Eftimie2019-Macrophages Plasticity

  public model
Model Identifier
BIOMD0000000806
Short description
This paper describes the complex interactions between two extreme types of macrophages (M1 and M2 cells), effector T cells and an oncolytic Vesicular Stomatitis Virus (VSV), on the growth/elimination of B16F10 melanoma. The mathematics model descirbes, in terms of VSV and macrophages levels, two different types of immune responses which could ensure tumour control and eventual elimination. It shows that both innate and adaptive anti-tumour immune responses, as well as the oncolytic virus, could be very important in delaying tumour relapse and eventually eliminating the tumour. Overall this study supports the use mathematical modelling to increase our understanding of the complex immune interaction following oncolytic virotherapies. However, the complexity of the model combined with a lack of sufficient data for model parametrisation has an impact on the possibility of making quantitative predictions. The Model was created using COPASI version 4.24 (Build 197)
Format
SBML (L3V1)
Related Publication
  • Investigating Macrophages Plasticity Following Tumour-Immune Interactions During Oncolytic Therapies.
  • Eftimie R, Eftimie G
  • Acta biotheoretica , 8/ 2019 , PubMed ID: 31410657
  • Division of Mathematics, University of Dundee, Dundee, DD1 4HN, UK. r.a.eftimie@dundee.ac.uk.
  • Over the last few years, oncolytic virus therapy has been recognised as a promising approach in cancer treatment, due to the potential of these viruses to induce systemic anti-tumour immunity and selectively killing tumour cells. However, the effectiveness of these viruses depends significantly on their interactions with the host immune responses, both innate (e.g., macrophages, which accumulate in high numbers inside solid tumours) and adaptive (e.g., [Formula: see text] T cells). In this article, we consider a mathematical approach to investigate the possible outcomes of the complex interactions between two extreme types of macrophages (M1 and M2 cells), effector [Formula: see text] T cells and an oncolytic Vesicular Stomatitis Virus (VSV), on the growth/elimination of B16F10 melanoma. We discuss, in terms of VSV, [Formula: see text] and macrophages levels, two different types of immune responses which could ensure tumour control and eventual elimination. We show that both innate and adaptive anti-tumour immune responses, as well as the oncolytic virus, could be very important in delaying tumour relapse and eventually eliminating the tumour. Overall this study supports the use mathematical modelling to increase our understanding of the complex immune interaction following oncolytic virotherapies. However, the complexity of the model combined with a lack of sufficient data for model parametrisation has an impact on the possibility of making quantitative predictions.
Contributors
Submitter of the first revision: Szeyi Ng
Submitter of this revision: Szeyi Ng
Modellers: Szeyi Ng

Metadata information

is (2 statements)
BioModels Database BIOMD0000000806
BioModels Database MODEL1909050001

isDescribedBy (1 statement)
PubMed 31410657

hasTaxon (2 statements)
hasProperty (6 statements)
Gene Ontology regulation of immune response to tumor cell
Mathematical Modelling Ontology Ordinary differential equation model
Human Disease Ontology skin cancer
Human Disease Ontology cancer
NCIt Oncolytic Virus Therapy
Experimental Factor Ontology cancer

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

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files
model.xml SBML L3V1 file for the model 129.75 KB Preview | Download

Additional files
Eftimie2019-Macrophages Plasticity.cps COPASI 4.24 (Build 197) file for the model 153.67 KB Preview | Download
Macrophages Plasticity a.sedml Sedml L1V2 file producing figure 5a(i) 6.57 KB Preview | Download
Macrophages Plasticity b.sedml Sedml L1V2 file producing figure 2b(i) 6.86 KB Preview | Download
figure.png Reproduced figure 2b(i) and 5a(i) 113.28 KB Preview | Download

  • Model originally submitted by : Szeyi Ng
  • Submitted: Sep 5, 2019 11:44:02 AM
  • Last Modified: Oct 3, 2019 2:35:06 PM
Revisions
  • Version: 9 public model Download this version
    • Submitted on: Oct 3, 2019 2:35:06 PM
    • Submitted by: Szeyi Ng
    • With comment: Automatically added model identifier BIOMD0000000806
  • Version: 6 public model Download this version
    • Submitted on: Oct 2, 2019 2:11:09 PM
    • Submitted by: Szeyi Ng
    • With comment: Model revised without commit message
  • Version: 5 public model Download this version
    • Submitted on: Sep 5, 2019 11:44:02 AM
    • Submitted by: Szeyi Ng
    • With comment: Automatically added model identifier BIOMD0000000806

