Identification and prediction of common molecular culprits between psoriasis and melanoma via bioinformatical analysis

Abstract

Background: Psoriasis is an autoimmune, chronic inflammatory dermatosis characterized by excessive hyperproliferation of keratinocytes, manifested by skin lesions. Melanoma is a type of skin cancer that develops from melanocytes. Growing epidemiology evidence has indicated psoriasis could be associated with melanoma. This study aims to explore the common molecular mechanisms that connect psoriasis with melanoma. Methods: Differentially expressed genes (DEGs) were obtained from melanoma and psoriasis GEO datasets. Next, using the GEO2R tool, common DEGs between melanoma and psoriasis samples were picked out. Finally, using in silico analysis, the hub genes and their significant molecular mechanisms were identified. Results: 244 DEGs (p < 0.05, vertical bar LogFC vertical bar >= 1) were shared between psoriasis and melanoma. Of these, 116 were down-regulated, and 62 were up-regulated. In the protein-protein interaction (PPI) network, 19 DEGs were obtained as central nodes with criteria of interaction numbers and considered as hubs. Besides, the most crucial axis (module) among DEGs was predicted. Finally, Toll-like receptors and chemokine signaling pathways were identified as potential mechanisms underlying psoriasis and melanoma. Conclusion: This in-silico study may shed light on the molecular culprits that predispose psoriasis patients to melanoma.