Jung2019 - egulating glioblastoma signaling pathways and anti-invasion therapy cell cycle dynamics model

  public model
Model Identifier
BIOMD0000000829
Short description
This model is based on paper, based on its cell cycle dynamics model: Strategies in regulating glioblastoma signaling pathways and anti-invasion therapy Abstract: Glioblastoma multiforme is one of the most invasive type of glial tumors, which rapidly grows and commonly spreads into nearby brain tissue. It is a devastating brain cancer that often results in death within approximately 12 to 15 months after diagnosis. In this work, optimal control theory was applied to regulate intracellular signaling pathways of miR-451–AMPK–mTOR–cell cycle dynamics via glucose and drug intravenous administration infusions. Glucose level is controlled to activate miR-451 in the up-stream pathway of the model. A potential drug blocking the inhibitory pathway of mTOR by AMPK complex is incorporated to explore regulation of the down-stream pathway to the cell cycle. Both miR-451 and mTOR levels are up-regulated inducing cell proliferation and reducing invasion in the neighboring tissues. Concomitant and alternating glucose and drug infusions are explored under various circumstances to predict best clinical outcomes with least administration costs.
Format
SBML (L2V4)
Related Publication
  • Strategies in regulating glioblastoma signaling pathways and anti-invasion therapy.
  • Jung E, de Los Reyes V AA, Pumares KJA, Kim Y
  • PloS one , 1/ 2019 , Volume 14 , Issue 4 , pages: e0215547 , PubMed ID: 31009513
  • Department of Mathematics, Konkuk University, Seoul, Republic of Korea.
  • Glioblastoma multiforme is one of the most invasive type of glial tumors, which rapidly grows and commonly spreads into nearby brain tissue. It is a devastating brain cancer that often results in death within approximately 12 to 15 months after diagnosis. In this work, optimal control theory was applied to regulate intracellular signaling pathways of miR-451-AMPK-mTOR-cell cycle dynamics via glucose and drug intravenous administration infusions. Glucose level is controlled to activate miR-451 in the up-stream pathway of the model. A potential drug blocking the inhibitory pathway of mTOR by AMPK complex is incorporated to explore regulation of the down-stream pathway to the cell cycle. Both miR-451 and mTOR levels are up-regulated inducing cell proliferation and reducing invasion in the neighboring tissues. Concomitant and alternating glucose and drug infusions are explored under various circumstances to predict best clinical outcomes with least administration costs.
Contributors
Submitter of the first revision: Szeyi Ng
Submitter of this revision: Szeyi Ng
Modellers: Szeyi Ng

Metadata information

is (2 statements)
BioModels Database MODEL1910020001
BioModels Database BIOMD0000000829

isDescribedBy (1 statement)
PubMed 31009513

hasProperty (5 statements)
Experimental Factor Ontology cancer
Mathematical Modelling Ontology Ordinary differential equation model
NCIt Glioblastoma
NCIt Signaling Pathway
Gene Ontology signaling


Curation status
Curated


Tags

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files

Jung2019 - egulating glioblastoma signaling pathways and anti-invasion therapy cell cycle dynamics model.xml SBML L2V4 file for the model 134.59 KB Preview | Download

Additional files

Fig 7 without mass.png PNG plot of the model simulation for Fig 7 51.54 KB Preview | Download
Jung2019 - egulating glioblastoma signaling pathways and anti-invasion therapy cell cycle dynamics model.cps COPASI 4.24 (Build 197) file for the model 171.91 KB Preview | Download
mass.png PNG plot of the model simulation for Fig 7 (mass) 34.92 KB Preview | Download

  • Model originally submitted by : Szeyi Ng
  • Submitted: Oct 2, 2019 11:46:54 AM
  • Last Modified: Oct 2, 2019 11:46:54 AM
Revisions
  • Version: 3 public model Download this version
    • Submitted on: Oct 2, 2019 11:46:54 AM
    • Submitted by: Szeyi Ng
    • With comment: Automatically added model identifier BIOMD0000000829
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
AMPK A

5'-AMP-activated protein kinase catalytic subunit alpha-2 ; 5'-AMP-Activated Protein Kinase
2.07567380053396E-21 mmol
Cdh1

Fizzy-related protein homolog
1.0 mmol
CycB

G2/mitotic-specific cyclin-B3
0.1 mmol
mass

Mass
0.45 mmol
p55cdc T

Cell division cycle protein 20 homolog
1.0 mmol
miR 451 M

cAMP-regulated phosphoprotein 19 ; MIR451A Pre-miRNA
3.05539183438598E-21 mmol
deltaD 1.0 mmol
p55cdc A

Cell division cycle protein 20 homolog
0.85 mmol
Glucose G

glucose
6.64215616170866E-22 mmol
Reactions
Reactions Rate Parameters
=> AMPK_A; miR_451_M compartment*l_3*l_4^2/(epsilon_1*(l_4^2+beta*miR_451_M^2)) l_3 = 4.0; beta = 1.0; l_4 = 1.0; epsilon_1 = 0.02
=> Cdh1 compartment*k_3*(1-Cdh1)/((J_3+1)-Cdh1) J_3 = 0.04; k_3 = 3.0
=> CycB compartment*k_1 k_1 = 0.12
=> mass compartment*myu_0*mass*(1-mass/m) myu_0 = 0.033; m = 10.0
=> p55cdc_T compartment*k_5 k_5 = 0.015
=> miR_451_M; Glucose_G, AMPK_A compartment*(Glucose_G+l_1*l_2^2/(l_2^2+alpha*AMPK_A^2)) l_2 = 1.0; l_1 = 4.0; alpha = 1.6
deltaD = exp(-Drug_D) [] []
CycB => compartment*k_2*CycB k_2 = 0.12
p55cdc_A => compartment*k_8*Mad*p55cdc_A/(J_8+p55cdc_A) k_8 = 1.5; J_8 = 0.001; Mad = 1.0
=> Glucose_G compartment*u_1 u_1 = 0.0
Curator's comment:
(added: 02 Oct 2019, 11:46:11, updated: 02 Oct 2019, 11:46:11)
I generated the figure using COPASI 4.24(Build 197) and the attached file. The model was in a chaotic status before 70, but matches with the publication after 70h. Possible reasons might be lack on initial condition and the value of mass and mass_s are not based on the paper.