Effects of Combined Admistration of Imatinib and Sorafenib in a Murine Model of Liver Fibrosis.
Antonio PesceRosella CiurleoAlessia BramantiEliana Concetta Armeli IapichinoMaria Cristina PetraliaGaetano Giuseppe MagroPaolo FagonePlacido BramantiFerdinando NicolettiKatia ManganoPublished in: Molecules (Basel, Switzerland) (2020)
Liver fibrosis is defined as excessive extracellular matrix deposition in the hepatic parenchyma as a consequence of complex interactions among matrix-producing hepatic stellate cells (HSCs) and liver-resident and infiltrating cells. In addition to the liver, the process of fibrosis may represent end-stage disease of several diseases including kidneys, lungs, spleens, heart, muscles and at certain extent, the central nervous system and the peripheral nerves. To date, antifibrotic treatment of fibrosis represents an unconquered area for drug development. The aim of the present study was to test the efficacy of a new drug combination for the treatment of hepatic fibrosis in order to provide a proof-of-concept for the use of therapeutic agents in clinical practice. For this purpose, we have studied the effects of the PDGF inhibitor imatinib and the angiogenesis inhibitor sorafenib, administered alone or in combination, in reducing the progression of the fibrogenetic process in a pre-clinical model of liver damage induced in mice by repeated administration of Concanavalin A (ConA), resembling long-tern autoimmune hepatitis. Our results suggest that treatments with imatinib and sorafenib can modulate potently and, in a superimposable fashion, the fibrinogenic process when administered alone. However, and in agreement with the computational data presently generated, they only exert partial overlapping antifibrotic effects in modulating the main pathways involved in the process of liver fibrosis, without significant additive or synergist effects, when administered in combination.
Keyphrases
- liver fibrosis
- extracellular matrix
- induced apoptosis
- clinical practice
- cell cycle arrest
- chronic myeloid leukemia
- oxidative stress
- heart failure
- multiple sclerosis
- signaling pathway
- endothelial cells
- type diabetes
- drug induced
- patient safety
- atrial fibrillation
- weight gain
- cell death
- diabetic rats
- quality improvement
- high fat diet induced
- electronic health record
- machine learning
- cell proliferation
- skeletal muscle
- angiotensin ii
- combination therapy
- physical activity
- smooth muscle
- pi k akt
- cerebrospinal fluid
- deep learning
- pulmonary fibrosis