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BIOMD0000000314 - Raia2011_IL13_L1236

 

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Reference Publication
Publication ID: 21127196
Raia V, Schilling M, Böhm M, Hahn B, Kowarsch A, Raue A, Sticht C, Bohl S, Saile M, Möller P, Gretz N, Timmer J, Theis F, Lehmann WD, Lichter P, Klingmüller U.
Dynamic mathematical modeling of IL13-induced signaling in Hodgkin and primary mediastinal B-cell lymphoma allows prediction of therapeutic targets.
Cancer Res. 2011 Feb; 71(3): 693-704
Division of Systems Biology of Signal Transduction, DKFZ-ZMBH Alliance and Molecular Genetics, German Cancer Research Center, Heidelberg, Germany.  [more]
Model
Original Model: BIOMD0000000314.xml.origin
Submitter: Marcel Schilling
Submission ID: MODEL1102020002
Submission Date: 02 Feb 2011 09:47:17 UTC
Last Modification Date: 07 Jun 2013 15:08:38 UTC
Creation Date: 14 Feb 2011 03:36:22 UTC
Encoders:  Lukas Endler
   Marcel Schilling
set #1
bqbiol:occursIn Taxonomy Homo sapiens
ICD C81
Brenda Tissue Ontology BTO:0004973
bqbiol:isVersionOf KEGG Pathway hsa04630
Gene Ontology JAK-STAT cascade
set #2
bqbiol:isVersionOf Reactome REACT_22232
Notes

This is the model of IL13 induced signalling in L1236 cells described in the article:
Dynamic Mathematical Modeling of IL13-Induced Signaling in Hodgkin and Primary Mediastinal B-Cell Lymphoma Allows Prediction of Therapeutic Targets.
Raia V, Schilling M, Böhm M, Hahn B, Kowarsch A, Raue A, Sticht C, Bohl S, Saile M, Möller P, Gretz N, Timmer J, Theis F, Lehmann WD, Lichter P and Klingmüller U. Cancer Res. 2011 Feb 1;71(3):693-704. PubmedID: 21127196 ; DOI: 10.1158/0008-5472.CAN-10-2987
Abstract:
Primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of JAK (Janus kinase)/STAT signaling pathway. Because of complex, nonlinear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. We report the development of dynamic pathway models based on quantitative data collected on signaling components of JAK/STAT pathway in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We show that the amounts of STAT5 and STAT6 are higher whereas those of SHP1 are lower in the two lymphoma cell lines than in normal B cells. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In both lymphoma cell lines, we observe interleukin-13 (IL13)-induced activation of IL4 receptor α, JAK2, and STAT5, but not of STAT6. Genome-wide, 11 early and 16 sustained genes are upregulated by IL13 in both lymphoma cell lines. Specifically, the known STAT-inducible negative regulators CISH and SOCS3 are upregulated within 2 hours in MedB-1 but not in L1236 cells. On the basis of this detailed quantitative information, we established two mathematical models, MedB-1 and L1236 model, able to describe the respective experimental data. Most of the model parameters are identifiable and therefore the models are predictive. Sensitivity analysis of the model identifies six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1. We experimentally confirm reduction in target gene expression in response to inhibition of STAT5 phosphorylation, thereby validating one of the predicted targets.

All concentrations in the model, apart from IL13, are in molecules/cell. IL13 is given in ng/ml. As the cell volume is not explicitely given in the article, it is just approximately derived from the MW of IL13 (15.8 kDa) and the conversion factor 3.776 molecules IL13/cell = 1 ng/ml to be around 100 fl.

