Abstract:
The efficiency of surgery is limited in hepatocellular carcinoma (HCC) due to the occurrence of metastasis. Transforming Growth Factor Beta (TGF-β) and Matrix Metalloproteinases (MMPs) have been associated with HCC migration and invasion which in collaboration with the PI3K/AKT signaling leads to metastasis. Both TGF-𝛽 and MMPs’ are known to activate each other and consequently, the reciprocal positive interplay between them results in disease by induction of Epithelial-Mesenchymal Transition (EMT). Recent studies have demonstrated that MMP’s roles in extracellular signaling are involved in both homeostasis and disease. In cancer cells, TGF-𝛽 regulates the expression of several MMPs, while MMPs may activate secreted latent TGF-β, causing an enhancement of tumor progression. Different opinions from previous studies regarding the interplay between the two entities have to lead our attention towards the qualitative properties of TGF-𝛽 signaling pathways using computational methods. Systems-level approaches employ contemporary computational theories and high-throughput experimental data to model and simulate complex biological procedures such as in cancer. In this study, a qualitative model for an HCC-associated Biological Regulatory Network (BRN) is constructed to study the TGF-𝛽 mediated pathogenesis in HCC. The qualitative model predicts the qualitative cycles along with paths leading to pathogenesis and recovery. The significant qualitative (discrete) cycle is identified by analyzing betweenness centralities of the qualitative (discrete) states. We further analyzed the model through a continuous Petri nets (PN) based approach in order to study the continuous network dynamics. This model will help to provide better insights into the dynamics of HCC tumorigenesis and will aid future treatment developments.
