Reppas2015 - tumor control via alternating immunostimulating and immunosuppressive phases

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Model Identifier
BIOMD0000000749
Short description
The paper describes a model of tumor control via alternating immunostimulating and immunosuppressive phases. Created by COPASI 4.25 (Build 207) This model is described in the article: In silico tumor control induced via alternating immunostimulating and immunosuppressive phases AI Reppas, JCL Alfonso, and H Hatzikirou Virulence 7:2, 174--186 Abstract: Despite recent advances in the field of Oncoimmunology, the success potential of immunomodulatory therapies against cancer remains to be elucidated. One of the reasons is the lack of understanding on the complex interplay between tumor growth dynamics and the associated immune system responses. Toward this goal, we consider a mathematical model of vascularized tumor growth and the corresponding effector cell recruitment dynamics. Bifurcation analysis allows for the exploration of model’s dynamic behavior and the determination of these parameter regimes that result in immune-mediated tumor control. In this work, we focus on a particular tumor evasion regime that involves tumor and effector cell concentration oscillations of slowly increasing and decreasing amplitude, respectively. Considering a temporal multiscale analysis, we derive an analytically tractable mapping of model solutions onto a weakly negatively damped harmonic oscillator. Based on our analysis, we propose a theory-driven intervention strategy involving immunostimulating and immunosuppressive phases to induce long-term tumor control. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.
Format
SBML (L3V1)
Related Publication
  • In silico tumor control induced via alternating immunostimulating and immunosuppressive phases.
  • Reppas AI, Alfonso JC, Hatzikirou H
  • Virulence , 1/ 2016 , Volume 7 , Issue 2 , pages: 174-186 , PubMed ID: 26305801
  • a Center for Advancing Electronics; Technische Universität Dresden ; Dresden , Germany.
  • Despite recent advances in the field of Oncoimmunology, the success potential of immunomodulatory therapies against cancer remains to be elucidated. One of the reasons is the lack of understanding on the complex interplay between tumor growth dynamics and the associated immune system responses. Toward this goal, we consider a mathematical model of vascularized tumor growth and the corresponding effector cell recruitment dynamics. Bifurcation analysis allows for the exploration of model's dynamic behavior and the determination of these parameter regimes that result in immune-mediated tumor control. In this work, we focus on a particular tumor evasion regime that involves tumor and effector cell concentration oscillations of slowly increasing and decreasing amplitude, respectively. Considering a temporal multiscale analysis, we derive an analytically tractable mapping of model solutions onto a weakly negatively damped harmonic oscillator. Based on our analysis, we propose a theory-driven intervention strategy involving immunostimulating and immunosuppressive phases to induce long-term tumor control.
Contributors
Submitter of the first revision: Jinghao Men
Submitter of this revision: Jinghao Men
Modellers: Jinghao Men

Metadata information

is (2 statements)
BioModels Database MODEL1907110002
BioModels Database BIOMD0000000749

isDescribedBy (1 statement)
PubMed 26305801

hasTaxon (1 statement)
Taxonomy Homo sapiens

isVersionOf (1 statement)
hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model

Curation status
Curated
Modelling approach(es)
ordinary differential equation model
Tags
Immuno-oncology

Connected external resources

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Name Description Size Actions

Model files
Reppas2015.xml SBML L3V1 representation of the alternating immunostimulating and immunosuppressive phases model 61.21 KB Preview | Download

Additional files
Reppas2015.cps CPS file of the model in COPASI 79.42 KB Preview | Download
Reppas2015.sedml Auto-generated SEDML file 2.14 KB Preview | Download

  • Model originally submitted by : Jinghao Men
  • Submitted: Jul 11, 2019 4:25:37 PM
  • Last Modified: Jul 11, 2019 4:27:02 PM
Revisions
  • Version: 3 public model Download this version
    • Submitted on: Jul 11, 2019 4:27:02 PM
    • Submitted by: Jinghao Men
    • With comment: Automatically added model identifier BIOMD0000000749
  • Version: 2 public model Download this version
    • Submitted on: Jul 11, 2019 4:25:37 PM
    • Submitted by: Jinghao Men
    • With comment: Edited model metadata online.

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
R

malignant cell 		2.0 mmol
E 0

Effector Immune Cell 		10.0 mmol
f

Mathematical Operator 		0.414213562373095 mmol
E

Effector Immune Cell 		1000000.0 mmol
Reactions
Reactions Rate Parameters
=> R tumor_microenvironment*lm*(1-B)*ld/tanh(R/ld) ld = 0.3 1; B = 0.5 1; lm = 1.34 1/d
R => ; E_0, f tumor_microenvironment*c*E_0*R*f c = 0.03 1/d
R => tumor_microenvironment*lm*(1-B)*ld*ld/R ld = 0.3 1; B = 0.5 1; lm = 1.34 1/d
E_0 = E/100000 [] []
f = R^(B-1)/(R^(B-1)+1) [] B = 0.5 1
E => ; R, f tumor_microenvironment*d1*E*R*R*R*f d1 = 0.01 1/d
E => tumor_microenvironment*d0*E d0 = 0.37 1/d
=> E tumor_microenvironment*sigma sigma = 13000.0 1/d
=> E; R tumor_microenvironment*r*R*R*R*E/(k+R*R*R) k = 2.72 1; r = 0.57 1/d
Curator's comment:
(added: 11 Jul 2019, 16:26:48, updated: 11 Jul 2019, 16:26:48)
Publication figure 1I reproduced as per literature. Other figures are reproduced with different sets of parameters. Figure data is generated using COPASI 4.25 (build 197).