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PLoS One ; 13(11): e0207872, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-30485339

RESUMEN

Pathological features of pulmonary fibrosis include accumulation of myofibroblasts and increased extracellular matrix (ECM) deposition in lung tissue. Contractile α-smooth muscle actin (α-SMA)-expressing myofibroblasts that produce and secrete ECM are key effector cells of the disease and therefore represent a viable target for potential novel anti-fibrotic treatments. We used primary normal human lung fibroblasts (NHLF) in two novel high-throughput screening assays to discover molecules that inhibit or revert fibroblast-to-myofibroblast differentiation. A phenotypic high-content assay (HCA) quantified the degree of myofibroblast differentiation, whereas an impedance-based assay, multiplexed with MS / MS quantification of α-SMA and collagen 1 alpha 1 (COL1) protein, provided a measure of contractility and ECM formation. The synthetic prostaglandin E1 (PGE1) alprostadil, which very effectively and potently attenuated and even reversed TGF-ß1-induced myofibroblast differentiation, was identified by screening a library of approved drugs. In TGF-ß1-induced myofibroblasts the effect of alprostadil was attributed to activation of prostanoid receptor 2 and 4 (EP2 and EP4, respectively). However, selective activation of the EP2 or the EP4 receptor was already sufficient to prevent or reverse TGF-ß1-induced NHLF myofibroblast transition. Our high-throughput assays identified chemical structures with potent anti-fibrotic properties acting through potentially novel mechanisms.


Asunto(s)
Evaluación Preclínica de Medicamentos/métodos , Ensayos Analíticos de Alto Rendimiento/métodos , Miofibroblastos/efectos de los fármacos , Miofibroblastos/metabolismo , Fibrosis Pulmonar/tratamiento farmacológico , Subtipo EP2 de Receptores de Prostaglandina E/agonistas , Subtipo EP4 de Receptores de Prostaglandina E/agonistas , Desdiferenciación Celular/efectos de los fármacos , Femenino , Humanos , Persona de Mediana Edad , Miofibroblastos/patología , Fenotipo , Fibrosis Pulmonar/metabolismo , Fibrosis Pulmonar/patología , Aprendizaje Automático Supervisado
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