Abstract
PURPOSE: This study aimed to identify potential diagnostic markers of restenosis after stent implantation and to determine their association with immune checkpoint, ferroptosis, and N6-methyladenosine (m6A). PATIENTS AND METHODS: Microarray data were downloaded from the National Center for Biotechnology Information (NCBI: GSE46560 and GSE48060 datasets) to identify differentially expressed genes (DEGs) between in-stent restenosis and no-restenosis samples. We then conducted systematic functional enrichment analyses of the DEGs based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and further predicted the interactions of different proteins using the Search Tool for the Retrieval of Interacting Genes (STRING). We used the MCC and MCODE algorithms in the cytoHubba plug-in to screen three key genes in the network, and employed receiver operating characteristic (ROC) curves to determine their diagnostic significance using a multiscale curvature classification algorithm. Next, we investigated the relationships between these target genes, immune checkpoint, ferroptosis, and m6A. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the above results. RESULTS: We identified 62 upregulated genes and 243 downregulated genes. Based on GO, KEGG, and screening results, EEF1D, RPL36, and RPSA are promising genes for predicting restenosis. In addition, the methylation of YTHDF2, the ferroptosis-related gene GLS2, and the immune checkpoint-related gene CTLA4 were observed to be associated with restenosis. The qRT-PCR test confirmed that RPSA and RPL36 are useful diagnostic markers of the restenosis that can provide new insights for future studies on its occurrence and molecular mechanisms. CONCLUSION: We found that RPSA and RPL36, as useful diagnostic markers of restenosis, can provide new insights for future studies on its occurrence and molecular mechanisms.