Identification of STAT3 and MYC as critical ferroptosis-related biomarkers in septic cardiomyopathy: a bioinformatics and experimental study.

IF 4.8 3区 医学 Q1 GENETICS & HEREDITY Journal of Molecular Medicine-Jmm Pub Date : 2025-01-01 Epub Date: 2024-11-19 DOI:10.1007/s00109-024-02502-z
Fangyu Liu, Qian Wang, Haoran Ye, Yuan Du, Mingjiao Wang, Yuhong Guo, Shasha He
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Abstract

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.

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将 STAT3 和 MYC 鉴定为脓毒性心肌病中关键的铁变态相关生物标志物:一项生物信息学和实验研究。
铁蜕变是众所周知的脓毒性心肌病(SCM)的发病机制。通过生物信息学分析,确定了与败血病心肌病相关的铁变态反应差异表达基因(DEG)。探讨了 DEGs 的功能富集性。利用加权基因共表达网络分析(WGCNA)形成基因簇。通过生成接收操作者特征曲线(ROC)和提名图预测模型,进一步评估了已确定的枢纽基因、信号转导和转录激活因子 3(STAT3)和骨髓细胞瘤病(MYC)。此外,还对脓毒症小鼠模型的存活率、心脏损伤指标、心脏功能和铁变态指标进行了评估。通过免疫组化(IHC)染色、实时聚合酶链反应(qPCR)和免疫印迹分析测定了单核细胞增多症心脏组织中的STAT3和MYC水平。分析确定了 225 个 DEGs,并发现了 22 个交叉基因。在 7 个中心基因中,STAT3 和 MYC 在脓毒症心脏组织中显示出富集性,并且根据 AUC 值具有很强的预测能力。心脏损伤、铁代谢和脂质过氧化发生在单核细胞模型中。通过实验,STAT3 和 MYC 的表达在 SCM 模型中有所增加。铁变态反应抑制剂 Fer-1 可逆转这种损伤。总之,STAT3 和 MYC 与铁变态反应有关,可作为潜在的 SCM 预测指标。关键信息:脓毒症心肌病(SCM)通常会导致脓毒症患者的高死亡率,但其诊断标准仍不明确。作为脓毒症心肌病致病机制的铁蜕变有助于预测其进展和临床结果。STAT3 和 MYC 与铁蜕变有关,可作为潜在的 SCM 预测生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Medicine-Jmm
Journal of Molecular Medicine-Jmm 医学-医学:研究与实验
CiteScore
9.30
自引率
0.00%
发文量
100
审稿时长
1.3 months
期刊介绍: The Journal of Molecular Medicine publishes original research articles and review articles that range from basic findings in mechanisms of disease pathogenesis to therapy. The focus includes all human diseases, including but not limited to: Aging, angiogenesis, autoimmune diseases as well as other inflammatory diseases, cancer, cardiovascular diseases, development and differentiation, endocrinology, gastrointestinal diseases and hepatology, genetics and epigenetics, hematology, hypoxia research, immunology, infectious diseases, metabolic disorders, neuroscience of diseases, -omics based disease research, regenerative medicine, and stem cell research. Studies solely based on cell lines will not be considered. Studies that are based on model organisms will be considered as long as they are directly relevant to human disease.
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