Abstract

Sepsis-induced acute respiratory distress syndrome (ARDS) poses a grave danger to life, resulting from sepsis-induced multi-organ failure. Although ferroptosis, a form of iron-dependent lipid peroxidative cell death, has been associated with sepsis-induced ARDS, the specific mechanisms are not fully understood. In this study, we utilized WGCNA, PPI, friends analysis, and six machine learning techniques (Lasso, SVM, RFB, XGBoost, AdaBoost, and LightGBM) to pinpoint STAT3 as a potential diagnostic marker. A significant increase in monocyte and neutrophil levels was observed in patients with sepsis-induced ARDS, as revealed by immune infiltration analyses, when compared to controls. Moreover, there was a positive correlation between STAT3 expression and the level of infiltration. Single-cell analysis uncovered a notable disparity in B-cell expression between sepsis and sepsis-induced ARDS. Furthermore, in vitro experiments using LPS-treated human bronchial epithelial cells (BEAS-2B) and THP1 cells demonstrated a significant increase in STAT3 phosphorylation expression. Additionally, the inhibition of STAT3 phosphorylation by Stattic effectively prevented LPS-induced ferroptosis in both BEAS-2B and THP1 cells. This indicates that the activation of STAT3 phosphorylation promotes ferroptosis in human bronchial epithelial cells in response to LPS. In summary, this research has discovered and confirmed STAT3 as a potential biomarker for the diagnosis and treatment of sepsis-induced ARDS.

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