ArticleFrontiers in cardiovascular medicine2023
Coronary artery disease-associated immune gene
Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Comprehensive Analysis Based on Genes Associated With Cuproptosis, Ferroptosis, and Pyroptosis for the Prediction of Diagnosis and Therapies in Coronary Artery Disease.Cardiovascular therapeutics · 2025Article
- Identification of Disease-Relevant, Sex-Based Proteomic Differences in iPSC-Derived Vascular Smooth Muscle Cells.International journal of molecular sciences · 2024Article
- Identification of Endoplasmic Reticulum Stress-Related Biomarkers in Coronary Artery Disease.Cardiovascular therapeutics · 2024Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To identify immune-related biomarkers in coronary artery disease (CAD), investigate their possible function in the immunological milieu of tumors, and initially investigate the mechanisms and therapeutic targets shared by CAD and cancer. Methods: Download the CAD-related dataset GSE60681 from the GEO database. GSVA and WGCNA analyses were performed based on the GSE60681 dataset to identify the modules most pertinent to CAD, identify candidate hub genes and finally intersect the genes associated with immunity downloaded from the import database to find the hub genes. The GTEx, CCLE, and TCGA database were used to examine the expression of the hub gene in normal tissues, tumor cell lines, tumor tissues, and different tumor STAGES. One-factor cox and Kaplan-Meier analyses were performed to explore the prognosis of hub genes. Hub gene methylation levels in CAD and cancer were analyzed in the diseaseMeth 3.0 and ualcan databases, respectively. R package CiberSort processed the GSE60681 dataset to assess immune infiltration in CAD. TIMER2.0 evaluated hub genes with pan-cancer immune infiltration. The hub genes were analyzed for drug sensitivity and correlation with TMB, MSI, MMR, cancer-related functional status, and immune checkpoints in different tumors. Finally, GSEA was carried out on the crucial genes. Results: WGCNA were used to pinpoint the green modules that were most closely related to CAD and intersections with immune-related genes were taken to remember the pivotal gene Conclusion:
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