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

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.

Ethanol Metabolism and Melanoma

“…Among the ethanol metabolizing enzymes (ADH1-7, CYP2E1, and CAT), ADH1B, ADH5, and CAT were relatively highly expressed in all three datasets. When compared to normal skin tissues, primary melanoma tissues showed reduced ADH1B, CYP2E1, and CAT gene expression in at least two of three datasets (Figure 3b,h,i, left), consistent with previous observations for ADH1B [147,148]. Moreover, CYP2E1 was shown to be further downregulated in metastatic melanoma compared to primary melanoma in two of three datasets (Figure 3h, left).…”

“…Several recent studies have suggested the potential roles of ethanol metabolizing enzymes in human melanoma by identifying differentially expressed genes using publicly available microarray data. Liu et al analyzed three microarray datasets from the Gene Expression Omnibus (GEO) database, including GSE15605, GSE46517, and GSE114445, and found that ADH1B was significantly downregulated in primary melanoma samples vs. normal skin samples [147]. Their Cox regression analysis revealed that ADH1B is an independent prognostic factor in human melanoma [147].…”

“…Liu et al analyzed three microarray datasets from the Gene Expression Omnibus (GEO) database, including GSE15605, GSE46517, and GSE114445, and found that ADH1B was significantly downregulated in primary melanoma samples vs. normal skin samples [147]. Their Cox regression analysis revealed that ADH1B is an independent prognostic factor in human melanoma [147]. Another study confirmed the downregulation (~9-fold) of ADH1B in human primary melanoma samples compared to normal skin tissues by analyzing two of the three datasets (GSE15605 and GSE46517) and another dataset GDS1375 [148].…”

Integrated network pharmacology analysis and in vitro validation revealed the underlying mechanism of Xiyanping injection in treating coronavirus disease 2019

“…Key modules were also analyzed using the Molecular Complex Detection (MCODE) algorithm. [ 29 ] The parameters were set to Degree Cutoff = 2, Node Score Cutoff = 0.2 and K-Core = 2. Then, the DAVID ( https://david.ncifcrf.gov/ ) database was used for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of the core modules, and adj- P < .05 was set as the screening criterion.…”

Association between environmental chemicals co-exposure and peripheral blood immune-inflammatory indicators

“…In the present study, the chemicals - genes associated with inflammation were obtained from CTD ( http://CTD.mdibl.org ), which is a robust, publicly available database that provides manually curated information about chemical–gene/protein interactions. In order to explore chemical-immune inflammation genes function, pathway and disease enrichment characteristics, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and DisGeNET (DGN) enrichment analyses were evaluated using R packages “clusterProfiler (version 4.2.2) ” and “DOSE (version 3.20.1)” ( 23 ). In order to further discover and explore the chemical-immune inflammation genes interaction at the protein level, chemical-immune inflammation genes were uploaded to the Search Tool for the Retrieval of Interacting Genes (STRING) database (Version 10.0, http://string-db.org ) and a combined score > 0.4 (medium confidence score) was considered significant.…”