Mathematical models for the EP2 and EP4 signaling pathways and their crosstalk

Alessandra Cambi, Diane S. Lidke, Mariya Ptashnyk, Willemijn Smit, Stefanie Sonner

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Abstract

G protein-coupled receptors EP2 and EP4 are both activated by the lipid messenger Prostaglandin E2 (PGE2) and induce the intracellular production of cyclic AMP (cAMP), ultimately affecting gene expression. Changes in cellular responses to PGE2 can have important consequences on immunity and disease, yet a detailed understanding of the EP2-EP4 signaling network is lacking. EP2 and EP4 are often co-expressed in cells but their specific contribution to cAMP production is poorly understood. Experimental data have shown that cAMP levels differ depending on whether PGE2 triggers EP2 or EP4, or both. To better understand the underlying mechanisms and predict cellular responses to PGE2, we developed mathematical models for EP2 and EP4 cAMP signaling, including receptor crosstalk. The mathematical models qualitatively reproduce the experimentally observed cAMP levels and provide mechanistic insight into both the differences and commonalities in EP2/EP4 signaling. We found that ligand binding dynamics play a crucial role for both single-receptor signaling and inter-receptor crosstalk. Inhibition of PGE2 signaling via receptor antagonists is gaining increasing attention in tumor immunology. These mathematical models could therefore contribute to the design of more effective anti-tumor therapies targeting EP2 and EP4.
Original languageEnglish
Article number112287
JournalJournal of Theoretical Biology
Volume617
Early online date15 Oct 2025
DOIs
Publication statusE-pub ahead of print - 15 Oct 2025

Keywords

  • Cellular signaling pathways
  • G protein-coupled receptors
  • Ordinary differential equations
  • Receptor crosstalk

ASJC Scopus subject areas

  • Statistics and Probability
  • General Medicine
  • Modelling and Simulation
  • General Immunology and Microbiology
  • General Biochemistry,Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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