(*) 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
UnInfected Tumour Cells Xu

cancer ; B16-F10 cell 		500000.0 mmol
M1 Macrophage Xm1

M1 Macrophage 		0.0 mmol
Infected Tumour Cells Xi

B16-F10 cell ; EFO:0000311 ; infected cell 		0.0 mmol
Effector Cytotoxic CD8 TCells Xe

CD8-positive, alpha-beta cytotoxic T cell 		0.0 mmol
Virus Xv

Vesicular stomatitis virus 		0.0 mmol
M2 Macrophage Xm2

M2 Macrophage 		0.0 mmol
Reactions
Reactions Rate Parameters
UnInfected_Tumour_Cells_Xu => Infected_Tumour_Cells_Xi; Virus_Xv compartment*d_v*Virus_Xv*UnInfected_Tumour_Cells_Xu/(v_h_u+UnInfected_Tumour_Cells_Xu) v_h_u = 100000.0; d_v = 0.011
=> M1_Macrophage_Xm1; Infected_Tumour_Cells_Xi, Virus_Xv compartment*v_a_1*(Infected_Tumour_Cells_Xi+Virus_Xv) v_a_1 = 1.0E-6 1/ms
Infected_Tumour_Cells_Xi => compartment*delta_i*Infected_Tumour_Cells_Xi delta_i = 0.475 1/ms
Effector_Cytotoxic_CD8_TCells__Xe => ; UnInfected_Tumour_Cells_Xu compartment*d_t*UnInfected_Tumour_Cells_Xu*Effector_Cytotoxic_CD8_TCells__Xe d_t = 1.0E-10 1/ms
=> Virus_Xv; Infected_Tumour_Cells_Xi compartment*delta_i*b*Infected_Tumour_Cells_Xi delta_i = 0.475 1/ms; b = 2500.0
Virus_Xv => ; Virus_Xv compartment*omega*Virus_Xv omega = 2.0 1/ms
M2_Macrophage_Xm2 => M1_Macrophage_Xm1; Virus_Xv compartment*M2_Macrophage_Xm2*(o_r_m2+v_r_m2*Virus_Xv/(h_v+Virus_Xv)) h_v = 0.105636; v_r_m2 = 0.5 1/ms; o_r_m2 = 0.001 1/ms
UnInfected_Tumour_Cells_Xu => ; Effector_Cytotoxic_CD8_TCells__Xe compartment*d_u*UnInfected_Tumour_Cells_Xu*Effector_Cytotoxic_CD8_TCells__Xe/(h_e+Effector_Cytotoxic_CD8_TCells__Xe) d_u = 0.44; h_e = 1.0
=> M2_Macrophage_Xm2; UnInfected_Tumour_Cells_Xu compartment*u_a_2*UnInfected_Tumour_Cells_Xu u_a_2 = 4.0E-8 1/ms
Virus_Xv => ; Virus_Xv, Effector_Cytotoxic_CD8_TCells__Xe compartment*v_d_u*Virus_Xv*Effector_Cytotoxic_CD8_TCells__Xe/(h_e+Effector_Cytotoxic_CD8_TCells__Xe) h_e = 1.0; v_d_u = 4.4 1/ms
Curator's comment:
(added: 05 Sep 2019, 11:11:28, updated: 05 Sep 2019, 12:31:54)
I reproduced Fig.2 (b)(i) from the paper, using COPASI and the file eftimie2019-2.sedml and setting time equals 22 days. In this figure, v_r_m2=0 I reproduced Fig.5 (a)(i) from the paper,using COPASI and file eftimie2019-2.sedml to generate the data, setting time equals 80 days and plotting the figure using python. In this figure, change v_r_m2 to 0.5 The data h_v=0.105636 was not found in the paper, and was generated by using Parameter Estimation in COPASI.