Dynamics of cancer progression and suppression: A novel evolutionary game theory based approach

Author(s):  
Jeet Banerjee ◽  
Tanvi Ranjan ◽  
Ritwik Kumar Layek
2014 ◽  
Vol 4 (4) ◽  
pp. 20140028 ◽  
Author(s):  
Amy Wu ◽  
David Liao ◽  
Thea D. Tlsty ◽  
James C. Sturm ◽  
Robert H. Austin

Preventing relapse is the major challenge to effective therapy in cancer. Within the tumour, stromal (ST) cells play an important role in cancer progression and the emergence of drug resistance. During cancer treatment, the fitness of cancer cells can be enhanced by ST cells because their molecular signalling interaction delays the drug-induced apoptosis of cancer cells. On the other hand, competition among cancer and ST cells for space or resources should not be ignored. We explore the population dynamics of multiple myeloma (MM) versus bone marrow ST cells by using an experimental microecology that we call the death galaxy, with a stable drug gradient and connected microhabitats. Evolutionary game theory is a quantitative way to capture the frequency-dependent nature of interactive populations. Therefore, we use evolutionary game theory to model the populations in the death galaxy with the gradients of pay-offs and successfully predict the future densities of MM and ST cells. We discuss the possible clinical use of such analysis for predicting cancer progression.


2020 ◽  
Author(s):  
Benjamin Wölfl ◽  
Hedy te Rietmole ◽  
Monica Salvioli ◽  
Frank Thuijsman ◽  
Joel S. Brown ◽  
...  

AbstractEvolutionary game theory mathematically conceptualizes and analyzes biological interactions where one’s fitness not only depends on one’s own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather, inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer’s eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. We discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with an evolutionary game theory approach has medically useful implications that can inform and create a lockstep between empirical findings, and mathematical modeling. We suggest that cancer progression is an evolutionary game and needs to be viewed as such.


Author(s):  
Benjamin Wölfl ◽  
Hedy te Rietmole ◽  
Monica Salvioli ◽  
Artem Kaznatcheev ◽  
Frank Thuijsman ◽  
...  

AbstractEvolutionary game theory mathematically conceptualizes and analyzes biological interactions where one’s fitness not only depends on one’s own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer’s eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. Moreover, we discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with evolutionary game theory has medically useful implications that can inform and create a lockstep between empirical findings and mathematical modeling. We suggest that cancer progression is an evolutionary competition between different cell types and therefore needs to be viewed as an evolutionary game.


2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.


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