Related Experiment Video
Updated: May 16, 2025
Evaluation of a Reliable Biomarker in a Cecal Ligation and Puncture-Induced Mouse Model of Sepsis
Published on: December 9, 2022
Integrated bioinformatics and experiment validation reveal cuproptosis-related biomarkers and therapeutic targets in
Xuemei Shi1, Zhonghan Yan1, Ruilin Ding2
1Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, 646000, China.
Background:
Sepsis-induced myocardial dysfunction (SIMD) is a serious sepsis complication with high mortality, yet current diagnostic and therapeutic approaches remain limited. The lack of early, specific biomarkers and effective treatments necessitates exploration of novel mechanisms. Recently, cuproptosis has been implicated in various diseases, but its role in SIMD is unclear. This study aimed to identify cuproptosis-related biomarkers and potential therapeutic agents, supported by animal model validation.
Methods:
Four GEO datasets (GSE79962, GSE267388, GSE229925, GSE229298) were analyzed using Limma and WGCNA to identify overlapping genes from differentially expressed genes (DEGs), cuproptosis-related DEGs (DE-CRGs), and module-associated genes. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed to assess biological functions and immune cell infiltration, respectively. ceRNA and transcription factor networks were constructed to explore gene regulatory mechanisms, while consensus clustering was employed to define cuproptosis-related subtypes. Diagnostic genes were selected through SVM-RFE, LASSO, and random forest models. Additionally, potential gene-targeting agents were predicted using drug-gene interaction analysis. The findings were validated in SIMD animal models through qPCR and immunohistochemical analysis to confirm gene expression.
Results:
PDHB and DLAT emerged as key cuproptosis-related biomarkers. GSEA indicated upregulation of oxidative phosphorylation and downregulation of chemokine signaling. ssGSEA revealed negative correlations with several immune cell types. A ceRNA network (51 nodes, 56 edges) was constructed. Machine learning identified PDHB, NDUFA9, and TIMMDC1 as diagnostic genes, with PDHB showing high accuracy (AUC = 0.995 in GSE79962; AUC = 0.960, 0.864, and 0.984 in external datasets). Using the DSigDB database, we predicted six drugs that exhibit significant binding activity with PDHB. qPCR and immunohistochemistry confirmed reduced PDHB and DLAT expression in SIMD animal models.
Conclusion:
This study identifies PDHB and DLAT as cuproptosis-related biomarkers, addressing the diagnostic and therapeutic gaps in SIMD by unveiling novel molecular insights for early intervention and targeted treatment.
Clinical Trial Number:
Not applicable.
More Related Videos
Related Concept Videos
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...