Analysis of inhibition of HER2
signaling to apoptotic
transcription factors
Marc Fink & Yan Liu & Shangying Wang
Student Project Proposal
Computational Cell Biology 2012
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
Outline
 Brief review
 Boolean network model and results
 Modeling with ODEs in VCell and COPASI
 Analysis of simulation results
 Summary and outlook
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
01/13
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
02/13
Boolean network model
HER2
Lapatinib
IGF1R
FoxO
Apoptosis
AKT
Time steps
BIM
apoptosis
=> Average value of
apoptosis is around 0.5 with
simplification.
03/13
Boolean network model
HER2
Lapatinib
IGF1R
FoxO
Apoptosis
AKT
FASL
Time steps
BIM
apoptosis
=> Average apoptosis is
around 0.6 with additional
information.
03/13
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.
03/13
Modeling with ODEs
=> 22 species and 32 reactions, reasonable rates???!!!
04/13
Model reduction and modification
Due to the importance of FOXO
=> Neglect the downstream and add the self regulation
05/13
Model reduction and modification
HER2
AKT
FoxO
Lapatinib
IGF1R
RAF
MEK
ERK
FASL
RSK
BIM
BAD
apoptosis
05/13
Model reduction and modification
Due to the importance of FOXO
=> Neglect the downstream and add the self regulation
HER2
AKT
Lapatinib
HER2_dimer
HER2_dimer*
PI3K
H_PI3K
FoxO
PIP3
PIP2
AKT
Apoptosis
Φ
FoxO_gene
FoxO_mRNA (x)
AKT*
Φ
FoxO (y)
FoxO* (z)
Model reduction and modification
Due to the importance of FOXO
=> Neglect the downstream and add the self regulation
HER2
AKT
Lapatinib
[Birtwistle et al., 2007]
HER2_dimer
HER2_dimer*
PI3K
H_PI3K
FoxO
PIP3
PIP2
AKT
Apoptosis
Φ
FoxO_gene
FoxO_mRNA (x)
AKT*
Φ
FoxO (y)
FoxO* (z)
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 in COPASI
Binding of
Laptinib to
HER2
Dimerization of HER2
FOXO
=> Laptinib is important for cancer cell apoptosis
08/13
Analysis of simulation results
 Deterministic simulations with parameter scan (Laptinib)
FOXO concentration
With increasing
initial Laptinib
concentration
0 -> 400 nM
09/13
Analysis of simulation results
 Deterministic simulations with parameter scan (Laptinib)
Phosphorylation
=> Laptinib is able to stimulate FOXO, crucial to apoptosis 09/13
Analysis of simulation results
 Random initial concentrations and constant Laptinib (200nM)
FOXO concentration
=> Initial concentrations influence the effect of Laptinib. 10/13
Analysis of simulation results
 Stochastic simulation using Gillespie algorithm (in VCell & C)
High Laptinib
Low Laptinib
11/13
Summary and outlook
 Inhibition of HER2 signaling to apoptotic transcription factors
is studied.
 Models with different complexities are analyzed.
 Laptinib induced inhibition of HER2 is simulated.
Outlook
 Improve the stochastic study
 Improve the pathway model with more details by getting
more rates from experiments
 Measurement of concentrations within small time scale before
and after treatment will help to understand the whole
signaling process and validate the model.
12/13
Experience with the softwares
COPASI
vs
VCell
 Writing reactions
+
+++
 Checking parameters
+
+++
 Deterministic simulation
+++
+
 Stochastic simulation
++
+
 Parameter scan
+++
++
 Sensitivity analysis
+++
-
-
+++
 Visualization
13/13
Happy Birthday
to Nina!