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脓毒症肺损伤中 ferroptosis 相关关键基因及治疗性化合物的生物信息学鉴定与验证

Bioinformatics Identification and Validation of Ferroptosis-Related Key Genes and Therapeutic Compounds in Septic Lung Injury.

作者信息

Li Zhile, Gan Han, Li Siyuan, Xue Yuchen, Luo Kai, Huang Kai, Zhang Yunqian, Wang Yan, Jiang Lai, Zhang Hui

机构信息

Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.

出版信息

J Inflamm Res. 2024 Nov 21;17:9215-9230. doi: 10.2147/JIR.S476522. eCollection 2024.

DOI:10.2147/JIR.S476522
PMID:39600675
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11589777/
Abstract

BACKGROUND

Septic lung injury (SLI) is a severe condition with high mortality, and ferroptosis, a form of programmed cell death, is implicated in its pathogenesis. However, the explicit mechanisms underlying this condition remain unclear. This study aimed to elucidate and validate key ferroptosis-related genes involved in the pathogenesis of SLI through bioinformatics analysis and experimental validation.

METHODS

Microarray data related to SLI from the GSE130936 dataset were downloaded from the Gene Expression Omnibus (GEO) database. These data were then intersected with the FerrDb database to obtain ferroptosis-related differentially expressed genes (DEGs). Protein-protein interaction (PPI) networks and functional enrichment analysis were employed to identify key ferroptosis-related DEGs. The Connectivity Map (c-MAP) tool was used to search for potential compounds or drugs that may inhibit ferroptosis-related DEGs. The transcriptional levels of the key genes and potential therapeutic compounds were verified in an LPS-induced mouse model of lung injury. The expression of these key genes was further verified using the GSE60088 and GSE137342 datasets.

RESULTS

38 ferroptosis-related DEGs were identified between the septic and control mice. PPI network analysis revealed four modules, the most significant of which included eight ferroptosis-related DEGs. Functional enrichment analysis showed that these genes were enriched in the HIF-1 signaling pathway, including IL-6 (Interleukin-6), TIMP1 (Tissue Inhibitor of Metalloproteinase 1), HIF-1α (Hypoxia-Inducible Factor-1α), and HMOX1 (Heme Oxygenase-1). Phloretin, a natural compound, was identified as a potential inhibitor of these genes. Treatment with phloretin significantly reduced the expression of these genes ( < 0.05), mitigated lung injury, improved inflammatory profiles by approximately 50%, and ferroptosis profiles by nearly 30% in the SLI models.

CONCLUSION

This study elucidates the significant role of ferroptosis in SLI and identifies phloretin as a potential therapeutic agent. However, further research, particularly involving human clinical trials, is necessary to validate these findings for clinical use.

摘要

背景

脓毒症肺损伤(SLI)是一种死亡率很高的严重病症,铁死亡作为一种程序性细胞死亡形式,参与其发病机制。然而,该病症背后的具体机制仍不清楚。本研究旨在通过生物信息学分析和实验验证,阐明并验证参与SLI发病机制的关键铁死亡相关基因。

方法

从基因表达综合数据库(GEO)下载GSE130936数据集中与SLI相关的微阵列数据。然后将这些数据与FerrDb数据库进行交叉分析,以获得铁死亡相关差异表达基因(DEG)。利用蛋白质-蛋白质相互作用(PPI)网络和功能富集分析来识别关键的铁死亡相关DEG。使用连通性图谱(c-MAP)工具搜索可能抑制铁死亡相关DEG的潜在化合物或药物。在脂多糖诱导的小鼠肺损伤模型中验证关键基因和潜在治疗化合物的转录水平。使用GSE60088和GSE137342数据集进一步验证这些关键基因的表达。

结果

在脓毒症小鼠和对照小鼠之间鉴定出38个铁死亡相关DEG。PPI网络分析揭示了四个模块,其中最显著的模块包括八个铁死亡相关DEG。功能富集分析表明,这些基因在HIF-1信号通路中富集,包括白细胞介素-6(IL-6)、金属蛋白酶组织抑制剂1(TIMP1)、缺氧诱导因子-1α(HIF-1α)和血红素加氧酶-1(HMOX1)。根皮素作为一种天然化合物,被确定为这些基因的潜在抑制剂。在SLI模型中,用根皮素治疗可显著降低这些基因的表达(<0.05),减轻肺损伤,使炎症指标改善约50%,铁死亡指标改善近30%。

结论

本研究阐明了铁死亡在SLI中的重要作用,并确定根皮素为一种潜在的治疗药物。然而,需要进一步研究,特别是涉及人类临床试验,以验证这些发现用于临床治疗的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee8/11589777/2771485e29d8/JIR-17-9215-g0007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee8/11589777/2771485e29d8/JIR-17-9215-g0007.jpg
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