Experiment-based computational model predicts that IL-6 classic and trans-signaling exhibit similar potency in

Min Song1, Youli Wang2, Brian H Annex2

  • 1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. msong25@jhmi.edu.

PubMed

Insights

Interleukin-6 (IL-6) signaling in endothelial cells is modeled to understand inflammation and angiogenesis. The model reveals trans-signaling is dominant, offering insights for targeted therapies.

Area of Science:

  • Computational biology and systems medicine
  • Molecular and cellular biology
  • Immunology and inflammation research

Background:

  • Inflammatory cytokines, like interleukin-6 (IL-6), are implicated in diseases involving angiogenesis.
  • Targeting angiogenesis has shown limited success, possibly due to the interplay between inflammation and angiogenesis.
  • Understanding IL-6 signaling in endothelial cells is crucial but not fully elucidated.

Purpose of the Study:

  • To develop a computational model of IL-6 classic and trans-signaling pathways in endothelial cells.
  • To quantitatively characterize the dynamics of key downstream signaling molecules: phosphorylated STAT3 (pSTAT3), Akt (pAkt), and ERK (pERK).
  • To identify key modulators of IL-6 mediated inflammatory and angiogenic signals.

Main Methods:

  • Development of a detailed, experiment-based computational model for IL-6 signaling.
  • Quantitative characterization of IL-6 classic and trans-signaling effects on STAT3, PI3K/Akt, and MAPK pathways.
  • Model validation and application to predict signaling dynamics and identify influential parameters.

Main Results:

  • IL-6 classic and trans-signaling responses are dose-dependent on IL-6 and soluble IL-6 receptor (sIL-6R).
  • Trans-signaling exhibits stronger downstream responses and dominates IL-6 effects in vitro due to abundant sIL-6R.
  • Both IL-6 and sIL-6R levels regulate signaling strength, with specific species and parameters identified as key modulators.

Conclusions:

  • The computational model quantitatively predicts IL-6 classic and trans-signaling effects in endothelial cells.
  • The model provides a framework for integrating experimental data and understanding IL-6 mediated inflammation and angiogenesis.
  • This approach can guide the identification of novel therapeutic targets for modulating IL-6 signaling in endothelial cells.