Saad2017 - immune checkpoint and BCG in superficial bladder cancer

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The paper describes a model on the Dynamics of Immune Checkpoints, Immune System, and BCG in the Treatment of Superficial Bladder Cancer. Created by COPASI 4.25 (Build 207) This model is described in the article: Dynamics of Immune Checkpoints, Immune System, and BCG in the Treatment of Superficial Bladder Cancer Farouk Tijjani Saad, Evren Hincal, and Bilgen Kaymakamzade Computational and Mathematical Methods in Medicine, vol. 2017, no. 3573082 Abstract: This paper aims to study the dynamics of immune suppressors/checkpoints, immune system, and BCG in the treatment of superficial bladder cancer. Programmed cell death protein-1 (PD-1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA4), and transforming growth factor-beta (TGF-b) are some of the examples of immune suppressors/checkpoints. They are responsible for deactivating the immune system and enhancing immunological tolerance. Moreover, they categorically downregulate and suppress the immune system by preventing and blocking the activation of T-cells, which in turn decreases autoimmunity and enhances self- tolerance. In cancer immunotherapy, the immune checkpoints/suppressors prevent and block the immune cells from attacking, spreading, and killing the cancer cells, which leads to cancer growth and development. We formulate a mathematical model that studies three possible dynamics of the treatment and establish the effects of the immune checkpoints on the immune system and the treatment at large. Although the effect cannot be seen explicitly in the analysis of the model, we show it by numerical simulations. This model is hosted on BioModels Database and identified by: MODEL1907100001. 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
  • Dynamics of Immune Checkpoints, Immune System, and BCG in the Treatment of Superficial Bladder Cancer.
  • Saad FT, Hincal E, Kaymakamzade B
  • Computational and mathematical methods in medicine , 1/ 2017 , Volume 2017 , pages: 3573082
  • Department of Mathematics, Near East University, North Nicosia, Northern Cyprus, Mersin 10, Turkey.
  • This paper aims to study the dynamics of immune suppressors/checkpoints, immune system, and BCG in the treatment of superficial bladder cancer. Programmed cell death protein-1 (PD-1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA4), and transforming growth factor-beta (TGF-β) are some of the examples of immune suppressors/checkpoints. They are responsible for deactivating the immune system and enhancing immunological tolerance. Moreover, they categorically downregulate and suppress the immune system by preventing and blocking the activation of T-cells, which in turn decreases autoimmunity and enhances self-tolerance. In cancer immunotherapy, the immune checkpoints/suppressors prevent and block the immune cells from attacking, spreading, and killing the cancer cells, which leads to cancer growth and development. We formulate a mathematical model that studies three possible dynamics of the treatment and establish the effects of the immune checkpoints on the immune system and the treatment at large. Although the effect cannot be seen explicitly in the analysis of the model, we show it by numerical simulations.
Contributors
Jinghao Men

Metadata information

hasTaxon
Taxonomy Homo sapiens
isVersionOf
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model
0000292
isDescribedBy
occursIn

Curation status
Curated


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Model files

Saad2017.xml SBML L3V1 representation of checkpoint-immune-BCG-bladder cancer model 67.25 KB Preview | Download

Additional files

Fig.2B.png Fig.2 generated in the no checkpoint submodel 10.69 KB Preview | Download
Fig.1.png Fig.1 generated in the no treatment submodel 13.79 KB Preview | Download
Fig.3'.png Fig.3 generated in the main model 10.84 KB Preview | Download
Saad2017-no treatment.xml submodel-no treatment 66.55 KB Preview | Download
Fig.2C.png Fig.2 generated in the no checkpoint submodel 11.68 KB Preview | Download
Saad2017-no treatment.cps CPS file of the submodel in COPASI 79.27 KB Preview | Download
Saad2017.cps CPS file of the model in COPASI 82.58 KB Preview | Download
Saad2017-no checkpoint.xml submodel-no checkpoint 57.86 KB Preview | Download
Fig.2E.png Fig.2 generated in the no checkpoint submodel 11.60 KB Preview | Download
Fig.1'.png Fig.1 generated in the no treatment submodel 10.99 KB Preview | Download
Saad2017-no checkpoint.cps CPS file of the submodel in COPASI 70.08 KB Preview | Download
Saad2017.sedml Auto-generated SEDML file 1.09 KB Preview | Download

  • Model originally submitted by : Jinghao Men
  • Submitted: 10-Jul-2019 12:56:18
  • Last Modified: 10-Jul-2019 12:56:18
Revisions
  • Version: 4 public model Download this version
    • Submitted on: 10-Jul-2019 12:56:18
    • Submitted by: Jinghao Men
    • With comment: Automatically added model identifier BIOMD0000000746
Curator's comment:
(added: 10 Jul 2019, 12:55:33, updated: 10 Jul 2019, 12:55:33)
Publication figure 3 reproduced as per literature. Other figures are produced in the submodels. Figure data is generated using COPASI 4.25 (build 197).