Literature DB >> 25862520

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

Poonam Desai1, Jun Yang2, Bing Tian3, Hong Sun2, Mridul Kalita4, Hyunsu Ju5, Adriana Paulucci-Holthauzen6, Yingxin Zhao7, Allan R Brasier7, Rovshan G Sadygov8.   

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 mixed effects 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.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cellular signaling; Correlative networks; EMT; Mixed-effects modeling

Mesh:

Substances:

Year:  2015        PMID: 25862520      PMCID: PMC4437893          DOI: 10.1016/j.cellsig.2015.03.024

Source DB:  PubMed          Journal:  Cell Signal        ISSN: 0898-6568            Impact factor:   4.315


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