Using bioinformatics to reveal the pathogenic mechanisms of small ubiquitin-like modification in psoriasis and to predict drug sensitivity

[Objective] Using bioinformatics to assess the expression levels and regulatory mechanisms of small ubiquitin-related modifier (SUMO) in psoriasis, and to analyze its effect on metabolism. [Methods] R language (3.3.6 version) was used to determine the difference in expression levels of SUMO between psoriatic patients and controls, and the receiver operating characteristic (ROC) curve of SUMO. The interaction network of SUMO was built using the website of GeneMANIA. The network gene enrichment analysis software GSVA was used to determine the enrichment pathway of SUMO in the psoriasis dataset. XGBOOST and random forest were used to screen dominant genes and verify their differential expression. pRRophetic was used to identify potential drugs targeting SUMO in the psoriasis dataset. [Results] SUMO1, SUMO3, SUMO1P3, SUMO2P3 were highly expressed in psoriasis-involved skin. SUMO interacted with multiple metabolic pathways in psoriasis. SUMO1 could be the gene most closely related to metabolic pathways. [Conclusions] SUMO mRNA is highly expressed in psoriasis-involved skin, and SUMO1 may be involved in the onset and development of psoriasis by regulating the metabolic process.