In Vitro Generated Equine Hepatic-Like Progenitor Cells as a Novel Potent Cell Pool for Equine Metabolic Syndrome (EMS) Treatment.
Krzysztof MaryczNabila BourebabaAnna Serwotka-SuszczakMalwina MularczykLarry GaluppoLynda BourebabaPublished in: Stem cell reviews and reports (2023)
Equine metabolic syndrome (EMS) is recognized as one of the leading cause of health threatening in veterinary medicine worldwide. Recently, PTP1B inhibition has been proposed as an interesting strategy for liver insulin resistance reversion in both equines and humans, however as being a multifactorial disease, proper management of EMS horses further necessities additional interventional approaches aiming at repairing and restoring liver functions. In this study, we hypothesized that in vitro induction of Eq_ASCs hepatogenic differentiation will generate a specialized liver progenitor-like cell population exhibiting similar phenotypic characteristics and regenerative potential as native hepatic progenitor cells. Our obtained data demonstrated that Eq_ASCs-derived liver progenitor cells (Eq_HPCs) displayed typical flattened polygonal morphology with packed fragmented mitochondrial net, lowered mesenchymal CD105 and CD90 surface markers expression, and significant high expression levels of specific hepatic lineage genes including PECAM-1, ALB, AFP and HNF4A. therewith, generated Eq_HPCs exhibited potentiated stemness and pluripotency markers expression (NANOG, SOX-2 and OCT-4). Hence, in vitro generation of hepatic progenitor-like cells retaining high differentiation capacity represents a promising new approach for the establishment of cell-based targeted therapies for the restoration of proper liver functions in EMS affected horses.
Keyphrases
- metabolic syndrome
- stem cells
- insulin resistance
- single cell
- poor prognosis
- cell therapy
- public health
- type diabetes
- uric acid
- mesenchymal stem cells
- palliative care
- binding protein
- high fat diet
- gene expression
- big data
- social media
- dna methylation
- anti inflammatory
- cardiovascular risk factors
- polycystic ovary syndrome
- human health
- electronic health record
- epithelial mesenchymal transition
- combination therapy
- diabetic retinopathy
- nk cells
- bioinformatics analysis
- artificial intelligence
- machine learning
- tissue engineering