Modeling of Acute Resistance to the HER2 Inhibitor, Lapatinib, in

Breast Cancer Cells

Marc Fink & Yan Liu & Shangying WangStudent Project Proposal

Computational Cell Biology 2012

OutlineBrief review of the project goalBoolean network model and resultsModeling with ODEs in VCell and COPASIAnalysis of cell survival rateSummary 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

HER2

PDK1

AKT (PKB)

14-3-3FoxOFoxO

PI3K

p

pp

p Translocation

FoxOFoxO Apoptotic genes

Transcription

Translocation

ProteinTranslation

FoxOFoxO Survival genes

DeathSurvival

??????

ER

Lapatinib

Apoptosis

02/13

Flow chart and strategies Lack of experimental

parameters => Boolean network

Better understanding of dynamics => ODEs

Analysis of survival rate => Stochastic simulation

03/13

LapatinibHER2 IGF1R

FASL

AKT

FoxO

apoptosis

RAF

MEK

ERK

RSK

BADBIM

Boolean network model

=> Average value of apoptosis is around 0.5 with simplification.

HER2

AKT

FoxO

apoptosis

BIMAp

opto

sisTime steps

04/13

Lapatinib IGF1R

Boolean network modelHER2

FASL

AKT

FoxO

apoptosis

BIM => Average apoptosis is around 0.6 with additional information.

Apop

tosis

Time steps

04/13

Lapatinib IGF1R

Boolean network modelHER2

FASL

AKT

FoxO

apoptosis

RAF

MEK

ERK

RSK

BADBIM => Results depend on

the complexity, adding weights not possible.

Apop

tosis

Time steps

04/13

Lapatinib IGF1R

Modeling with ODEs

=> 22 species and 32 reactions, reasonable rates???!!! 05/13

Model reduction and modification

LapatinibHER2

AKT

FoxO

Due to the importance of FOXO => Neglect the downstream and add the self regulation

Apoptosis

Self regulation of FOXO

FoxO_gene FoxO_mRNA (x) FoxO (y) FoxO* (z)Φ Φ

06/13=> Bistability of the positive feedback loop

Modified model

=> 14 species and 16 reactions 07/13

Sensitivity analysis

=> Laptinib is important for cancer cell apoptosis 08/13

Binding of Laptinib to HER2

FOXODimerization of HER2

Modeling with ODEs IVDeterministic simulations with parameter scan (Laptinib)

=> Laptinib is able to stimulate FOXO, crucial to apoptosis 09/13

Analysis of cell survival rateRandom initial concentrations (with COPASI)

=> Laptinib is able to stimulate cancer cell apoptosis 10/13

Analysis of cell survival rateStochastic simulation (with VCell and C)

=> Laptinib is able to stimulate cancer cell apoptosis 11/13

Summary and outlookApoptosis pathway of breast cancer cell is modeled

and analyzed with simplificationsSurvival rate of cancer cell is analyzed Laptinib induced cancer cell apoptosis is with

certain probabilityOutlookImprove the pathway model with more details by

getting more rates from experimentsValidation 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!