Systems Biology (Methods in Molecular Biology)

(Tina Sui) #1
Model simulation:Model is simulated to analyze the input-output
response for normal execution of the system. The model recapitu-
lates a “healthy system” for normal pathway function and “cancer
system” when the pathway is mutated. First, we initialized the input
nodes by 1 (i.e., activated). The model simulations show that both
the apoptotic and proliferative genes are 1 (i.e., expressed), which is
a necessary condition for healthy cell systems. Second, we mutate
the pathway by deactivating the PTEN which results in the consti-
tutive activation of the AKT/PI3K pathway. The activated AKT/-
PI3K pathway inhibits the pro-apoptotic genes regulated by TP53
and E2F1 [70] and leads to an uncontrolled proliferation [71],
which recapitulates the cancer system. In Table3, the active and
in-active states of the nodes are represented by “1” and “0” respec-
tively. In the table “healthy system” represents normal pathway
execution where both the proliferative and apoptotic genes are
active when there is no mutation in PTEN and other input nodes
are active. The last “Perturbed system” represents the mutation
scenario in PTEN (expression state indicated by “0”) which results
in the activation of proliferative genes and inactivation of apoptotic
genes.
The choice for modeling formalism with the aim of applying on
biochemical networks which are large and have complex structure,

Table 2
CellNetAnalyzer representation of the Boolean functions


1 1 EGF_LIGAND¼1 EGFR
2 1 EGF¼1 EGFR
3 1 EGFR¼1 CYCLIN_CDKS
4 1 CYCLIN_CDKS¼1 PI3K
5 1 PIP3¼1 AKT1
6 1 E2F1þ1 DP1¼1 E2F1_DP1
7 1 CYCLIN_CDKS¼1 E2F1
8 1 E2F1_APOPTOTIC_GENES¼1 P14
9 1 AKT1¼1 TOPBP1
10 1 E2F1_PROLIFERATIVE_GENES¼1 EGF_LIGAND
11 1! P14þ1 AKT1¼1 MDM2
12 1! PTENþ1 PI3K¼1 PIP3
13 1 E2F1_DP1¼1 E2F1_proliferative_genes
14 1! MDM2¼1 PT53_reg_genes
15 1! TOPBP1þ1 E2F1_DP1þ1 DNA_damage¼1 E2F1_apoptotic_genes

Integrative Workflow for Predicting Disease Signatures 261
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