Atherosclerosis is an underlying cause of cardiovascular disease which is a leading cause of death worldwide. Foam cells play a crucial role in atherosclerotic lesion development, and macrophages and vascular smooth muscle cells (VSMCs) appear to contribute to the formation of the majority of atheromatous foam cells via oxidized low-density lipoprotein (ox-LDL) uptake.
An integrated, microarray-based analysis using GSE54666 and GSE68021, which contain samples of human macrophages and VSMCs incubated with ox-LDL, was conducted. The differentially expressed genes (DEGs) in each dataset were investigated via the linear models for microarray data ( limma) v. 3.40.6 software package in R v. 4.1.2 (The R Foundation for Statistical Computing). Gene ontology (GO) and pathway enrichment were performed via the ClueGO v. 2.5.8 and CluePedia v. 1.5.8 databases and the Database of Annotation, Visualization and Integrated (DAVID; https://david.ncifcrf.gov). The convergent DEGs in the two cell types were obtained, and the protein interactions and network of transcriptional factors were analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) v. 11.5 and the Transcriptional Regulatory Relationships Unraveled by Sentence-based Text-mining (TRRUST) v. 2 databases. The selected DEGs were further validated using external data from GSE9874, and a machine learning algorithm of the least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) analysis were applied to explore the candidate biomarkers.
We discovered the significant DEGs and pathways that were shared or unique among the 2 cell types, coupling with enriched lipid metabolism in macrophages, and upregulated defense response in VSMCs. Moreover, we identified BTG2, ABCA1, and SLC7A11 as potential biomarkers and molecular targets for atherogenesis.