Pharmacological and genetic reappraisals of protease and oxidative stress pathways in a mouse model of obstructive lung diseases.
Sci Rep
; 6: 39305, 2016 12 16.
Article
en En
| MEDLINE
| ID: mdl-27982104
ABSTRACT
Protease-antiprotease imbalance and oxidative stress are considered to be major pathophysiological hallmarks of severe obstructive lung diseases including chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF), but limited information is available on their direct roles in the regulation of pulmonary phenotypes. Here, we utilized ßENaC-transgenic (Tg) mice, the previously established mouse model of severe obstructive lung diseases, to produce lower-mortality but pathophysiologically highly useful mouse model by backcrossing the original line with C57/BL6J mice. C57/BL6J-ßENaC-Tg mice showed higher survival rates and key pulmonary abnormalities of COPD/CF, including mucous hypersecretion, inflammatory and emphysematous phenotypes and pulmonary dysfunction. DNA microarray analysis confirmed that protease- and oxidative stress-dependent pathways are activated in the lung tissue of C57/BL6J-ßENaC-Tg mice. Treatments of C57/BL6J-ßENaC-Tg mice with a serine protease inhibitor ONO-3403, a derivative of camostat methylate (CM), but not CM, and with an anti-oxidant N-acetylcystein significantly improved pulmonary emphysema and dysfunction. Moreover, depletion of a murine endogenous antioxidant vitamin C (VC), by genetic disruption of VC-synthesizing enzyme SMP30 in C57/BL6J-ßENaC-Tg mice, exaggerated pulmonary phenotypes. Thus, these assessments clarified that protease-antiprotease imbalance and oxidative stress are critical pathways that exacerbate the pulmonary phenotypes of C57/BL6J-ßENaC-Tg mice, consistent with the characteristics of human COPD/CF.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Transducción de Señal
/
Estrés Oxidativo
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Perfilación de la Expresión Génica
/
Redes y Vías Metabólicas
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Enfermedades Pulmonares Obstructivas
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Sci Rep
Año:
2016
Tipo del documento:
Article