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BIOMD0000000521 - Ribba2012 - Low-grade gliomas, tumour growth inhibition model

 

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Reference Publication
Publication ID: 22761472
Ribba B, Kaloshi G, Peyre M, Ricard D, Calvez V, Tod M, Cajavec-Bernard B, Idbaih A, Psimaras D, Dainese L, Pallud J, Cartalat-Carel S, Delattre JY, Honnorat J, Grenier E, Ducray F.
A tumor growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy.
Clin. Cancer Res. 2012 Sep; 18(18): 5071-5080
Ribba, INRIA, Project-team NUMED, Ecole Normale Superieure de Lyon, 46 allee d0Italie, 69007 Lyon Cedex 07, France. benjamin.ribba@inria.fr  [more]
Model
Original Model: BIOMD0000000521.xml.origin
Submitter: Vijayalakshmi Chelliah
Submission ID: MODEL1402250000
Submission Date: 25 Feb 2014 11:43:46 UTC
Last Modification Date: 03 Mar 2014 14:24:41 UTC
Creation Date: 01 Mar 2014 16:41:17 UTC
Encoders:  Vijayalakshmi Chelliah
set #1
bqbiol:isVersionOf Gene Ontology defense response to tumor cell
Human Disease Ontology DOID:0060101
bqbiol:hasTaxon Taxonomy Homo sapiens
bqbiol:hasProperty Mathematical Modelling Ontology MAMO_0000046
Notes
Ribba2012 - Low-grade gliomas, tumour growth inhibition model

Using longitudinal mean tumour diameter (MTD) data, this model describe the size evolution of low-grade glioma (LGG) in patients treated with chemotherapy or radiotherapy.

This model is described in the article:

Ribba B, Kaloshi G, Peyre M, Ricard D, Calvez V, Tod M, Cajavec-Bernard B, Idbaih A, Psimaras D, Dainese L, Pallud J, Cartalat-Carel S, Delattre JY, Honnorat J, Grenier E, Ducray F.
Clin. Cancer Res. 2012 Sep; 18(18): 5071-5080

Abstract:

PURPOSE: To develop a tumor growth inhibition model for adult diffuse low-grade gliomas (LGG) able to describe tumor size evolution in patients treated with chemotherapy or radiotherapy.

EXPERIMENTAL DESIGN: Using longitudinal mean tumor diameter (MTD) data from 21 patients treated with first-line procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-l-nitrosourea, and vincristine (PCV) chemotherapy, we formulated a model consisting of a system of differential equations, incorporating tumor-specific and treatment-related parameters that reflect the response of proliferative and quiescent tumor tissue to treatment. The model was then applied to the analysis of longitudinal tumor size data in 24 patients treated with first-line temozolomide (TMZ) chemotherapy and in 25 patients treated with first-line radiotherapy.

RESULTS: The model successfully described the MTD dynamics of LGG before, during, and after PCV chemotherapy. Using the same model structure, we were also able to successfully describe the MTD dynamics in LGG patients treated with TMZ chemotherapy or radiotherapy. Tumor-specific parameters were found to be consistent across the three treatment modalities. The model is robust to sensitivity analysis, and preliminary results suggest that it can predict treatment response on the basis of pretreatment tumor size data.

CONCLUSIONS: Using MTD data, we propose a tumor growth inhibition model able to describe LGG tumor size evolution in patients treated with chemotherapy or radiotherapy. In the future, this model might be used to predict treatment efficacy in LGG patients and could constitute a rational tool to conceive more effective chemotherapy schedules.

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.

Model
Publication ID: 22761472 Submission Date: 25 Feb 2014 11:43:46 UTC Last Modification Date: 03 Mar 2014 14:24:41 UTC Creation Date: 01 Mar 2014 16:41:17 UTC
Mathematical expressions
Rules
Assignment Rule (variable: Pstar) Rate Rule (variable: PCV_plasma) Rate Rule (variable: Proliferative tissue) Rate Rule (variable: nonproliferative quiescent tissue)
Rate Rule (variable: damaged quiescent cells)      
Physical entities
Compartments Species
plasma PCV_plasma    
tissue Proliferative tissue nonproliferative quiescent tissue damaged quiescent cells
Global parameters
Pstar P0 Q0 lambda_P
k_PQ k_Qp_P delta_QP gamma
KDE K    
Reactions (0)
Rules (5)
 
 Assignment Rule (name: Pstar) Pstar = P+Q+Qp
 
 Rate Rule (name: C) d [ PCV_plasma] / d t= (-KDE)*C
 
 Rate Rule (name: P) d [ Proliferative tissue] / d t= lambda_P*P*(1-Pstar/K)+k_Qp_P*Qp-k_PQ*P-gamma*C*KDE*P
 
 Rate Rule (name: Q) d [ nonproliferative quiescent tissue] / d t= k_PQ-gamma*C*KDE*Q
 
 Rate Rule (name: Qp) d [ damaged quiescent cells] / d t= gamma*C*KDE*Q-k_Qp_P*Qp-delta_QP*Qp
 
 plasma Spatial dimensions: 3.0  Compartment size: 1.0
 
 PCV_plasma
Compartment: plasma
Initial concentration: 1.0
 
 tissue Spatial dimensions: 3.0  Compartment size: 1.0
 
 Proliferative tissue
Compartment: tissue
Initial concentration: 7.13
 
 nonproliferative quiescent tissue
Compartment: tissue
Initial concentration: 41.2
 
 damaged quiescent cells
Compartment: tissue
Initial concentration: 0.0
 
Global Parameters (10)
 
   Pstar  
 
   P0
Value: 7.13
Constant
 
   Q0
Value: 41.2
Constant
 
   lambda_P
Value: 0.121
Constant
 
   k_PQ
Value: 0.00295
Constant
 
   k_Qp_P
Value: 0.0031
Constant
 
   delta_QP
Value: 0.0087
Constant
 
   gamma
Value: 0.729
Constant
 
   KDE
Value: 0.24
Constant
 
   K
Value: 100.0
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000521

Curator's comment: (updated: 03 Mar 2014 11:31:48 GMT)

Population prediction (Figure 4 - top right - dashed line) based on the mean parameter values for PCV (Table 1) treatment is reproduced here. The model was simulated using Copasi v4.11 (Build 64). The plot was generated using Gnuplot.

Note: Parameter values corresponding to individual subjects can be obtained on request (to biomodels-cura@ebi.ac.uk).

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