Identification of biomarkers and key pathways in synovial sarcoma cells exposed to anlotinib by integrating bioinformatics analysis and experimental validation.

OBJECTIVE:To identify potential biomarkers, key pathways and modules following the exposure of synovial sarcoma (SS) cells to anlotinib. METHODS:In the current study, we integrated multiple bioinformatics methods to identify the hub genes and key pathways associated with the effects of anlotinib treatment in SS cells. In addition, we used reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) to validate the expression levels of the identified hub genes in SS cells treated with anlotinib. RESULTS:In total, 183 differentially expressed genes (DEGs) were identified, of which 47 were upregulated and 136 were downregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that the DEGs were predominantly involved in cell division and cell cycle progression. A total of two modules were identified from the protein-protein interaction network using the MCODE plugin in Cytoscape, where module 1 was the most significant. By combining the results of CytoHubba analysis based on the module 1 and The Cancer Genome Atlas database, six real hub genes, cyclin (CCN) A2, kinesin family member 2C, cell division cycle 20, CCNB2, aurora kinase B and CCNB1, were identified. Subsequent GO and KEGG pathway analysis revealed that these six real hub genes were significantly associated with the cell cycle and mitosis. Finally, RT-qPCR verified that the mRNA expression levels of these six real hub genes were significantly decreased in SS cells treated with anlotinib compared with those in the control group. Altogether, our study identified biomarkers and key pathways associated with the effects of anlotinib treatment in SS cells, which may provide novel insights into the underlying mechanism of anlotinib treatment in SS.