Background
Osteosarcoma is one of the leading causes in cancer-related death of children and adolescents. However current standard therapeutic strategy, surgery combined with neoadjuvant chemotherapy is very limited in effects. As big data mining and analysis using bioinformatics method has been applied in the diagnosis and treatment of many cancers, we want to use bioinformatic combined with experimental assays to found new molecular targets and test new drug for osteosarcoma.
Methods
The gene chip of osteosarcoma samples constructed by Richter GH et al were downloaded from the Gene Expression Omnibus (GEO) database, Gene Ontology analysis (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed on differential expression genes which screened by bioinformatics methods.
Protein-protein interaction network was constructed by suing STRING database to found hub gene. Combined with pertinent literature, genes of interest and corresponding drug was selected. Series of experiments were performed on the osteosarcoma cell lines in vitro, involved cell viability test, colony formation assay, migratory and invasive tests, western blot as well.
Results
A total of 1069 DEGs were obtained from data, including 375 up-regulated genes and 694 down-regulated genes. Differentially expressed genes mainly involve biological processes such as cellular immune function, such as interferon-gamma-mediated signaling pathway and antigen processing and presentation of peptide. Among top 20-ranked degree hug gene evaluated by PPI network, vascular cell adhesion molecule-1(VCAM1) was picked out. An VCAM1 inhibitor K-7174 was treated in U2OS and MG63 cell lines. In vitro experiments have shown that K-7174 can inhibit the proliferation, migration and invasion of osteosarcoma, the protein expression of VCAM1was also decreased by K-7174.
Conclusions
VCAM1 could be a potential target for osteosarcoma and K-7174 promises to be a therapeutic drug after more nuanced evaluation in animal and clinical trials.