Identification of Diagnostic Biomarkers for Myocardial Infarction Using Bioinformatics and Disulfidptosis-Targeted Computational Drug Discovery.

ABSTRACT: Disulfidptosis, a newly discovered form of regulated cell death, is involved in multiple disease processes. This study applied computational methods to identify disulfidptosis-related genes in myocardial infarction (MI). Differentially expressed genes (DEGs) from GSE66360 dataset were screened using the limma package and intersected with genes in weighted gene coexpression network analysis (WGCNA) modules to obtain candidate genes. Biomarkers were selected via support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO), and validated by quantitative real-time (qRT)-PCR, CCK-8, and flow cytometry. Enrichment and immune infiltration analyses were performed using clusterProfiler and CIBERSORT tools. Potential drugs were predicted

SUBMITTER: Zhang H 

PROVIDER: S-EPMC12419921 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature