Using Continuous Petri Nets to predict the impact of microRNA analysis in PI3K/Akt and MAPK Signaling Pathways

Personalized target therapies represent one of the possible treatment strategies to fight the ongoing battle against cancer. New treatment interventions are still needed for an effective and successful cancer therapy. In this scenario, we simulated and analyzed the dynamics of BRAF V600E melanoma patients treated with BRAF inhibitors in order to find potentially interesting targets that may make standard treatments more effective in particularly aggressive tumors that may not respond to selective inhibitor drugs. To this aim, we developed a continuous Petri Net model that simulates fundamental signalling cascades involved in melanoma development, such as MAPK and PI3K/AKT, in order to deeply analyze these complex kinase cascades and predict new crucial nodes involved in melanomagenesis. The model pointed out that some microRNAs, like hsa-mir-132, downregulates expression levels of p120RasGAP: under high concentrations of p120RasGAP, MAPK pathway activation is significantly decreased and consequently also PI3K/PDK1/AKT activation. Furthermore, our analysis carried out through the Genomic Data Commons (GDC) Data Portal shows the evidence that hsa-mir-132 is significantly associated with clinical outcome in melanoma cancer genomic data sets of BRAF-mutated patients. In conclusion, targeting miRNAs through antisense oligonucleotides technology may suggest the way to enhance the action of BRAF-inhibitors.