Catalpol, a natural iridoid glycoside, has potential therapeutic benefits, including anti-inflammatory and neuroprotective effects. Investigating catalpol's role in angiogenesis is critical for understanding its potential therapeutic applications, particularly in diseases where modulating angiogenesis is beneficial. This study investigates catalpol's influence on angiogenesis and its mechanisms, combining network pharmacology and in vitro experiments. The target genes corresponding to the catalpol were analyzed by SwissTargetPrediction. Then angiogenesis-related targets were acquired from databases like GeneCards. Subsequently, the Database for Annotation, Visualization and Integrated Discovery was employed for Gene Ontology and pathway analysis, while Cytoscape visualized protein interactions. The effect of catalpol on viability and angiogenesis of HUVECs was further examined using Cell Counting Kit-8 and angiogenesis assays. RT-qPCR and western blot were applied to check the expression of angiogenesis-related proteins. Totally, 312 target genes of catalpol and 823 angiogenesis-related targets were obtained with 56 common targets leading to PPI network analysis, highlighting hub genes (AKT1, EGFR, STAT3, MAPK3, and CASP3). These hub genes were mainly enriched in lipid and atherosclerosis pathway and EGFR-related pathway. The in vitro experimental results showed that catalpol achieved a concentration-dependent increase in HUVECs viability. Catalpol also promoted the migration and angiogenesis of HUVECs and up-regulated the expression of EGFR. EGFR knockdown inhibited the effect of catalpol on HUVECs. Catalpol promotes angiogenesis in HUVECs by upregulating EGFR and angiogenesis-related proteins, indicating its potential therapeutic application in vascular-related diseases.
Keyphrases
- endothelial cells
- vascular endothelial growth factor
- small cell lung cancer
- wound healing
- network analysis
- epidermal growth factor receptor
- tyrosine kinase
- genome wide
- signaling pathway
- small molecule
- cardiovascular disease
- emergency department
- machine learning
- stem cells
- mesenchymal stem cells
- genome wide identification
- type diabetes
- anti inflammatory
- oxidative stress
- rna seq
- dna methylation
- deep learning
- artificial intelligence
- climate change
- pi k akt
- genome wide analysis