Parra_Guillen2013 - Mathematical model approach to describe tumour response in mice after vaccine administration_model1

  public model
Model Identifier
BIOMD0000000914
Short description
Mathematical model approach to describe tumour response in mice after vaccine administration and its applicability to immune-stimulatory cytokine-based strategies.

Parra-Guillen ZP1, Berraondo P, Grenier E, Ribba B, Troconiz IF.
Author information
Abstract

Immunotherapy is a growing therapeutic strategy in oncology based on the stimulation of innate and adaptive immune systems to induce the death of tumour cells. In this paper, we have developed a population semi-mechanistic model able to characterize the mechanisms implied in tumour growth dynamic after the administration of CyaA-E7, a vaccine able to target antigen to dendritic cells, thus triggering a potent immune response. The mathematical model developed presented the following main components: (1) tumour progression in the animals without treatment was described with a linear model, (2) vaccine effects were modelled assuming that vaccine triggers a non-instantaneous immune response inducing cell death. Delayed response was described with a series of two transit compartments, (3) a resistance effect decreasing vaccine efficiency was also incorporated through a regulator compartment dependent upon tumour size, and (4) a mixture model at the level of the elimination of the induced signal vaccine (k 2) to model tumour relapse after treatment, observed in a small percentage of animals (15.6%). The proposed model structure was successfully applied to describe antitumor effect of IL-12, suggesting its applicability to different immune-stimulatory therapies. In addition, a simulation exercise to evaluate in silico the impact on tumour size of possible combination therapies has been shown. This type of mathematical approaches may be helpful to maximize the information obtained from experiments in mice, reducing the number of animals and the cost of developing new antitumor immunotherapies.
Format
SBML (L2V4)
Related Publication
  • Mathematical model approach to describe tumour response in mice after vaccine administration and its applicability to immune-stimulatory cytokine-based strategies.
  • Parra-Guillen ZP, Berraondo P, Grenier E, Ribba B, Troconiz IF
  • The AAPS journal , 7/ 2013 , Volume 15 , Issue 3 , pages: 797-807 , PubMed ID: 23605806
  • Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Navarra, C/Irunlarrea 1, 31008, Pamplona, Navarra, Spain.
  • Immunotherapy is a growing therapeutic strategy in oncology based on the stimulation of innate and adaptive immune systems to induce the death of tumour cells. In this paper, we have developed a population semi-mechanistic model able to characterize the mechanisms implied in tumour growth dynamic after the administration of CyaA-E7, a vaccine able to target antigen to dendritic cells, thus triggering a potent immune response. The mathematical model developed presented the following main components: (1) tumour progression in the animals without treatment was described with a linear model, (2) vaccine effects were modelled assuming that vaccine triggers a non-instantaneous immune response inducing cell death. Delayed response was described with a series of two transit compartments, (3) a resistance effect decreasing vaccine efficiency was also incorporated through a regulator compartment dependent upon tumour size, and (4) a mixture model at the level of the elimination of the induced signal vaccine (k 2) to model tumour relapse after treatment, observed in a small percentage of animals (15.6%). The proposed model structure was successfully applied to describe antitumor effect of IL-12, suggesting its applicability to different immune-stimulatory therapies. In addition, a simulation exercise to evaluate in silico the impact on tumour size of possible combination therapies has been shown. This type of mathematical approaches may be helpful to maximize the information obtained from experiments in mice, reducing the number of animals and the cost of developing new antitumor immunotherapies.
Contributors
Submitter of the first revision: Mohammad Umer Sharif Shohan
Submitter of this revision: Mohammad Umer Sharif Shohan
Modellers: Mohammad Umer Sharif Shohan

Metadata information

is (2 statements)
BioModels Database MODEL2001220002
BioModels Database BIOMD0000000914

isDescribedBy (1 statement)
PubMed 23605806

hasTaxon (1 statement)
Taxonomy Mus musculus

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


Curation status
Curated



Connected external resources

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Model files

Parra_Guillen2013.xml SBML L2V4 Parra_Guillen2013 - Mathematical model approach to describe tumour response in mice after vaccine administration_model1 37.53 KB Preview | Download

Additional files

Parra_Guillen2013.cps COPASI version 4.24 (Build 197) Parra_Guillen2013 - Mathematical model approach to describe tumour response in mice after vaccine administration_model1 69.91 KB Preview | Download
Parra_Guillen2013.sedml SEDML L1V2 Dubey2007 - Parra_Guillen2013 - Mathematical model approach to describe tumour response in mice after vaccine administration_model1 3.70 KB Preview | Download

  • Model originally submitted by : Mohammad Umer Sharif Shohan
  • Submitted: Jan 22, 2020 2:37:42 PM
  • Last Modified: Jan 22, 2020 2:37:42 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Jan 22, 2020 2:37:42 PM
    • Submitted by: Mohammad Umer Sharif Shohan
    • With comment: Automatically added model identifier BIOMD0000000914
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
Ts

Tumor Mass
0.324 mmol
SVAC

Signal ; Vaccine ; Signal
0.0 mmol
REG

Regulator
0.0 mmol
VAC

Vaccine
1.0 mmol
TRAN 0.0 mmol
Reactions
Reactions Rate Parameters
Ts => ; REG, SVAC compartment*k3*REG_50^gamma/(REG_50^gamma+REG^gamma)*Ts*SVAC gamma = 5.24; REG_50 = 3.18; k3 = 1.08
SVAC => compartment*k2_pop2*SVAC k2_pop2 = 0.0907
=> REG; Ts compartment*k4*Ts k4 = 0.039
=> SVAC; TRAN compartment*k1*TRAN k1 = 0.0907
=> Ts compartment*gamma gamma = 5.24
REG => compartment*k4*REG k4 = 0.039
VAC => compartment*k1*VAC k1 = 0.0907
TRAN => compartment*k1*TRAN k1 = 0.0907
=> TRAN; VAC compartment*k1*VAC k1 = 0.0907
Curator's comment:
(added: 22 Jan 2020, 14:37:24, updated: 22 Jan 2020, 14:37:24)
The model has been encoded in COPASI and the Figure 2 of the publication has been reproduced usig COPASI The paper lacked the initial condition as well as wrongly presented the value of VAC. From the figure The value was changed to 1. But with the other parameters were left as it was before