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Table 1 Attractor states of short-term perturbation simulations

From: Boolean ErbB network reconstructions and perturbation simulations reveal individual drug response in different breast cancer cell lines

 

BT474

  

HCC1954

  

SKBR3

  

Simulation

AKT

ERK1/2

p70S6K

AKT

ERK1/2

p70S6K

AKT

ERK1/2

p70S6K

 

A

E

A

E

A

E

A

E

A

E

A

E

A

E

A

E

A

E

X

1

1

1

1

1

1

1

1

1

E

0

1

1

0

1

0

1

0

1

0

1

0

0

1

P

1

1

1

0

1

0

1

0

1

0

1

0

1

0

1

T

1

1

1

1

1

1

1

1

1

E, P

1

1

0

1

0

1

0

0

1

0

0

0

0

1

E, T

0

1

1

0

1

1

0

1

1

0

1

0

0

1

P, T

1

1

1

0

1

0

0

1

0

0

0

1

E, P, T

1

1

0

1

0

1

0

0

1

0

0

0

  1. The therapeutics erlotinib, trastuzumab and pertuzumab, abbreviated by first letters, that were permanently active besides EGF and HRG in the simulated perturbation conditions are stored in the column Simulation. No simulated drug treatment is denoted by ‘X’. The A columns hold the attractor states of the proteins AKT, ERK1/2 and p70S6K, associated with the perturbations. The E columns contain the protein activity status, statistically deduced from the experimental data. In case of a significant (p-value < 0.05) combined influence of both, drug treatment and time, on the protein signal intensity, a Wilcoxon rank sum test was conducted for the measurements at time point 60 minutes. The drug treatments leading to significantly (p-value < 0.05) smaller intensity values compared to the control measurement ‘X’ were considered as efficient inhibitors, resulting in a table entry of zero. Consistency between simulations and experimental observations is printed in bold.