Key candidate genes of STAT1 and CXCL10 in melanoma identified by integrated bioinformatical analysis.

The underlying mechanisms and gene signatures of melanoma are unknown. In this study, three expression profile data sets (GSE65568, GSE100050, GSE114445) were integrated to identify candidate genes explaining the pathways and functions of melanoma. Expression data sets including 24 melanoma tumours and 13 normal skin samples were merged and analysed in detail. The three GSE profiles shared 431 differentially expressed genes (DEGs), including 227 upregulated genes, 200 downregulated genes and 4 differentially regulated genes. Moreover, the functions and signalling pathways of the shared DEGs with significant p-values were identified. The two most significant modules were filtered from the DEGs protein-protein interaction (PPI) network, which consisted of 284 nodes. We also plotted the prognostic value of hub genes from an online database. In summary, using integrated bioinformatic analysis, we have identified candidate DEGs and pathways in melanoma that could improve our understanding of the causes and underlying molecular events of melanoma, and these candidate genes and pathways could be therapeutic targets for melanoma.