Identification of Potential Biomarkers and Small Molecule Drugs for Cutaneous Melanoma Using Integrated Bioinformatic Analysis

Front Cell Dev Biol. 2022 Mar 30:10:858633. doi: 10.3389/fcell.2022.858633. eCollection 2022.

Abstract

Background: Cutaneous melanoma (CM) is a type of skin cancer with a high fatality rate, and its pathogenesis has not yet been fully elucidated. Methods: We obtained the gene expression datasets of CM through the Gene Expression Omnibus (GEO) database. Subsequently, robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between CM cases and normal skin controls. Gene functional annotation was performed to explore the potential function of the DEGs. We built the protein-protein interaction (PPI) network by the Interactive Gene database retrieval tool (STRING) and selected hub modules by Molecular Complexity Detection (MCODE). We furthered and validated our results using the TCGA-GTEX dataset. Finally, potential small molecule drugs were predicted by CMap database and verified by molecular docking method. Results: A total of 135 DEGs were obtained by RRA synthesis analysis. GMPR, EMP3, SLC45A2, PDZD2, NPY1R, DLG5 and ADH1B were screened as potential targets for CM. Furazolidone was screened as a potential small molecule drug for the treatment of CM, and its mechanism may be related to the inhibition of CM cell proliferation by acting on GMPR. Conclusion: We identified seven prognostic therapeutic targets associated with CM and furazolidone could be used as a potential drug for CM treatment, providing new prognostic markers, potential therapeutic targets and small molecule drugs for the treatment and prevention of CM.

Keywords: bioinformatics; cutaneous melanoma; furazolidone; normal skin; prognosis.