An agent-based model of avascular tumor growth: Immune response tendency to prevent cancer development

被引:25
|
作者
Pourhasanzade, Fateme [1 ,4 ]
Sabzpoushan, S. H. [1 ]
Alizadeh, Ali Mohammad [2 ]
Esmati, Ebrahim [3 ]
机构
[1] IUST, Dept Biomed Engn, Res Lab Biomed Signals & Sensors, Tehran, Iran
[2] Univ Tehran Med Sci, Canc Res Ctr, Tehran, Iran
[3] Univ Tehran Med Sci, Inst Canc, Dept Radiat Oncol, Tehran, Iran
[4] IUST, Sch Elect Engn, Tehran 1684613114, Iran
关键词
Agent-based model; tumor growth model; mathematical model; immune cell; recruitment; hypoxia; MATHEMATICAL-MODELS; DYNAMICS; OXYGEN;
D O I
10.1177/0037549717699072
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Mathematical and computational models are of great help to study and predict phenomena associated with cancer growth and development. These models may lead to introduce new therapies or improve current treatments by discovering facts that may not be easily discovered in clinical experiments. Here, a new two-dimensional (2D) stochastic agent-based model is presented for the spatiotemporal study of avascular tumor growth based on the effect of the immune system. The simple decision-making rules of updating the states of each agent depend not only on its intrinsic properties but also on its environment. Tumor cells can interact with both normal and immune cells in their Moore neighborhood. The effect of hypoxia has been checked off by considering non-mutant proliferative tumor cells beside mutant ones. The recruitment of immune cells after facing a mass of tumor is also considered. Results of the simulations are presented before and after the appearance of immune cells in the studied tissue. The growth fraction and necrotic fraction are used as output parameters along with a 2D graphical growth presentation. Finally, the effect of input parameters on the output parameters generated by the model is discussed. The model is then validated by an in vivo study published in medical articles. The results show a multi-spherical tumor growth before the immune system strongly involved in competition with tumor cells. Besides, considering the immune system in the model shows more compatibility with biological facts. The effect of the microenvironment on the proliferation of cancer and immune cells is also studied.
引用
收藏
页码:641 / 657
页数:17
相关论文
共 50 条
  • [11] Using an agent-based model to analyze the dynamic communication network of the immune response
    Folcik, Virginia A.
    Broderick, Gordon
    Mohan, Shunmugam
    Block, Brian
    Ekbote, Chirantan
    Doolittle, John
    Khoury, Marc
    Davis, Luke
    Marsh, Clay B.
    THEORETICAL BIOLOGY AND MEDICAL MODELLING, 2011, 8
  • [12] Research on Agent-based Enterprise's Innovation Tendency Simulation Model
    Liu Wenrong
    Li Jianhua
    Xu Xiaolong
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON INNOVATION & MANAGEMENT, VOLS I AND II, 2008, : 448 - 453
  • [13] An Agent-Based Model of Solid Tumor Progression
    Dreau, Didier
    Stanimirov, Dimitre
    Carmichael, Ted
    Hadzikadic, Mirsad
    BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, PROCEEDINGS, 2009, 5462 : 187 - +
  • [14] Multiscale Agent-based Model of Tumor Angiogenesis
    Olsen, Megan M.
    Siegelmann, Hava T.
    2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, 2013, 18 : 1016 - 1025
  • [15] An Agent-Based Stochastic Tumor Model for Predicting Mitotic Arrest Drug Response
    Fox, Brandon M.
    Moffitt, Richard A.
    Wang, May D.
    2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 2008, : 5458 - +
  • [16] Model of avascular tumor growth and response to low dose exposure
    Rodriguez Aguirre, J. M.
    Custidiano, E. R.
    8TH ARGENTINEAN BIOENGINEERING SOCIETY CONFERENCE (SABI 2011) AND 7TH CLINICAL ENGINEERING MEETING, 2011, 332
  • [17] Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment
    Norton, Kerri-Ann
    Gong, Chang
    Jamalian, Samira
    Popel, Aleksander S.
    PROCESSES, 2019, 7 (01)
  • [18] Trust, Growth, and Inequality: An Agent-Based Model
    Chen, Shu-Heng
    Chie, Bin-Tzong
    AGENT-BASED APPROACHES IN ECONOMIC AND SOCIAL COMPLEX SYSTEMS VIII, 2015, : 115 - 128
  • [19] LDEF Formalism for Agent-Based Model Development
    Bae, Jang Won
    Moon, Il-Chul
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 46 (06): : 793 - 808
  • [20] The impact of "search precision" in an agent-based tumor model
    Mansury, Y
    Deisboeck, TS
    JOURNAL OF THEORETICAL BIOLOGY, 2003, 224 (03) : 325 - 337