Dynamic modeling of HuR pathway in renal proximal tubule cells: potential induction in Renal Cell Carcinoma

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 iv in the HuR associated pathway for the therapeutic interventions against RCC.