Combined Experimental and Computational Modeling Studies at the Example of ErbB Family
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Transcript of Combined Experimental and Computational Modeling Studies at the Example of ErbB Family
Combined Experimental and Computational Modeling Studies at the
Example of ErbB Family
Birgit Schoeberl
How do perturbations affect the network?
A431
A431 and other tumorcell lines
– Model focused on understanding the quantitative contributions from homo- and hetero-dimers of ErbB1,2,3, and 4.
– Mechanistic model based on biochemical reactions and relevant data, described by ordinary differential equations (ODE).
Facts about the Model
• Compartment model (plasma membrane, endosomes/cytosol)
• Based on elementary biochemical reactions -> automatic model generation
• ODEs with ~501 states and up to 130 kinetic parameters describing the detailed biochemical reaction network
Models need quantitative Biology
• Volume of the cells ?• Receptor Numbers ? • Protein Concentration ?• •
?
Need for new methods:
• quantitative Westernblots• high throughput assays (protein assays)
?
Accurate high throughput analysis of signaling
Adapted from Yarden and Sliwkowski 2001
Different Coexpression Patterns found in Non-Small Lung Cancer (NSCL)
High ErbB1 High ErbB2
Low ErbB1 Low ErbB2
Low ErbB1 High ErbB2
High ErbB1 Low ErbB2
22%
18%
11%
49%
Franklin et. Al., Seminars in Oncology, 2002
EGF Affinities
Monomer: KD
ErbB1 0.1-1nM
Dimer:
ErbB1:ErbB2 1-100nMErbB2:ErbB3 20nMErbB2:ErbB4 1-100nM
General Notion
• ErbB2 potentiates and prolongs the output signal (ERK, AKT). (Graus-Prota:1997)
• ErbB1 expression is of no prognostic significance. (Franklin, Seminars in Oncology, 2002)
• It maybe important in clinical trials to quantitatively assess relative levels of both receptors to predict optimal responses to drugs and biologic targeting RTK pathways. (Franklin, Seminars in Oncology)
Training the Model
A431: Model Validation: Simulation of ErbB1 - Inhibition
A431: Model Validation: ErbB1 – Inhibition Simulation + Experimental Validation
A431: Model Validation: ErbB1 – Inhibition Simulation + Experimental Validation
A431: Model Validation: Simulation of ErbB2 - Inhibition
A431: Model Validation: ErbB2 – Inhibition Simulation + Experimental Validation
KI1 high affinity
Effect of ErbB1, ErbB2 and ErbB4 Inhibition on A431 cells
KI1 low affinity
ErbB1 inhibition most effective !
100% ERK:P:P
0% ERK:P:P
predictions verified in other tumor cells with different receptor setup
Model predicts ERK:P:P for different cell lines
predictions verified in other tumor cells with different receptor setup
Model predicts ERK:P:P for different cell lines
Influence of ErbB2 receptor number for different cell lines
1e6 ErbB17e4 ErbB1
A431BT47450ng/ml EGF
7e4
Maximal ERK activation as function of ErbB1 and ErbB3 expression + ErbB2 Inhibitor
ErbB2:3e5
ERK:P:P @ 5min
Model trained for HRG in A431
….and in comparison to EGF stimulation in A431
EGF: 50ng/ml HRG: 50ng/ml
ErbB1 drivenErbB2 + ErbB 3 drivenErbB2 + ErbB 3 driven
Which receptors drive ERK activation ?
100% ERK:P:P
0% ERK:P:P
General Notion
• ErbB2 potentiates and prolongs the output signal (ERK, AKT). (Graus-Prota:1997)
• ErbB1 expression is of no prognostic significance. (Franklin, Seminars in Oncology, 2002)
• It maybe important in clinical trials to quantitatively assess relative levels of both receptors to predict optimal responses to drugs and biologic targeting RTK pathways. (Franklin, Seminars in Oncology)
Summary & Conclusions
• Different protein/receptor expression levels have large impact on signal response
• Tumor cells use alternative pathways to ensure their proliferative capacity: ErbB1 replaces / supports ErbB3
• Tumor cells amplify the signal by using ErbB2 if the number of ErbB1 or ErbB3 receptors is small.
• ErbB2 is very important for HRG induced signaling.
• Inhibitor selection is dependent on receptor expression and the ligand(s) (concentration / type)-> Characterization of tumors is important
Acknowledgements
• Ulrik B. Nielsen, Merrimack Pharmaceuticals• Jack Beusmans, David DeGraaf, AstraZeneca• Douglas Lauffenburger • Peter Sorger