Giani2019 - Computational modeling to predict MAP3K8 effects as mediator of resistance to vemurafenib in thyroid cancer stem cells

  public model
Model Identifier
BIOMD0000000883
Short description 
Computational modeling to predict MAP3K8 effects as mediator of resistance to vemurafenib in thyroid cancer stem cells
Format
SBML (L2V4)
Related Publication
  • Computational modeling reveals MAP3K8 as mediator of resistance to vemurafenib in thyroid cancer stem cells
  • Gianì F, Russo G, Pennisi M, Sciacca L, Frasca F, Pappalardo F
  • Bioinformatics , 10/ 2018 , pages: doi:10.1093/bioinformatics/bty969 , PubMed ID: 30481266
  • 1 Department of Clinical and Molecular BioMedicine, Endocrinology Unit, Garibaldi-Nesima Medical Center, University of Catania, Catania, Italy. 2 The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors. 3 Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy. 4 Department of Mathematics and Computer Science, University of Catania, Catania, Italy. 5 Department of Drug Sciences, University of Catania, Catania, Italy.
  • MOTIVATION: Val600Glu (V600E) mutation is the most common BRAF mutation detected in thyroid cancer. Hence, recent research efforts have been performed trying to explore several inhibitors of the V600E mutation-containing BRAF kinase as potential therapeutic options in thyroid cancer refractory to standard interventions. Among them, vemurafenib is a selective BRAF inhibitor approved by FDA for clinical practice. Unfortunately, vemurafenib often displays limited efficacy in poorly differentiated and anaplastic thyroid carcinomas probably because of intrinsic and/or acquired resistance mechanisms. In this view, cancer stem cells may represent a possible mechanism of resistance to vemurafenib, due to their self-renewal and chemo resistance properties. RESULTS: We present a computational framework to suggest new potential targets to overcome drug resistance. It has been validated with an in vitro model based upon a spheroid-forming method able to isolate thyroid cancer stem cells that may mimic resistance to vemurafenib. Indeed, vemurafenib did not inhibit cell proliferation of BRAF V600E thyroid cancer stem cells, but rather stimulated cell proliferation along with a paradoxical overactivation of ERK and AKT pathways. The computational model identified a fundamental role of mitogen-activated protein kinase 8 (MAP3K8), a serine/threonine kinase expressed in thyroid cancer stem cells, in mediating this drug resistance. To confirm model prediction, we set a suitable in vitro experiment revealing that the treatment with MAP3K8 inhibitor restored the effect of vemurafenib in terms of both DNA fragmentation and PARP cleavage (apoptosis) in thyroid cancer stem cells. Moreover, MAP3K8 expression levels may be a useful marker to predict the response to vemurafenib.
Contributors
Submitter of the first revision: Francesco Pappalardo
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Rahuman Sheriff, Francesco Pappalardo, Krishna Kumar Tiwari

Metadata information

hasTaxon (1 statement)
Taxonomy Homo sapiens

isDerivedFrom (2 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Taxonomy Homo sapiens

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

Curation status
Curated
Tags

Connected external resources

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Name Description Size Actions

Model files
Giani2019.xml SBML L2V4 model file for Giani2019 341.20 KB Preview | Download

Additional files
Giani2019.cps COPASI 4.27(Build217) file for Giani2019 373.30 KB Preview | Download
Giani2019.sedml SEDML file for Giani2019 4.01 KB Preview | Download
MAP3K8_Thyroid_Spheres_V3.4.cps Originally submitted Copasi file for model simulation 326.04 KB Preview | Download
MAP3K8_Thyroid_Spheres_V3.4.cps.xml Original submitted model file SBML L2V1 326.04 KB Preview | Download

  • Model originally submitted by : Francesco Pappalardo
  • Submitted: May 8, 2019 4:30:00 PM
  • Last Modified: Dec 6, 2019 1:11:50 PM
Revisions
  • Version: 9 public model Download this version
    • Submitted on: Dec 6, 2019 1:11:50 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Automatically added model identifier BIOMD0000000883
  • Version: 7 public model Download this version
    • Submitted on: May 8, 2019 4:30:00 PM
    • Submitted by: Rahuman Sheriff
    • With comment: Edited model metadata online.

(*) 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
species 15

Phosphatidylinositol 3-kinase regulatory subunit alpha ; inactive 		10.0 nmol
species 17

RAC-alpha serine/threonine-protein kinase 		10.0 nmol
species 14

Phosphatidylinositol 3-kinase regulatory subunit alpha ; Active 		0.0 nmol
species 16

RAC-alpha serine/threonine-protein kinase ; phosphorylated 		0.0 nmol
species 25

Pro-epidermal growth factor 		10000.0 nmol
mTORC2Active

Active ; Rapamycin-insensitive companion of mTOR ; Serine/threonine-protein kinase mTOR ; Active 		0.0 nmol
mTORC1Inactive

inactive ; Regulatory-associated protein of mTOR ; Serine/threonine-protein kinase mTOR ; inactive 		10.0 nmol
TNF

Q5STB3 		10000.0 nmol
freeTNFR2

P20333 		10.0 nmol
Reactions
Reactions Rate Parameters
species_14 => species_15 compartment_0*k1*species_14 k1=0.1
species_17 => species_16; species_14 compartment_0*Kcat*species_14*species_17/(km+species_17) Kcat=0.1; km=0.1
species_15 => species_14; species_0 compartment_0*Kcat*species_0*species_15/(km+species_15) Kcat=0.1; km=0.1
species_17 => species_16; PIP3Active compartment_0*Kcat*PIP3Active*species_17/(km+species_17) Kcat=0.1; km=0.1
species_25 + species_1 => species_0 compartment_0*k1*species_25*species_1 k1=0.1
mTORC2Inactive => mTORC2Active; species_14 compartment_0*Kcat*species_14*mTORC2Inactive/(km+mTORC2Inactive) Kcat=0.1; km=0.1
mTORC1Inactive => mTORC1Active; species_16 compartment_0*Kcat*species_16*mTORC1Inactive/(km+mTORC1Inactive) Kcat=0.1; km=0.1
TNF + freeTNFR1 => pTNFR1 compartment_0*k1*TNF*freeTNFR1 k1=0.1
TNF + freeTNFR2 => pTNFR2 compartment_0*k1*TNF*freeTNFR2 k1=0.1
pTNFR2 => TNF + freeTNFR2 compartment_0*k1*pTNFR2 k1=0.1
Curator's comment:
(added: 06 Dec 2019, 13:10:01, updated: 06 Dec 2019, 13:11:08)
Model is created using Copasi 4.27 (Build217). Figure 2C is reproduced by doing parameter Scan for MAP3K8 inhibitors presence and absence.