastasis, including epithelial-mesenchymal transition and chronotherapy.
Area of Science:
- Integrative biology
- Nonlinear dynamics
- Cancer research
Background:
- Physiological complexity can be explained by thermodynamic formalism of nonequilibrium systems and complex systems theory.
- These frameworks offer a conceptual basis for studying cancer emergence and evolution.
Purpose of the Study:
- To characterize cancer emergence and evolution as a nonlinear dynamic system.
- To present mathematical models and techniques for studying cancer metastasis.
- To explore the temporal and spatial aspects of cancer metastasis, including epithelial-mesenchymal transition and chronotherapeutics.
Main Methods:
- Integrated theoretical framework combining nonequilibrium thermodynamics, complex systems theory, and systems biology.
- Development and application of mathematical models for cancer metastasis.
- Analysis of temporal dynamics, focusing on epithelial-mesenchymal transition and chronotherapy.
- Modeling of spatial evolution of cancer metastasis.
Main Results:
- Cancer can be conceptualized as a self-organized, nonlinear dynamic system operating out of thermodynamic equilibrium.
- Various mathematical models and techniques are available for characterizing cancer metastasis.
- Epithelial-mesenchymal transition and chronotherapeutic treatments are key factors in the temporal progression of metastasis.
- Models exist to describe the spatial spread of cancer metastasis.
Conclusions:
- The integration of thermodynamic and complex systems approaches provides a robust framework for understanding cancer.
- This framework facilitates the development of predictive and therapeutic strategies for cancer metastasis.
- Further research into dynamic models can enhance our understanding and treatment of cancer evolution.
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