Identification of cuproptosis-related characteristic genes in unstable atherosclerotic plaque
Objective:To identify the characteristic genes related to cuproptosis and atherosclerotic plaque instability through bioinformatics.Methods:Datasets(GSE163154,GSE41571,and GSE43292)re-lated to atherosclerotic plaque were downloaded from the comprehensive database of gene expression.Three datasets were merged and differential expression analysis was based on the collected cuproptosis-related genes(CRGs).Three algorithms of machine learning were used to screen the characteristic genes in the differentially expressed CRGs,and the results were verified using the external dataset GSE28829.Results:A total of 27 differentially expressed CRGs were identified.Based on three ma-chine learning algorithms,which contain algorithms of least absolute shrinkage and selection operator(LASSO),support vector machine-recursive feature elimination(SVM-RFE),and random forest(RF),five feature genes,ATOX1,NLRP3,MAP1LC3A,SLC31A1,and ATP7B,were select-ed.Diagnostic effectiveness was verified using receiver operating characteristic(ROC)curves in exter-nal datasets.Conclusion:The results show that copper death is closely related to the instability of ath-erosclerotic plaque,which provides new insights into the pathogenesis and treatment of unstable ath-erosclerotic plaque.
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