Cuproptosis-related Gene Signatures and Immunological Characterization in Sepsis-associated Acute Lung Injury

Abstract

Background: Sepsis is a frequent cause of acute lung injury (ALI), characterized by immune dysregulation and a high mortality rate. The role of cuproptosis, a recently discovered cell death mechanism, in sepsis-associated ALI is still unclear. The study aimed to investigate the regulatory mechanisms and immune characteristics associated with cuproptosis in sepsisassociated ALI, with implications for novel diagnostic and therapeutic approaches. Methods: Data from the GEO database was utilized to conduct a comprehensive analysis of the cuproptosis-related genes (CRGs) in sepsis-associated ALI. Gene enrichment analysis, WGCNA, CIBERSORT algorithm, and consensus clustering were employed to investigate the associations between CRGs and immune cells. A predictive model for sepsis-associated ALI was developed based on key CRGs, and its diagnostic accuracy was assessed. Finally, qPCR was employed to validate alterations in the expression of CRGs in the sepsis-associated ALI cellular model. Results: A total of 14 CRGs were identified in sepsis-associated ALI. Strong correlations between the CRGs and immune cells were observed, and two different CRG subtypes were identified. The expression of immune-related factors in both the CRG and gene clusters exhibited similarities, suggesting a connection between the subgroups and immune cells. The prediction model effectively forecasted the incidence of sepsis-associated ALI based on the expression of CRGs. Finally, qPCR analysis confirmed that the expressions of CRGs in the sepsis-associated ALI cell model closely matched those identified through bioinformatic analyses. Conclusion: The study comprehensively evaluated the complex relationship between cuproptosis and sepsis-associated ALI. CRGs were found to be significantly associated with the occurrence, immune characteristics, and biological processes of sepsis-associated ALI. These findings provide valuable new insights into the mechanisms underlying sepsis-associated ALI. result: In total, 14 CRGs were identified in sepsis-associated ALI with healthy controls. Strong correlations between the CRGs and immune cells were observed and two different CRG subtypes were identified. The expression of immune-related factors in the CRG and gene clusters were similar, indicating an association between the subgroups and immune cell. The prediction model was effective in predicting the incidence of sepsis-associated ALI through the expression of CRGs. Real-time PCR analysis showed that the expression of CRGs in the sepsis-associated ALI cell model were similar to those from bioinformatic analyses.