SBML model exported from PottersWheel on 2010-08-10 12:14:57.
Inline follows the original matlab code:

% PottersWheel model definition file

function m = Raia2010_IL13_L1236()

m             = pwGetEmptyModel();

%% Meta information

m.ID          = 'Raia2010_IL13_L1236';
m.name        = 'Raia2010_IL13_L1236';
m.description = '';
m.authors     = {'Raia et al'};
m.dates       = {'2010'};
m.type        = 'PW-2-0-47';

%% X: Dynamic variables
% m = pwAddX(m, ID, startValue, type, minValue, maxValue, unit, compartment, name, description, typeOfStartValue)

m = pwAddX(m, 'Rec'         ,              1.8, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'Rec_i'       , 118.598421286338, 'global',  0.001, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'IL13_Rec'    ,                0, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'p_IL13_Rec'  ,                0, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'p_IL13_Rec_i',                0, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'JAK2'        ,               24, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'pJAK2'       ,                0, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'SHP1'        ,              9.4, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'STAT5'       ,              209, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'pSTAT5'      ,                0, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'CD274mRNA'   ,                0, 'fix'   , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', []  , []  , []             , []  , 'protein.generic');


%% R: Reactions
% m = pwAddR(m, reactants, products, modifiers, type, options, rateSignature, parameters, description, ID, name, fast, compartments, parameterTrunks, designerPropsR, stoichiometry, reversible)

m = pwAddR(m, {'Rec'         }, {'IL13_Rec'    }, {'IL13stimulation'}, 'C' , [] , 'k1 * m1 * r1 * 3.776', {'Kon_IL13Rec'             });
m = pwAddR(m, {'Rec'         }, {'Rec_i'       }, {                 }, 'MA', [] , []                    , {'Rec_intern'              });
m = pwAddR(m, {'Rec_i'       }, {'Rec'         }, {                 }, 'MA', [] , []                    , {'Rec_recycle'             });
m = pwAddR(m, {'IL13_Rec'    }, {'p_IL13_Rec'  }, {'pJAK2'          }, 'E' , [] , []                    , {'Rec_phosphorylation'     });
m = pwAddR(m, {'JAK2'        }, {'pJAK2'       }, {'IL13_Rec'       }, 'E' , [] , []                    , {'JAK2_phosphorylation'    });
m = pwAddR(m, {'JAK2'        }, {'pJAK2'       }, {'p_IL13_Rec'     }, 'E' , [] , []                    , {'JAK2_phosphorylation'    });
m = pwAddR(m, {'p_IL13_Rec'  }, {'p_IL13_Rec_i'}, {                 }, 'MA', [] , []                    , {'pRec_intern'             });
m = pwAddR(m, {'p_IL13_Rec_i'}, {              }, {                 }, 'MA', [] , []                    , {'pRec_degradation'        });
m = pwAddR(m, {'pJAK2'       }, {'JAK2'        }, {'SHP1'           }, 'E' , [] , []                    , {'pJAK2_dephosphorylation' });
m = pwAddR(m, {'STAT5'       }, {'pSTAT5'      }, {'pJAK2'          }, 'E' , [] , []                    , {'STAT5_phosphorylation'   });
m = pwAddR(m, {'pSTAT5'      }, {'STAT5'       }, {'SHP1'           }, 'E' , [] , []                    , {'pSTAT5_dephosphorylation'});
m = pwAddR(m, {              }, {'CD274mRNA'   }, {'pSTAT5'         }, 'C' , [] , 'm1*k1'               , {'CD274mRNA_production'    });



%% C: Compartments
% m = pwAddC(m, ID, size,  outside, spatialDimensions, name, unit, constant)

m = pwAddC(m, 'cell', 1);


