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The theory of tumor immuno-ecodynamics
1State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.
Background:
In previous studies, I established theoretical frameworks for immunodynamics and tumor ecodynamics, respectively, to quantitatively describe immune responses and the interactions between the immune system and the tumor ecosystem. Although these two theories are closely related, they are still distinct. This study aims to integrate these two theories into a unified theory termed tumor immuno-ecodynamics, and provide a simple standard mathematical model for medical researchers and clinicians.
Methods And Results:
After conducting an information-theoretical analysis on the fundamental equations of immunodynamics and tumor ecodynamics, and incorporating them into the framework of information theory, I standardized a series of equations by subtracting the background values from the measured values of the variables. At the same time, I mathematized the cancer immunoediting theory that had been included in this framework, and rigorously proved some important formulae mathematically. Thus, a standard mathematical model termed the theory of tumor immuno-ecodynamics was established to unify the above two different theories. This model containing ten standard conceptual equations focuses on the signal (information) connections and interactions between the immune system and the tumor ecosystem, which are redefined as two subsystems of the tumor immuno-ecosystem.
Conclusion:
The standard mathematical model composed of these ten conceptual equations unifies immunodynamics and tumor ecodynamics into the theory of tumor immuno-ecodynamics, which incorporates four existing important theories, namely the theories of immune equilibrium, the tumor ecosystem, the cancer hallmarks, and the cancer immunoediting. This theory can quantitatively describe the actions of the tumor immuno-ecosystem, laying a theoretical foundation for the development of immuno-oncology from qualitative to quantitative science.
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