ArticleJournal of inflammation research2024
Cuproptosis-Related Genes as Prognostic Biomarkers for Sepsis: Insights into Immune Function and Personalized Immunotherapy.
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 11 papers.
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Who cites it
11 citing papers in PubMed.
- Combining bioinformatics and machine learning to analyze and validate sepsis-related cell senescence genes and potential drugs.Renal failure · 2026Article
- SF1 regulates the transcription of FDX1 to promote cuproptosis in pediatric sepsis-related acute lung injury by interacting with cJUN.Biology direct · 2026Article
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- Aging at the Crossroads of Cuproptosis and Ferroptosis: From Molecular Pathways to Age-Related Pathologies and Therapeutic Perspectives.International journal of molecular sciences · 2026Review
- Identification of immunometabolism-associated genes and immune infiltration in sepsis-induced cardiomyopathy using integrated bioinformatics and machine learning approaches.The Journal of international medical research · 2025Article
- T cell-related diagnostic model and the underlying mechanism related to PRF1-mediated glycolysis in sepsis: evidences from single-cell, bulk transcriptomics, and experiment validation.European journal of medical research · 2025Article
- Integrated bioinformatics and experiment validation reveal cuproptosis-related biomarkers and therapeutic targets in sepsis-induced myocardial dysfunction.BMC infectious diseases · 2025Article
- Multi-Dimensional Characterization of Programmed Cell Death Patterns for Prognostic Stratification and Therapeutic Insights in Sepsis.ImmunoTargets and therapy · 2025Article
- The potential impact of GLS and PDHA1 on tumor immunity and immunotherapy response in LUSC.Frontiers in genetics · 2025Article
- Application of Machine Learning and Mendelian Randomization Analysis to Identify the Cuproptosis-Related Biomarker and Its Related Regulation in Osteonecrosis of the Femoral Head.Current genomics · 2025Article
- The role of cuproptosis in gastric cancer.Frontiers in immunology · 2024Review
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to discover diagnostic and prognostic biomarkers for sepsis immunotherapy through analyzing the novel cellular death process, cuproptosis. Methods: We used transcriptome data from sepsis patients to identify key cuproptosis-related genes (CuRGs). We created a predictive model and used the CIBERSORT algorithm to observe the link between these genes and the septic immune microenvironment. We segregated sepsis patients into three subgroups, comparing immune function, immune cell infiltration, and differential analysis. Single-cell sequencing and real-time quantitative PCR were used to view the regulatory effect of CuRGs on the immune microenvironment and compare the mRNA levels of these genes in sepsis patients and healthy controls. We established a sepsis forecast model adapted to heart rate, body temperature, white blood cell count, and cuproptosis key genes. This was followed by a drug sensitivity analysis of cuproptosis key genes. Results: Our results filtered three key genes (LIAS, PDHB, PDHA1) that impact sepsis prognosis. We noticed that the high-risk group had poorer immune cell function and lesser immune cell infiltration. We also discovered a significant connection between CuRGs and immune cell infiltration in sepsis. Through consensus clustering, sepsis patients were classified into three subgroups. The best immune functionality and prognosis was observed in subgroup B. Single-cell sequencing exposed that the key genes manage the immune microenvironment by affecting T cell activation. The qPCR results highlighted substantial mRNA level reduction of the three key genes in the SP compared to the HC. The prediction model, which combines CuRGs and traditional diagnostic indicators, performed better in accuracy than the other markers. The drug sensitivity analysis listed bisphenol A as highly sensitive to all the key genes. Conclusion: Our study suggests these CuRGs may offer substantial potential for sepsis prognosis prediction and personalized immunotherapy.
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