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Metadata

Name
FOXF1 inhibits pulmonary fibrosis by preventing CDH2-CDH11 cadherin switch in myofibroblasts
Repository
Gene Expression Omnibus
Identifier
geo.series:GSE110408
Description
Idiopathic pulmonary fibrosis (IPF) is characterized by aberrant accumulation of collagen-secreting myofibroblasts. Development of effective therapies is limited due to incomplete understanding of molecular mechanisms regulating myofibroblast expansion. FOXF1 transcription factor is expressed in resident lung fibroblasts, but its role in lung fibrosis remains unknown due to the lack of genetic mouse models. Through comprehensive analysis of human IPF genomics data, lung biopsies and transgenic mice with fibroblast-specific inactivation of FOXF1, the present study shows that FOXF1 inhibits pulmonary fibrosis. FOXF1 deletion increases myofibroblast invasion, collagen secretion, and promotes a switch from of N-cadherin (CDH2) to Cadherin-11 (CDH11), which is critical step in acquisition of pro-fibrotic phenotype. FOXF1 directly binds to Cdh2 and Cdh11 promoters and differentially regulates transcription of these genes. Re-expression of CDH2 or inhibition of CDH11 in FOXF1-deficient cells reduces myofibroblast invasion in vitro. FOXF1 inhibits pulmonary fibrosis by regulating a switch from CDH2 to CDH11 in lung myofibroblasts.
Data or Study Types
Expression profiling by high throughput sequencing
Source Organization
National Center for Biotechnology Information
Access Conditions
available
Year
2018
Access Hyperlink
http://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GSE110408

Distributions

  • Encoding Format: Bioproject ; URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA433652
  • Encoding Format: TXT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE110408/matrix/
  • Encoding Format: MINiML ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE110408/miniml/
  • Encoding Format: SOFT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE110408/soft/
This project was funded in part by grant U24AI117966 from the NIH National Institute of Allergy and Infectious Diseases as part of the Big Data to Knowledge program. We thank all members of the bioCADDIE community for their valuable input on the overall project.