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Modeling of Acute Resistance to the HER2 Inhibitor, Lapatinib, in Breast Cancer Cells Marc Fink & Yan Liu & Shangying Wang Student Project Proposal Computational Cell Biology 2012 Outline Brief review of the project goal Boolean network model and results Modeling with ODEs in VCell and COPASI Analysis of cell survival rate Summary and outlook Goals - Modeling the signaling pathway of HER2 inhibitor, Lapatinib, in Breast Cancer Cells - Analyze the influence factors of cell apoptosis - Explanation of cell survival rate after treatment 01/13 Mechanistic (process) diagrams Death ?????? Survival Lapatinib HER2 PI3K p PDK1 AKT (PKB) p FoxO p p 14-3-3 FoxO FoxO FoxO FoxO FoxO ER Protein Translation Translocation Transcription Apoptotic genes Survival genes Translocation Apoptosis 02/13 Flow chart and strategies HER2 AKT FoxO Lapatinib IGF1R RAF MEK ERK FASL RSK Lack of experimental parameters => Boolean network Better understanding of dynamics => ODEs Analysis of survival rate => Stochastic simulation BIM BAD apoptosis 03/13 Boolean network model HER2 Lapatinib IGF1R FoxO Apoptosis AKT Time steps BIM apoptosis => Average value of apoptosis is around 0.5 with simplification. 04/13 Boolean network model HER2 Lapatinib IGF1R FoxO Apoptosis AKT FASL Time steps BIM apoptosis => Average apoptosis is around 0.6 with additional information. 04/13 Boolean network model AKT FoxO Lapatinib IGF1R RAF MEK ERK Apoptosis HER2 FASL RSK BIM BAD apoptosis Time steps => Results depend on the complexity, adding weights not possible. 04/13 Modeling with ODEs => 22 species and 32 reactions, reasonable rates???!!! 05/13 Model reduction and modification Due to the importance of FOXO => Neglect the downstream and add the self regulation HER2 AKT FoxO Apoptosis Lapatinib Self regulation of FOXO Φ FoxO_gene FoxO_mRNA (x) Φ FoxO (y) => Bistability of the positive feedback loop FoxO* (z) 06/13 Modified model => 14 species and 16 reactions 07/13 Sensitivity analysis Binding of Laptinib to HER2 Dimerization of HER2 FOXO => Laptinib is important for cancer cell apoptosis 08/13 Modeling with ODEs IV Deterministic simulations with parameter scan (Laptinib) => Laptinib is able to stimulate FOXO, crucial to apoptosis 09/13 Analysis of cell survival rate Random initial concentrations (with COPASI) => Laptinib is able to stimulate cancer cell apoptosis 10/13 Analysis of cell survival rate Stochastic simulation (with VCell and C) => Laptinib is able to stimulate cancer cell apoptosis 11/13 Summary and outlook Apoptosis pathway of breast cancer cell is modeled and analyzed with simplifications Survival rate of cancer cell is analyzed Laptinib induced cancer cell apoptosis is with certain probability Outlook Improve the pathway model with more details by getting more rates from experiments Validation of the model and survival rate 12/13 Experience with the softwares COPASI vs VCell Writing reactions + +++ Checking parameters + +++ Deterministic simulation +++ + Stochastic simulation ++ + Parameter scan +++ ++ Sensitivity analysis +++ - - +++ Visualization 13/13 Thank you for your attention!