Cell death-related gene signatures as dual-function biomarkers: Early diagnosis and therapeutic targeting in Staphylococcus aureus pneumonia - Cao Qing; Wanjuan Sun; Chaomian Yang; Yien Yao; Qiong Liang; Tianxia Huang; Lu Lin (PLoS ONE, 2026)
Background Staphylococcus aureus ( S. aureus ) pneumonia constitutes a lethal respiratory infection with persistently high clinical mortality. Although programmed cell death (PCD) pathways are implicated in diverse disease processes, their mechanistic roles in S. aureus pneumonia pathogenesis, particularly as dual-purpose biomarkers for early diagnosis and therapeutic targeting remain insufficiently characterized. Methods High-throughput RNA sequencing was conducted on S. aureus challenged murine pulmonary tissues to delineate pneumonia-associated differentially expressed genes (DEGs). Through bioinformatics screening, we established a PCD -related gene signature and validated its clinical relevance via transcriptomic profiling of peripheral blood samples from confirmed S. aureus pneumonia patients. Machine learning (including LASSO regression and SVM-RFE algorithms) were employed to prioritize characteristic biomarkers, followed by construction of a risk-prediction nomogram with Receiver Operating Characteristic (ROC) curve validation. Multidimensional analyses encompassing immune cell infiltration patterns and DSigDB based drug discovery were performed, supplemented by molecular docking simulations and qPCR confirmation of core regulatory elements. Results Whole-transcriptome analysis revealed 71 PCD-related DEGs (DE-PCDs) with conserved cross-species dysregulation (19 genes in human specimens). Machine learning identified 11 hub genes modulating apoptosis, necroptosis, autophagy, and ferroptosis interconnections. A four-gene diagnostic panel (NAMPT, NFKBIA, SLC40A1, PRKCQ) demonstrated high predictive accuracy (AUC = 0.92) via nomogram modeling. Significant correlations emerged between biomarkers and neutrophil/T-cell infiltration dynamics, while computational drug screening identified 27 candidate compounds targeting these determinants. Conclusion This investigation delineates PCD-mediated regulatory networks in S. aureus pneumonia, establishing a clinically translatable biomarker panel with theranostic potential against infectious pulmonary inflammation.