Physics of cancer propagation: A game theory perspective

Cleveland, Chris; Liao, David; Austin, Robert H.

doi:10.1063/1.3699043

Cited by 18 publications

(13 citation statements)

References 17 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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“…Thus, when the initial value (x 00 , y 00 ) is substituted into equation (1) and iterated 50 times, a complete ring-like trajectory is obtained. By constructing the relationship between M-ary information and initial value of Hamilton oscillator, which can determine the sub zone, the M-ary information can be modulated by Hamilton oscillator.…”

Section: A Hamilton Oscillator Modulation Methodsmentioning

confidence: 99%

“…Figure 1 shows the phase diagram of Hamiltion oscillator. Each ring-like trajectory is obtained by iterating equation (1) 50 times with different initial values, and p is set to be 0.1. These phase trajectories are composed of nine cell flows which are regular arrangement, independent with each other, symmetrical in structure, and their locations and zone boundaries are relatively fixed without interference with each other as well.…”

Section: A Hamilton Oscillator Modulation Methodsmentioning

confidence: 99%

The design and research of anti-color-noise chaos M-ary communication system

et al. 2016

AIP Advances

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Previously a novel chaos M-ary digital communication method based on spatiotemporal chaos Hamilton oscillator has been proposed. Without chaos synchronization circumstance, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-white-noise performance compared with traditional communication method. In this paper, the channel noise influence on chaotic modulation signals and the construction problem of anti-color-noise chaotic M-ary communication system are studied. The formula of zone partition demodulator's boundary in additive white Gaussian noise is derived, besides, the problem about how to determine the boundary of zone partition demodulator in additive color noise is deeply studied; Then an approach on constructing anti-color-noise chaos M-ary communication system is proposed, in which a pre-distortion filter is added after the chaos baseband modulator in the transmitter and whitening filter is added before zone partition demodulator in the receiver. Finally, the chaos M-ary communication system based on Hamilton oscillator is constructed and simulated in different channel noise. The result shows that the proposed method in this paper can improve the anti-color-noise performance of the whole communication system compared with the former system, and it has better anti-fading and resisting disturbance performance than Quadrature Phase Shift Keying system. Chaotic communication has become research hotspots in recent years and has developed very rapidly. Chaos M-ary communication has more transmission efficiency and bandwidth efficiency than binary communication, which utilize large bandwidth and have low power spectrum density. In traditional communication systems, the analogue sample functions sent through the channel are weight sums of sinusoid waveforms and are linear. However, in chaotic communication systems, the samples are segments of chaotic waveforms and are nonlinear. This nonlinear, unstable and aperiodic characteristic of chaotic signal has numerous features that make it attractive for communication use. It has wideband characteristic, it is resistant against multipath fading and it offers a cheaper solution to traditional spread spectrum systems. In the former study, we have proposed a novel chaos M-ary communication method based on spatiotemporal chaos Hamilton map, which has not been widely studied yet. It uses zone mapping method and zone partition method to realize chaos M-ary modulation and demodulation, and the whole communication system has been constructed, it is shown that in M-ary high speed transmission communication system and with no chaos synchronization, the proposed chaotic M-ary modulation and demodulation method has outperformed some conventional M-ary modulation methods, such as Quadrature Phase Shift Keying (QPSK) and M-ary Pulse Amplitude Modulation (PAM) in bit error rate. Besides, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-white-noise performance, and the a Author to whom correspondence should b...

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“…Using the spatial simulation framework developed by Cleveland, et al [51] as a starting point, we developed a fast, minimal simulation of a metabolically and spatially heterogeneous cell population with diffusible metabolites, gasses, and signaling molecules. We extend the framework in significant and novel ways to further suit our needs.…”

Section: Introductionmentioning

confidence: 99%

Simulating Heterogeneous Tumor Cell Populations

Sundstrom¹,

Bar–Sagi²,

Mishra³

2016

PLoS ONE

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Certain tumor phenomena, like metabolic heterogeneity and local stable regions of chronic hypoxia, signify a tumor’s resistance to therapy. Although recent research has shed light on the intracellular mechanisms of cancer metabolic reprogramming, little is known about how tumors become metabolically heterogeneous or chronically hypoxic, namely the initial conditions and spatiotemporal dynamics that drive these cell population conditions. To study these aspects, we developed a minimal, spatially-resolved simulation framework for modeling tissue-scale mixed populations of cells based on diffusible particles the cells consume and release, the concentrations of which determine their behavior in arbitrarily complex ways, and on stochastic reproduction. We simulate cell populations that self-sort to facilitate metabolic symbiosis, that grow according to tumor-stroma signaling patterns, and that give rise to stable local regions of chronic hypoxia near blood vessels. We raise two novel questions in the context of these results: (1) How will two metabolically symbiotic cell subpopulations self-sort in the presence of glucose, oxygen, and lactate gradients? We observe a robust pattern of alternating striations. (2) What is the proper time scale to observe stable local regions of chronic hypoxia? We observe the stability is a function of the balance of three factors related to O2—diffusion rate, local vessel release rate, and viable and hypoxic tumor cell consumption rate. We anticipate our simulation framework will help researchers design better experiments and generate novel hypotheses to better understand dynamic, emergent whole-tumor behavior.

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Physics of cancer propagation: A game theory perspective

Cited by 18 publications

References 17 publications

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

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

The design and research of anti-color-noise chaos M-ary communication system

Simulating Heterogeneous Tumor Cell Populations

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