ArticleBMC bioinformatics2023
A signature of immune-related genes correlating with clinical prognosis and immune microenvironment in sepsis.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genetic association studies in critically ill patients: a systematic review.EBioMedicine · 2025Pooled it
- Oroxin B prevented sepsis-evoked acute lung injury by promoting M2 macrophage polarization through the TLR4/NF-κB axis.Histology and histopathology · 2025Article
- Article
- Machine learning-based identification of leptin-associated biomarkers and prognostic prediction models in sepsis.Frontiers in cellular and infection microbiology · 2025Article
- Blood RNA biomarkers and a point-of-care elastase assay for detecting host immune activation in suspected sepsis: Trajectory matters.PloS one · 2025Article
- Article
- Acacetin protects against sepsis-induced acute lung injury by facilitating M2 macrophage polarization via TRAF6/NF-κB/COX2 axis.Innate immunity · 2024Article
- Whole blood ratio ofFrontiers in medicine · 2024Article
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6 authors.
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Abstract
backgroundImmune-related genes (IRGs) remain poorly understood in their function in the onset and progression of sepsis.
methodsGSE65682 was obtained from the Gene Expression Omnibus database. The IRGs associated with survival were screened for subsequent modeling using univariate Cox regression analysis and least absolute shrinkage and selection operator in the training cohort. Then, we assessed the reliability of the 7 IRGs signature's independent predictive value in the training and validation cohorts following the creation of a signature applying multivariable Cox regression analysis. After that, we utilized the E-MTAB-4451 external dataset in order to do an independent validation of the prognostic signature. Finally, the CIBERSORT algorithm and single-sample gene set enrichment analysis was utilized to investigate and characterize the properties of the immune microenvironment.
resultsBased on 7 IRGs signature, patients could be separated into low-risk and high-risk groups. Patients in the low-risk group had a remarkably increased 28-day survival compared to those in the high-risk group (P < 0.001). In multivariable Cox regression analyses, the risk score calculated by this signature was an independent predictor of 28-day survival (P < 0.001). The signature's predictive ability was confirmed by receiver operating characteristic curve analysis with the area under the curve reaching 0.876 (95% confidence interval 0.793-0.946). Moreover, both the validation set and the external dataset demonstrated that the signature had strong clinical prediction performance. In addition, patients in the high-risk group were characterized by a decreased neutrophil count and by reduced inflammation-promoting function.
conclusionWe developed a 7 IRGs signature as a novel prognostic marker for predicting sepsis patients' 28-day survival, indicating possibilities for individualized reasonable resource distribution of intensive care unit.
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