ArticleJournal of inflammation research2024
Cuproptosis-Related Biomarkers and Characterization of Immune Infiltration in Sepsis.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- SF1 regulates the transcription of FDX1 to promote cuproptosis in pediatric sepsis-related acute lung injury by interacting with cJUN.Biology direct · 2026Article
- Non-apoptotic Regulated Cell Death Mechanisms in Sepsis and their Therapeutic Potential.Inflammation · 2026Review
- SLC31A1 knockdown mitigates post-MI heart failure via regulation of copper metabolism.Frontiers in immunology · 2026Article
- The clinical significance of miR-18a-3p in traumatic spinal cord injury and its functional role in mediating apoptosis, inflammation and oxidative stress.Journal of orthopaedic surgery and research · 2025Article
- Redox Network Dysfunction: Integrating Ferroptosis and Cuproptosis Across Human Diseases.Antioxidants (Basel, Switzerland) · 2025Review
- Integrated bioinformatics and experiment validation reveal cuproptosis-related biomarkers and therapeutic targets in sepsis-induced myocardial dysfunction.BMC infectious diseases · 2025Article
- Cuproptosis related genes in immune infiltration and treatment of osteoporosis by bioinformatic analysis and machine learning methods.Frontiers in physiology · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Sepsis is a worldwide epidemic, with high morbidity and mortality. Cuproptosis is a form of cell death that is associated with a wide range of diseases. This study aimed to explore genes associated with cuproptosis in sepsis, construct predictive models and screen for potential targets. Methods: The LASSO algorithm and SVM-RFE model has been analysed the expression of cuproptosis-related genes in sepsis and immune infiltration characteristics and identified the marker genes under a diagnostic model. Gene-drug networks, mRNA-miRNA networks and PPI networks were constructed to screen for potential biological targets. The expression of marker genes was validated based on the GSE57065 dataset. Consensus clustering method was used to classify sepsis samples. Results: We found 381 genes associated with the development of sepsis and discovered significantly differentially expressed cuproptosis-related genes of 16 cell types in sepsis and immune infiltration with CD8/CD4 T cells being lower. Discussion: Our study systematically explored the relationship between sepsis and cuproptosis and constructed a diagnostic model. And, several cuproptosis-related genes may interfere with the progression of sepsis through immune cell infiltration.
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Registered trials
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