Abstract:
HuR, an RNA binding factor, is a widely expressed regulator of many cellular mRNAs
at both transcriptional and post-transcriptional level. The over-expression of HuR is
known to favor the progression of different types of cancers including RCC. Discrete
modeling, based on the kinetic logic formalism has gained acknowledgment in the
study of the interaction of genes and their Biological Regulatory Networks (BRNs).
The approach helps to analyze a BRN precisely and make predictions about behaviors
associated with normal or diseased conditions. In this study, we model the HuR
associated BRN with the discrete modeling approach of Ren´e Thomas. The logical
parameters for the model are inferred with model-checking approach implemented in
the tool SMBioNet. The qualitative model predicts cyclic and stable state behaviors.
Cycles represent the homeostasis of all the entities in the BRN. The stable states show
the over-expression of all the proteins (AKT, HuR, NF-kB and GRB10) which can
potentially lead towards Renal Cell carcinoma (RCC) while the loss of expression level
will mediate the system towards apoptosis which is predicted in the second stable state
where all the entities are down regulated. Additionally, the discrete model is converted
into a hybrid model by incorporating clocks and delays in order to predict conditions
in the form of constraints pertaining to homeostatic trajectories. The most significant
delay constraint which is common in every cycle, suggests that while designing drugs
for RCC the degradation rate of GRB10 must be kept higher than the activation rate of
NF-κB. Suppression of GRB10 can reduce the constitutive activation of this pathway
in RCC. Thus our findings suggest that GRB10 may be an attractive remedial target
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in the HuR associated pathway for the therapeutic interventions against RCC.
