Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer

PLoS One. 2016 Mar 25;11(3):e0152104. doi: 10.1371/journal.pone.0152104. eCollection 2016.

Abstract

Background: Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathways may represent promising therapeutic targets for an otherwise devastating disease.

Result: Here we show a computational model able to simulate the main biochemical and metabolic interactions in the PI3K/AKT and MAPK pathways potentially involved in melanoma development. Overall, this computational approach may accelerate the drug discovery process and encourages the identification of novel pathway activators with consequent development of novel antioncogenic compounds to overcome tumor cell resistance to conventional therapeutic agents. The source code of the various versions of the model are available as S1 Archive.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents / chemistry
  • Apoptosis
  • Cell Cycle
  • Cell Line, Tumor
  • Computer Simulation*
  • Drug Resistance, Neoplasm
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Imidazoles / chemistry
  • MAP Kinase Signaling System*
  • Melanoma / metabolism*
  • Melanoma, Cutaneous Malignant
  • Mutation
  • Oximes / chemistry
  • Phosphatidylinositol 3-Kinases / metabolism*
  • Proto-Oncogene Proteins B-raf / metabolism
  • Skin Neoplasms / metabolism*

Substances

  • Antineoplastic Agents
  • Imidazoles
  • Oximes
  • Phosphatidylinositol 3-Kinases
  • BRAF protein, human
  • Proto-Oncogene Proteins B-raf
  • dabrafenib

Grants and funding

This work has been partially supported by the FIR 2014 University of Catania, Italy grant. There were no other funding sources supporting this work. FIR 2014 partially supported the work. The remaining effort comes from internal personnel work.