Prediction of the engendering mechanism and specific genes of primary melanoma by bioinformatics analysis

Objective: Our aim was to explore the engendering mechanism and gene targets for melanoma. Methods: The microarray data of GSE46517 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between primary melanoma samples and normal controls were analyzed using the GEO2R online tool. The screened DEGs were mapped to a protein-protein interaction network based on the Search Tool for the Retrieval of Interacting Genes database. The functions and pathways involved with DEGs were analyzed using the Database for Annotation Visualization and Integrated Discovery software) online tools. Then, the DEGs were further annotated via the TRANSFAC, Tumor-Suppressor Gene, and Tumor-Associated Gene databases. Results: A total of 1095 DEGs including 511 upregulated genes and 584 down-regulated ones were screened out. The nodes of CCL5, ISG15, CDKN2A, EGFR, and ERBB2 showed a high connectivity degree in protein-protein interaction networks and were mainly enriched in Biological Process GO terms such as the regulation of catalytic activity and cell adhesion, as well as the pathways of cytochrome P450. The DEGs were classified into 31 transcription factors and 43 downregulated tumor associated genes. Conclusion: Catalytic activity, cell adhesion, and the cytochrome P450 associated pathways are dysregulated in the melanoma formation. The significant nodes such as ISG15, IRF4, ERBB2 and EGFP may be potential targets for primary melanoma treatment. Copyright (C) 2015, Taiwanese Dermatological Association. Published by Elsevier Taiwan LLC.