Cell fate decision network in the AGS gastric cancer cell line (Flobak et al 2015)
Taxon: Mammal
Process: Cancer
Submitter: D. Thieffry / C. Chaouiya
Supporting paper: Flobak, Åsmund and Baudot, Anaïs and Remy, Elisabeth and Thommesen, Liv and Thieffry, Denis and Kuiper, Martin and Lægreid, Astrid (2015). Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling. PLOS Computational Biology. 10.1371/journal.pcbi.1004426
Model file(s) | Description(s) |
---|---|
Flobak_FullModel_S2_Dataset.zginml | Full GINsim model |
Flobak_ReducedModel_S3_Dataset.zginml | Reduced GINsim model |
Summary:
This model accounts for cell fate decision network in the AGS gastric cancer
cell line. A set of logical equations has been defined, wich recapitulates AGS
data observed in cells in their baseline proliferative state. Using the
modeling software GINsim, model reduction and simulation compression
techniques were applied to cope with the vast state space of large logical
models and enable simulations of pairwise applications of specific signaling
inhibitory chemical substances. These simulations predicted synergistic growth
inhibitory action of five combinations from a total of 21 possible pairs. All
predicted non synergic pairs and four of the predicted synergic ones were
confirmed in AGS cell growth real-time assays, including known synergic
effects of MEK-AKT or MEK-PI3K inhibitions, along with novel synergistic
effects of combined TAK1-AKT or TAK1-PI3K inhibitions.