Mixed-effects model of epithelial-mesenchymal transition reveals rewiring of signaling networks

Poonam Desai, Jun Yang, Bing Tian, Hong Sun, Mridul Kalita, Hyunsu Ju, Adriana Paulucci-Holthauzen, Yingxin Zhao, Allan R. Brasier, Rovshan G. Sadygov

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

The type II epithelial-mesenchymal transition (EMT) produces airway fibrosis and remodeling, contributing to the severity of asthma and chronic obstructive pulmonary disease. While numerous studies have been done on the mechanisms of the transition itself, few studies have investigated the system effects of EMT on signaling networks. Here, we use mixed effects modeling to develop a computational model of phospho-protein signaling data that compares human small airway epithelial cells (hSAECs) with their EMT-transformed counterparts across a series of perturbations with 8 ligands and 5 inhibitors, revealing previously uncharacterized changes in signaling in the EMT state. Strong couplings between menadione, TNFα and TGFβ and their known phospho-substrates were revealed after mixedeffects modeling. Interestingly, the overall phospho-protein response was attenuated in EMT, with loss of Mena and TNFα coupling to heat shock protein (HSP)-27. These differences persisted after correction for EMT-induced changes in phospho-protein substrate abundance. Construction of network topology maps showed significant changes between the two cellular states, including a linkage between glycogen synthase kinase (GSK)-3α and small body size/mothers against decapentaplegic (SMAD)2. The model also predicted a loss of p38 mitogen activated protein kinase (p38MAPK)-independent HSP27 signaling, which we experimentally validated. We further characterized the relationship between HSP27 and signal transducers and activators of transcription (STAT)3 signaling, and determined that loss of HSP27 following EMT is only partially responsible for the downregulation of STAT3. These rewired connections represent therapeutic targets that could potentially reverse EMT and restore a normal phenotype to the respiratory mucosa.

Original languageEnglish (US)
Pages (from-to)1413-1425
Number of pages13
JournalCellular Signalling
Volume27
Issue number7
DOIs
StatePublished - Jul 1 2015

Keywords

  • Cellular signaling
  • Correlative networks
  • EMT
  • Mixed-effects modeling

ASJC Scopus subject areas

  • Cell Biology

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