Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model

被引:44
|
作者
You, Li [1 ]
Brown, Joel S. [3 ,4 ]
Thuijsman, Frank [1 ]
Cunningham, Jessica J. [4 ]
Gatenby, Robert A. [4 ,5 ]
Zhang, Jingsong [6 ]
Stankova, Katerina [1 ,2 ]
机构
[1] Maastricht Univ, Dept Data Sci & Knowledge Engn, Maastricht, Netherlands
[2] Delft Univ Technol, Delft Inst Appl Math, Delft, Netherlands
[3] Univ Illinois, Dept Biol Sci, Chicago, IL 60680 USA
[4] H Lee Moffitt Canc Ctr & Res Inst, Dept Integrated Math Oncol, Tampa, FL USA
[5] H Lee Moffitt Canc Ctr & Res Inst, Dept Diagnost Imaging & Intervent Radiol, Tampa, FL USA
[6] H Lee Moffitt Canc Ctr & Res Inst, Dept Genitourinary Oncol, Tampa, FL USA
关键词
Prostate cancer; Evolutionary game theory; Spatial game; Non-spatial game; CONTINUOUS ANDROGEN DEPRIVATION; RESISTANT PROSTATE-CANCER; INTRATUMOR HETEROGENEITY; GAME; COOPERATION; DISPERSAL; BIODIVERSITY; INTERMITTENT; ABIRATERONE; MUTATIONS;
D O I
10.1016/j.jtbi.2017.08.022
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T+), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (T-P), and (3) those independent of testosterone (T-). The interactions within and between cancer cell types can be represented by a 3 x 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T- cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:78 / 97
页数:20
相关论文
共 50 条
  • [41] Spatial patterns and recent temporal trends in global transpiration modelled using eco-evolutionary optimality
    Li, Shijie
    Wang, Guojie
    Zhu, Chenxia
    Hannemann, Marco
    Poyatos, Rafael
    Lu, Jiao
    Li, Ji
    Ullah, Waheed
    Hagan, Daniel Fiifi Tawia
    Garcia-Garcia, Almudena
    Liu, Yi
    Liu, Qi
    Ma, Siyu
    Liu, Qiang
    Sun, Shanlei
    Zhao, Fujie
    Peng, Jian
    AGRICULTURAL AND FOREST METEOROLOGY, 2023, 342
  • [42] Community assembly is a race between immigration and adaptation: eco-evolutionary interactions across spatial scales
    Vanoverbeke, Joost
    Urban, Mark C.
    De Meester, Luc
    ECOGRAPHY, 2016, 39 (09) : 858 - 870
  • [43] Non-spatial calibrations of a general unit model for ecosystem simulations
    Boumans, RM
    Villa, F
    Costanza, R
    Voinov, A
    Voinov, H
    Maxwell, T
    ECOLOGICAL MODELLING, 2001, 146 (1-3) : 17 - 32
  • [44] General non-linear imitation leads to limit cycles in eco-evolutionary dynamics
    Liu, Yuan
    Cao, Lixuan
    Wu, Bin
    CHAOS SOLITONS & FRACTALS, 2022, 165
  • [45] Eco-evolutionary dynamics of poly-aneuploid cancer cells: A life history model
    Bukkuri, Anuraag
    Pienta, Kenneth J.
    Austin, Robert H.
    Hammarlund, Emma U.
    Amend, Sarah R.
    Brown, Joel S.
    CANCER RESEARCH, 2022, 82 (10)
  • [46] OSCILLATORY NETWORK DYNAMICS UNDERLYING FEEDBACK-BASED LEARNING USING SPATIAL AND NON-SPATIAL INFORMATION
    van de Vijver, Irene
    van Kempen, Jochem
    Cohen, Michael X.
    PSYCHOPHYSIOLOGY, 2013, 50 : S126 - S126
  • [47] The welfare benefit of a home’s location: an empirical comparison of spatial and non-spatial model estimates
    Julia Koschinsky
    Nancy Lozano-Gracia
    Gianfranco Piras
    Journal of Geographical Systems, 2012, 14 : 319 - 356
  • [48] The welfare benefit of a home's location: an empirical comparison of spatial and non-spatial model estimates
    Koschinsky, Julia
    Lozano-Gracia, Nancy
    Piras, Gianfranco
    JOURNAL OF GEOGRAPHICAL SYSTEMS, 2012, 14 (03) : 319 - 356
  • [49] MetaIBM: A Python']Python-based library for individual-based modelling of eco-evolutionary dynamics in spatial-explicit metacommunities
    Lin, Jian-Hao
    Quan, Yu-Juan
    Han, Bo-Ping
    ECOLOGICAL MODELLING, 2024, 492
  • [50] Eco-evolutionary Dynamics of Non-episodic Neuroevolution in Large Multi-agent Environments
    Hamon, Gautier
    Nisioti, Eleni
    Moulin-Frier, Clement
    PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION, 2023, : 143 - 146