%% K: Dynamical parameters
% m = pwAddK(m, ID, value, type, minValue, maxValue, unit, name, description)

m = pwAddK(m, 'Kon_IL13Rec'             , 0.00174086832237195, 'global', 1e-009, 1000);
m = pwAddK(m, 'Rec_phosphorylation'     , 9.07540737285078   , 'global', 1e-009, 1000);
m = pwAddK(m, 'pRec_intern'             , 0.324132341358502  , 'global', 1e-009, 1000);
m = pwAddK(m, 'pRec_degradation'        , 0.417538218767296  , 'global', 1e-009, 1000);
m = pwAddK(m, 'Rec_intern'              , 0.259685756311325  , 'global', 1e-009, 1000);
m = pwAddK(m, 'Rec_recycle'             , 0.00392430355501153, 'global', 1e-009, 1000);
m = pwAddK(m, 'JAK2_phosphorylation'    , 0.300019047540849  , 'global', 1e-009, 1000);
m = pwAddK(m, 'pJAK2_dephosphorylation' , 0.0981610557569751 , 'global', 1e-009, 1000);
m = pwAddK(m, 'STAT5_phosphorylation'   , 0.00426766529531612, 'global', 1e-009, 1000);
m = pwAddK(m, 'pSTAT5_dephosphorylation', 0.0116388587580445 , 'global', 1e-009, 1000);
m = pwAddK(m, 'CD274mRNA_production'    , 0.0115927572109515 , 'global', 1e-009, 1000);


%% U: Driving input
% m = pwAddU(m, ID, uType, uTimes, uValues, compartment, name, description, u2Values, alternativeIDs, designerProps)

m = pwAddU(m, 'IL13stimulation', 'steps', [-100 0]  , [0 1]  , [], [], [], [], {}, [], 'protein.generic');


%% Default sampling time points
m.t = 0:1:120;


%% Y: Observables
% m = pwAddY(m, rhs, ID, scalingParameter, errorModel, noiseType, unit, name, description, alternativeIDs, designerProps)

m = pwAddY(m, 'Rec + IL13_Rec + p_IL13_Rec'         , 'RecSurf_obs'  , 'scale_RecSurf'  , '0.1 * y + 0.1 * max(y)');
m = pwAddY(m, 'IL13_Rec + p_IL13_Rec + p_IL13_Rec_i', 'IL13-cell_obs', 'scale_IL13-cell', '0.15 * y + 0.05 * max(y)');
m = pwAddY(m, 'p_IL13_Rec + p_IL13_Rec_i'           , 'pIL4Ra_obs'   , 'scale_pIL4Ra'   , '0.10 * y + 0.15 * max(y)');
m = pwAddY(m, 'pJAK2'                               , 'pJAK2_obs'    , 'scale_pJAK2'    , '0.1 * y + 0.1 * max(y)');
m = pwAddY(m, 'CD274mRNA'                           , 'CD274mRNA_obs', 'scale_CD274mRNA', '0.1 * y + 0.1 * max(y)');
m = pwAddY(m, 'pSTAT5'                              , 'pSTAT5_obs'   , 'scale_pSTAT5'   , '0.1 * y + 0.1 * max(y)');


%% S: Scaling parameters
% m = pwAddS(m, ID, value, type, minValue, maxValue, unit, name, description)

m = pwAddS(m, 'scale_pJAK2'    , 0.469836894150194, 'global',  0.001, 10000);
m = pwAddS(m, 'scale_pIL4Ra'   ,  1.80002942264669, 'global',  0.001, 10000);
m = pwAddS(m, 'scale_RecSurf'  ,                 1,    'fix', 0.0001, 10000);
m = pwAddS(m, 'scale_IL13-cell',  174.726805005048, 'global',  0.001, 10000);
m = pwAddS(m, 'scale_CD274mRNA', 0.110568221201943, 'global',  0.001, 10000);
m = pwAddS(m, 'scale_pSTAT5'   ,                 1,    'fix',  0.001, 10000);


