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

Banerjee, Joydeep; Ranjan, Tanvi; Layek, Ritwik Kumar

doi:10.1109/embc.2015.7319604

Cited by 8 publications

(9 citation statements)

References 18 publications

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“…In cancer, cells revert to an ancient unicellular lifestyle, abandoning their collective morphogenetic goals and treating the rest of the body as external environment [4,38,39]. While numerous studies of cancer from the perspective of game theory have been made [30,[40][41][42][43][44][45][46], further process could be achieved by better understanding this process not from the perspective of increased selfishness, but constant selfishness coupled with changes of the size of the Self, and thus changing incentives.…”

Section: Broader Implicationsmentioning

confidence: 99%

Physarum polycephalum: Establishing an Assay for Testing Decision-making Under Shifting Somatic Boundaries

Levin

2021

Preprint

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Prior studies of decision-making generally assume a fixed agent which maximizes utility among its various options. Physarum polycephalum is a popular model for basal cognition that can be cut into pieces that may or may not re-join. We exploited this capacity to develop a novel assay in which radical changes to the agent itself are among the options of the decision-making process. Specifically, we transected a Physarum culture in the presence of a food reward that was located closer to the new smaller piece. In this scenario, the newly created branch must choose between exploiting the reward itself, or first re-connecting with the original mass (and sharing the nutrient reward across a large body). We report a pilot study establishing a protocol in which the number of agents is part of the decision-making process. We observed that despite the presence of food, new branches strongly prefer to merge back to the syncytium before exploiting the reward. Many improvements to the protocol are possible, to extend this effort to understand the interplay between behavioral options and the structure and boundary of the individual making choices in its environment

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Section: Broader Implicationsmentioning

confidence: 99%

Physarum polycephalum: Establishing an Assay for Testing Decision-making Under Shifting Somatic Boundaries

Levin

2021

Preprint

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“…The net metabolic cost of production towards the cooperator is σ = c − rc N = c(1 − r N ). Therefore, the fitness of a cooperator is the difference between resource acquired and net metabolic cost of cooperation as denoted in the expression of f C in (2). The contribution of defectors towards the public goods production is zero, i.e.…”

Section: Population Dynamics In Biofilms: a Replicator Systemmentioning

confidence: 99%

“…In the previous section, we discussed the stability analysis of the equilibrium points of the replicator system in (1) using the fitness functions as defined in (2). In this stability analysis, the payoff ex-pressions in (2) do not contain any parameter(s) which signify the degree of assortment, present in microbial biofilms.…”

Section: Analysis Of Replicator Dynam-ics With Spatial Patternmentioning

confidence: 99%

“…Therefore, the stability analysis of such biofilms is an important question to study towards the development of novel anti-biofilm drugs [4,3]. In this paper, we formulate the replicator dynamics model [11,2] in microbial biofilms with non-competing strains [8] in two ways -first without consideration of spatial pattern and secondly include the pattern formation. Further, we analyze the stability of the equilibrium points of the proposed replicator system using nonlinear control theory [34].…”

Section: Introductionmentioning

confidence: 99%

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Stability Analysis of Population Dynamics Model in Microbial Biofilms with Non-participating Strains

Banerjee

Ranjan

Layek

2016

Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

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The existence of phenotypic heterogeneity in single-species bacterial biofilms is well-established in the published literature. However, the modeling of population dynamics in biofilms from the viewpoint of social interactions, i.e. interplay between heterotypic strains, and the analysis of this kind using control theory are not addressed significantly. Therefore, in this paper, we theoretically analyze the population dynamics model in microbial biofilms with non-participating strains (coexisting with public goods producers and non-producers) in the context of evolutionary game theory and nonlinear dynamics. Our analysis of the replicator dynamics model is twofold: first without the inclusion of spatial pattern, and second with the consideration of degree of assortment. In the first case, Lyapunov stability analysis of the stable equilibrium point of the proposed replicator system determines (1, 0) ('full dominance of cooperators') as a global asymptotic stable equilibrium whenever the return exceeds the metabolic cost of cooperation. Hence, the global asymptotic stable nature of (1, 0) in the context of nonconsideration of spatial pattern helps to justify mathematically the adversity in the eradication of "cooperative enterprise" that is an infectious biofilm. In the second case, we found non-existence of global asymptotic stability in the system, and it unveils two additional phenomena -bistability and coexistence. In this context, two inequality conditions are derived for the 'full dominance of cooperators' and coexistence. Therefore, the inclusion of spatial pattern in biofilms with non-competing strains intends conditional dominance of pathogenic (with respect to the hosts) public goods producers which can be an effective strategy towards the control of an infectious biofilm with the drug-dependent regulation of degree of segregation. Furthermore, the simulation results of the proposed dynamics for both the discussed scenario confirm the results of the analysis of equilibrium points. The proposed stability analysis not only demonstrate a mathematical framework to analyze the population dynamics in biofilms but also gives a clue to control an infectious biofilm, where phenotypic and spatial heterogeneity exist.

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“…More cancer modeling by mathematical tools can be found in (25)(26)(27)(28). Various mathematical approaches, such as game theory, replicator equations, and differential equations, have been applied in cancer investigation (29)(30)(31). The emergence of cancer was studied considering the interaction between healthy and cancerous cells as an evolutionary game (7,32).…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analyzing Stem-Cell Therapy toward Cancer: Evolutionary Game Theory Perspective

Veisi¹,

Khadem²,

Ravanshadi³

2020

ijph

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Background: Immunotherapy is a recently developed method of cancer therapy, aiming to strengthen a patient’s immune system in different ways to fight cancer. One of these ways is to add stem cells into the patient’s body. Methods: The study was conducted in Kermanshah, western Iran, 2016-2017. We first modeled the interaction between cancerous and healthy cells using the concept of evolutionary game theory. System dynamics were analyzed employing replicator equations and control theory notions. We categorized the system into separate cases based on the value of the parameters. For cases in which the system converged to undesired equilibrium points, “stem-cell injection” was employed as a therapeutic suggestion. The effect of stem cells on the model was considered by reforming the replicator equations as well as adding some new parameters to the system. Results: By adjusting stem cell-related parameters, the system converged to desired equilibrium points, i.e., points with no or a scanty level of cancerous cells. In addition to the theoretical analysis, our simulation results suggested solutions were effective in eliminating cancerous cells. Conclusion: This model could be applicable to different types of cancer, so we did not restrict it to a specific type of cancer. In fact, we were seeking a flexible mathematical framework that could cover different types of cancer by adjusting the system parameters.

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

Cited by 8 publications

References 18 publications

Physarum polycephalum: Establishing an Assay for Testing Decision-making Under Shifting Somatic Boundaries

Physarum polycephalum: Establishing an Assay for Testing Decision-making Under Shifting Somatic Boundaries

Stability Analysis of Population Dynamics Model in Microbial Biofilms with Non-participating Strains

Modeling and Analyzing Stem-Cell Therapy toward Cancer: Evolutionary Game Theory Perspective

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