Title |
Profibrotic role of WNT10A via TGF-β signaling in idiopathic pulmonary fibrosis
|
---|---|
Published in |
Respiratory Research, April 2016
|
DOI | 10.1186/s12931-016-0357-0 |
Pubmed ID | |
Authors |
Keishi Oda, Kazuhiro Yatera, Hiroto Izumi, Hiroshi Ishimoto, Sohsuke Yamada, Hiroyuki Nakao, Tetsuya Hanaka, Takaaki Ogoshi, Shingo Noguchi, Hiroshi Mukae |
Abstract |
WNT/β-catenin signaling plays an important role in the pathogenesis of idiopathic pulmonary fibrosis (IPF); however, the role of WNT10A via transforming growth factor (TGF)-β signaling remains unclear. We evaluated the expression of WNT10A and TGF-β in bleomycin (BLM)-treated mice and the interactions between TGF-β or BLM and WNT10A in vitro. Additionally, we investigated IPF patients who underwent video-assisted thoracoscopic surgery to determine whether the WNT10A expression is related to the survival. Increased WNT10A and TGF-β expressions were noted in the BLM-treated mice. Real-time PCR and luciferase reporter assays demonstrated the levels of WNT10A and collagen in the fibroblasts cells to increase after TGF-β administration. Conversely, WNT10A siRNA treatment inhibited the synthesis of collagen in the transfected fibroblasts cells. A Kaplan-Meier survival analysis demonstrated a tendency toward a poor survival among the IPF patients with a WNT10A-positive expression compared to those with a negative expression (Hazard ratio 5.351, 95 % CI 1.703-16.82; p = 0.0041). An overexpression of WNT10A was found to be significantly predictive of an acute exacerbation of IPF (AE-IPF) (Odds ratio 13.69, 95 % CI 1.728-108.5; p = 0.013). WNT10A plays an important role in the pathogenesis of IPF via TGF-β activation and it may also be a sensitive predictor for the onset of an AE-IPF. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 41 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 20% |
Student > Bachelor | 5 | 12% |
Other | 4 | 10% |
Researcher | 4 | 10% |
Student > Master | 3 | 7% |
Other | 7 | 17% |
Unknown | 10 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 15 | 37% |
Biochemistry, Genetics and Molecular Biology | 4 | 10% |
Agricultural and Biological Sciences | 4 | 10% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 7% |
Immunology and Microbiology | 2 | 5% |
Other | 2 | 5% |
Unknown | 11 | 27% |