ArticleFrontiers in immunology2025
Identification and validation of NETs-related biomarkers in active tuberculosis through bioinformatics analysis and machine learning algorithms.
Article in Frontiers in immunology, 2025. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- HeptaTB Dx: a diagnostic model leveraging cuproptosis-ferroptosis crosstalk for distinguishing latent from active tuberculosis.Microbiology spectrum · 2026Article
- Neutrophil extracellular traps: the hidden driver of gastrointestinal cancer and emerging therapeutic strategies.Frontiers in immunology · 2026Review
- The role of NETosis in breast cancer: mechanistic insights and biomarker potential.Breast cancer research : BCR · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Diagnostic delays in tuberculosis (TB) threaten global control efforts, necessitating early detection of active TB (ATB). This study explores neutrophil extracellular traps (NETs) as key mediators of TB immunopathology to identify NETs-related biomarkers for differentiating ATB from latent TB infection (LTBI). Methods: We analyzed transcriptomic datasets (GSE19491, GSE62525, GSE28623) using differential expression analysis (|log, FC| ≥ 0.585, adj. p < 0.05), immune cell profiling (CIBERSORT), and machine learning (SVM-RFE, LASSO, Random Forest). Regulatory networks and drug-target interactions were predicted using NetworkAnalyst, Tarbase, and DGIdb. Results: We identified three hub genes (CD274, IRF1, HPSE) showing high diagnostic accuracy (AUC 0.865-0.98, sensitivity/specificity >80%) validated through ROC/precision-recall curves. IRF1 and HPSE correlated with neutrophil infiltration (r > 0.6, p < 0.001), suggesting roles in NETosis. FOXC1, GATA2, and hsa-miR-106a-5p emerged as core regulators, and 46 candidate drugs (e.g., PD-1 inhibitors, heparin) were prioritized for repurposing. Discussion: CD274, IRF1, and HPSE represent promising NETs-derived diagnostic biomarkers for ATB. Their dual roles in neutrophil-mediated immunity highlight therapeutic potential, though drug predictions require preclinical validation. Future studies should leverage spatial omics and CRISPR screening to elucidate mechanistic pathways.
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