ArticleBMC cardiovascular disorders2024
The diagnostic value investigation of programmed cell death genes in heart failure.
Article in BMC cardiovascular disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Identification and validation of STEAP3 as a ferroptosis-related biomarker in heart failure.Frontiers in cardiovascular medicine · 2026Article
- Relationship between cathepsin K and extracellular matrix dynamics: a comprehensive review.Frontiers in oncology · 2026Review
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe aimed to identify the potential diagnostic markers and associated molecular mechanisms based on programmed cell death (PCD)-related genes in patients with heart failure (HF).
methodsThree HF gene expression data were extracted from the GEO database, including GSE57345 (training data), GSE141910 and GSE76701 (validation data), followed by differentially PCD related genes (DPCDs) was shown between HF and control samples. Enrichment and protein-protein interaction (PPI) network analyses were performed based on the DPCDs. Subsequently, a diagnostic model was constructed and validated after exploring the diagnostic markers using machine learning. A nomogram was used to determine the clinical diagnostic value. Diagnostic marker-based immune, transcription network, and gene set enrichment (GSE) analyses were performed. Finally, the drug-target network was investigated.
resultsTwenty DPCDs were revealed between the two groups. These genes, such as Serpin Family E Member 1 (SERPINE1), are mainly enriched in pathways such as the regulation of the inflammatory response. A PPI network was constructed using 14 DPCDs. Eight diagnostic markers, such as SERPINE1, CD38 molecule (CD38), and S100 calcium-binding protein A9 (S100A9), were explored using machine learning algorithms, followed by diagnostic model construction. A nomogram and immune-associated analysis was used to validate the diagnostic value of these genes and the model. Moreover, the transcription regulation network and drug-target interactions were further investigated. Finally, qRT-PCR confirmed that the expression levels of eight signature genes (CD14, CD38, CTSK, LAPTM5, S100A9, SERPINE1, SLC11A1, and STAT3) were significantly elevated in the observation group, consistent with the results of bioinformatics analysis.
conclusionsThis study constructed a valuable diagnostic model for HF using the eight identified DPCDs as diagnostic markers.
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