Background
Osthole was traditionally used in treatment for various diseases. However, few studies had demonstrated that osthole could suppress bladder cancer cells and its mechanism was unclear. Therefore, we performed a research to explore the potential mechanism for osthole against bladder cancer.
Methods
Internet web servers SwissTargetPrediction, PharmMapper, SuperPRED, and TargetNet were used to predict the Osthole targets. GeneCards and the OMIM database were used to indicate bladder cancer targets. The intersection of two target gene fragments was used to obtain the key target genes. Protein–protein interaction (PPI) analysis was performed using the Search Tool for the Retrieval of Interacting Genes (STRING) database. Furthermore, we used gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to explore the molecular function of target genes. AutoDock software was then used to perform molecular docking of target genes,osthole and co-crystal ligand. Finally, an in vitro experiment was conducted to validate bladder cancer inhibition by osthole.
Results
Our analysis identified 369 intersection genes for osthole, the top ten target genes included MAPK1, AKT1, SRC, HRAS, HASP90AA1, PIK3R1, PTPN11, MAPK14, CREBBP, and RXRA. The GO and KEGG pathway enrichment results revealed that the PI3K-AKT pathway was closely correlated with osthole against bladder cancer. The osthole had cytotoxic effect on bladder cancer cells according to the cytotoxic assay. Additionally, osthole blocked the bladder cancer epithelial-mesenchymal transition and promoted bladder cancer cell apoptosis by inhibiting the PI3K-AKT and Janus kinase/signal transducer and activator of transcription (JAK/STAT3) pathways.
Conclusions
We found that osthole had cytotoxic effect on bladder cancer cells and inhibited invasion, migration, and epithelial-mesenchymal transition by inhibiting PI3K-AKT and JAK/STAT3 pathways in in vitro experiment. Above all, osthole might have potential significance in treatment of bladder cancer.
Subjects
Bioinformatics, Computational Biology, Molecular Biology.