Affiliation:
1. Department of Respiratory Medicine and Rheumatology, Graduate School of Biomedical Sciences, Tokushima University
2. Department of Pathology and Laboratory Medicine, Graduate School of Biomedical Sciences, Tokushima University
3. Department of Clinical Pharmacology and Therapeutics, Graduate School of Biomedical Sciences, Tokushima University
Abstract
Abstract
Background
Idiopathic pulmonary fibrosis (IPF) is a fatal fibrotic lung disease with few effective therapeutic options. Recently, drug repositioning, which involves identifying novel therapeutic potentials for existing drugs, has been popularized as a new approach for the development of novel therapeutic reagents. However, this approach has not yet been fully utilized in the field of pulmonary fibrosis.
Methods
The present study identified novel therapeutic options for pulmonary fibrosis using a systematic computational approach for drug repositioning based on integration of public gene expression signatures of drug and diseases (in silico screening approach).
Results
Among the top compounds predicted to be therapeutic for IPF by the in silico approach, we selected BI2536, a polo-like kinase (PLK) 1/2 inhibitor, as a candidate for treating pulmonary fibrosis using an in silico analysis. However, BI2536 accelerated mortality and weight loss rate in an experimental mouse model of pulmonary fibrosis. Because immunofluorescence staining revealed that PLK1 expression was dominant in myofibroblasts while PLK2 expression was dominant in lung epithelial cells, we next focused on the anti-fibrotic effect of the selective PLK1 inhibitor GSK461364. Consequently, GSK461364 attenuated pulmonary fibrosis with acceptable mortality and weight loss in mice.
Conclusions
These findings suggest that targeting PLK1 may be a novel therapeutic approach for pulmonary fibrosis by inhibiting lung fibroblast proliferation without affecting lung epithelial cells. In addition, while in silico screening is useful, it is essential to fully determine the biological activities of candidates by wet-lab validation studies.
Publisher
Research Square Platform LLC