%% Designer properties (do not modify)
m.designerPropsM = [1 1 1 0 0 0 400 250 600 400 1 1 1 0 0 0 0];
Model
Publication ID: 21127196 Submission Date: 02 Feb 2011 09:47:17 UTC Last Modification Date: 07 Jun 2013 15:08:38 UTC Creation Date: 14 Feb 2011 03:36:22 UTC
Mathematical expressions
Reactions
reaction_1 reaction_2 reaction_3 reaction_4
reaction_5 reaction_6 reaction_7 reaction_8
reaction_9 reaction_10 reaction_11 reaction_12
Rules
Assignment Rule (variable: IL13)      
Physical entities
Compartments Species
cell Rec Rec_i IL13_Rec
p_IL13_Rec p_IL13_Rec_i JAK2
pJAK2 SHP1 STAT5
pSTAT5 CD274mRNA IL13
Global parameters
IL13stimulation Kon_IL13Rec Rec_phosphorylation pRec_intern
pRec_degradation Rec_intern Rec_recycle JAK2_phosphorylation
pJAK2_dephosphorylation STAT5_phosphorylation pSTAT5_dephosphorylation CD274mRNA_production
Reactions (12)
 
 reaction_1 [Rec] → [IL13_Rec];   {IL13}
 
 reaction_2 [Rec] → [Rec_i];  
 
 reaction_3 [Rec_i] → [Rec];  
 
 reaction_4 [IL13_Rec] → [p_IL13_Rec];   {pJAK2}
 
 reaction_5 [JAK2] → [pJAK2];   {IL13_Rec}
 
 reaction_6 [JAK2] → [pJAK2];   {p_IL13_Rec}
 
 reaction_7 [p_IL13_Rec] → [p_IL13_Rec_i];  
 
 reaction_8 [p_IL13_Rec_i] → ;  
 
 reaction_9 [pJAK2] → [JAK2];   {SHP1}
 
 reaction_10 [STAT5] → [pSTAT5];   {pJAK2}
 
 reaction_11 [pSTAT5] → [STAT5];   {SHP1}
 
 reaction_12  → [CD274mRNA];   {pSTAT5}
 
Rules (1)
 
 Assignment Rule (name: IL13) IL13 = 3.776*IL13stimulation
 
 cell Spatial dimensions: 3.0  Compartment size: 100.0
 
 Rec
Compartment: cell
Initial concentration: 1.8
 
 Rec_i
Compartment: cell
Initial concentration: 118.598
 
 IL13_Rec
Compartment: cell
Initial concentration: 0.0
 
 p_IL13_Rec
Compartment: cell
Initial concentration: 0.0
 
 p_IL13_Rec_i
Compartment: cell
Initial concentration: 0.0
 
 JAK2
Compartment: cell
Initial concentration: 24.0
 
 pJAK2
Compartment: cell
Initial concentration: 0.0
 
 SHP1
Compartment: cell
Initial concentration: 9.4
 
 STAT5
Compartment: cell
Initial concentration: 209.0
 
 pSTAT5
Compartment: cell
Initial concentration: 0.0
 
 CD274mRNA
Compartment: cell
Initial concentration: 0.0
 
  IL13
Compartment: cell
 
Global Parameters (12)
 
 IL13stimulation
Value: 1.0   (Units: ng_per_ml)
Constant
 
 Kon_IL13Rec
Value: 0.00174087
Constant
 
 Rec_phosphorylation
Value: 9.07541
Constant
 
 pRec_intern
Value: 0.324132
Constant
 
 pRec_degradation
Value: 0.417538
Constant
 
 Rec_intern
Value: 0.259686
Constant
 
 Rec_recycle
Value: 0.0039243
Constant
 
 JAK2_phosphorylation
Value: 0.300019
Constant
 
 pJAK2_dephosphorylation
Value: 0.0981611
Constant
 
 STAT5_phosphorylation
Value: 0.00426767
Constant
 
 pSTAT5_dephosphorylation
Value: 0.0116389
Constant
 
 CD274mRNA_production
Value: 0.0115928
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000314

Curator's comment: (updated: 14 Feb 2011 03:56:30 GMT)

Time course simulations with varying IL13 stimulation as in figure S27A of the supplement of the original publication. Integration was performed using SBML ODESolver.

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