Ferroptosis is the well-known mechanism of septic cardiomyopathy (SCM). Bioinformatics analysis was employed to identify ferroptosis-related SCM differentially expressed genes (DEG). DEGs' functional enrichment was explored. Weighted gene co-expression network analysis (WGCNA) was employed to form gene clusters. The identified hub genes, signal transducer and activator of transcription 3 (STAT3) and myelocytomatosis (MYC) were further evaluated by generating receiver operator characteristic (ROC) curves and a nomogram prediction model. Additionally, survival rate, cardiac damage markers, and cardiac function and ferroptosis markers were evaluated in septic mouse model. STAT3 and MYC levels were measured in SCM heart tissue via immunohistochemical (IHC) staining, real-time polymerase chain reaction (qPCR) and western blot analysis. Analysis identified 225 DEGs and revealed 22 intersected genes. Of the 7 hub genes, STAT3 and MYC showed enrichment in septic heart tissue and a strong predicative ability based on AUC values. Cardiac damage, iron metabolism, and lipid peroxidation occurred in the SCM model. By experiments, STAT3 and MYC expression was increased in the SCM model. Impairment was reversed with a ferroptosis inhibitor, Fer-1. As conclusion, STAT3 and MYC are related with ferroptosis and may serve as potential SCM predictor indicators. KEY MESSAGES: Septic cardiomyopathy (SCM) often leads to high mortality in septic patients, and the diagnostic criteria still remains unclear. Ferroptosis as the pathogenic mechanism of SCM could help predict its progression and clinical outcomes. STAT3 and MYC are related with ferroptosis and may serve as potential SCM predictor biomarkers.
Keywords: Ferroptosis; MYC; Nomogram predictive model; Organ distribution; STAT3; Septic cardiomyopathy.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.