The ecology of cancer from an evolutionary game theory perspective

Pacheco, Jorge M.; Santos, Francisco C.; Dingli, David

doi:10.1098/rsfs.2014.0019

Cited by 78 publications

(50 citation statements)

References 59 publications

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“…The cancer problem has been considered from many different modeling perspectives ranging from the standard mechanistic models [21][22][23][24][25], to applications of population dynamics [26][27][28][29], evolutionary game theory [30][31][32], and models of swarm dynamics [33,34]. However, these methods generally only consider one or two levels of organization in describing the dynamics of the systems they consider, and almost exclusively view the lowest level as giving rise to the higher levels.…”

Section: Information In Biological Systemsmentioning

confidence: 99%

Cancer as a disorder of patterning information: computational and biophysical perspectives on the cancer problem

Moore

Walker

Levin

2017

Converg. Sci. Phys. Oncol.

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TOPICAL REVIEWCancer as a disorder of patterning information: computational and biophysical perspectives on the cancer problem IntroductionCancer is well-recognized not only as an extremely pernicious medical problem, but also as a group of phenomena deeply connected to the fundamental questions of evolution, multicellularity, pattern (disregulation, and the interplay between the genome and the environment [1,2]. Two fundamental paradigms currently divide the field. One is that cancer results from disorders of genetics: cancer cells are fundamentally broken due to genomic mutation or instability, and their clonal progeny form tumors and metastases. This view is sometimes called the SMT, somatic mutation theory [3][4][5]. A competing perspective is that of cancer as a circuit disease-a disorder of the complex biophysical, transcriptional, and epigenetic dynamics that regulate cellular state and the ability of cells to cooperate in vivo [6][7][8]. Under this view (sometimes called the tissue organization field theory or TOFT, [9,10]), cancer is akin to a traffic jam [11]-the problem is not a permanent discrete alteration within a founder cell and all of its clonal descendants, but an undesirable stable attractor in the complex network of controls that normally guides anatomical homeostasis [12].The relative merits of the two models have been discussed extensively [10,[13][14][15][16][17] AbstractThe current paradigm views cancer as arising clonally from a degradation of genetic information in single cells. A complementary perspective, originating at the dawn of modern developmental biology, is that cancer is the result of a system disorder of algorithms that normally orchestrate individual cell activities toward specific anatomical structures and away from tumorigenesis. A view of cancer as a disease of geometry focuses on the pathways that allow cells to cooperate to build and maintain large-scale anatomical patterning. Cancer may result when cells stop maintaining higher-order structures and reduce the boundary of their computational selves to a single-cell level, reverting to a unicellular lifestyle in which the rest of the organism is merely part of the environment at the expense of which all living things survive. While this view has been widely discussed, little progress has been made in providing a quantitative, mechanistic framework within which this perspective's specific and unique implications for treatment strategies can be tested and biomedically exploited. Here, we highlight two recent areas of progress which may facilitate much-needed progress on the cancer problem. First, we review the roles that endogenous bioelectrical networks, operating across many tissues in vivo, play as a medium of information processing in tumor suppression, progression, and reprogramming. Second, we provide a primer to the development of computational theory and tools for quantifying the information and causal control structures in cancer and other complex biological systems. Rigorous mathematical formalisms now exist to...

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Section: Information In Biological Systemsmentioning

confidence: 99%

Cancer as a disorder of patterning information: computational and biophysical perspectives on the cancer problem

Moore

Walker

Levin

2017

Converg. Sci. Phys. Oncol.

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“…This framework allows for an easy interpretation and implementation of frequency-dependent selection processes which can lead to coexistence or bistable dynamics. Amongst others, evolutionary games have provided insights into evolution of cooperation [65], evolution of sex [57], host-parasite-dynamics [50] and more recently, the evolution of cancer [71]. The introduction of stochasticity albeit within fixed population sizes, allows the study of quantities such as fixation probabilities or mean fixation times [2,3,31].…”

Section: Introductionmentioning

confidence: 99%

Disentangling eco-evolutionary effects on trait fixation

Czuppon

Gokhale

2018

Preprint

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In population genetics, fixation of traits in a demographically changing population under frequencyindependent selection has been extensively analyzed. In evolutionary game theory, models of fixation have typically focused on fixed population sizes and frequency-dependent selection. However, combining ecological fluctuations with frequency-dependent interactions such as Lotka-Volterra dynamics and thus the analysis of eco-evolutionary fixation has received comparatively little attention. Here, we consider a two-type stochastic competitive Lotka-Volterra model with higher order interactions. The emerging individual based model allows for stochastic fluctuations not just in the frequencies of the two types but the total population size as well. Assuming weak selective di↵erences between the traits we approximate the fixation probability for di↵ering competition coe cients. We find that it resembles qualitatively the corresponding evolutionary deterministic dynamics within a population of fixed size. Furthermore, we analyze and partially disentangle the selection e↵ects into their ecological and evolutionary components. Concretely, we show that the evolutionary selection intensity has a larger e↵ect on the predictive power of our approximation than the ecological selection. However, the fixed points themselves are also a↵ected by the selection intensity which implies that a clean separation of the ecological and evolutionary impacts on the evolutionary outcome of the model is not possible. The entanglement of eco-evolutionary processes in a co-evolutionary system is thus a reality which needs to be considered when determining the fixation properties in populations of fluctuating size.

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“…The paper by Pacheco et al [5] is the more complete and tutorial of the two hardcore cancer game theory papers and can be read as a companion to the paper by Liao and Tlsty for a more direct connection to the clinical implications of the more classical elements of evolutionary game theory in terms of interacting populations of cells.…”

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confidence: 99%