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大鼠背根神经节中用于神经性疼痛的新型坏死性凋亡相关特征构建

Construction of a Novel Necroptosis-Related Signature in Rat DRG for Neuropathic Pain.

作者信息

Liu Yang, Hao Shikang, Hao Hongyu, Zheng Guona, Bing Jie, Kang Lin, Li Jia, Zhao Huanfen, Hao Han

机构信息

Department of Pathology, Hebei General Hospital, Shijiazhuang, People's Republic of China.

The First Clinical Medical School, Shanxi Medical University, Taiyuan, People's Republic of China.

出版信息

J Inflamm Res. 2025 Jan 6;18:147-165. doi: 10.2147/JIR.S494286. eCollection 2025.

Abstract

BACKGROUND

Recent studies have shown necroptosis may play a role in the development of inflammation-associated pain. However, research on the correlation between necroptosis-related genes and neuropathic pain in the dorsal root ganglia (DRG) is limited. This study aims to identify a gene signature related to necroptosis in DRG that can predict neuropathic pain.

METHODS

The mRNA expression profiles associated with neuropathic pain (GSE24982 and GSE30691) were acquired from the Gene Expression Omnibus (GEO) database. The Least Absolute Shrinkage and Selection Operator (Lasso) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) regressions were performed in GSE24982 database to constructed the necroptosis-related diferentially expressed genes (NRDEGs) signature related to neuropathic pain. Nomogram, Receiver Operating Characteristic (ROC), GSE30691 database analysis and basic experiments were used to verify the accuracy of the signature. Go and KEGG analysis, interaction network and immune infiltration were used to analyze the biological function of the signature.

RESULTS

A predictive signature targeting rat DRG for neuropathic pain through a variety of methods to verify the accuracy was developed based on 3 NRDEGs (TLR4, CAPN2, RIPK3). Significantly enriched KEGG and GO pathways, drug target prediction and non-coding RNAs related to the signature holded promise for advancing our understanding of potential avenues for treatment and the mechanisms underlying neuropathic pain. Immune infiltration analysis revealed which types of immune cells related to the NRDEGs signature played an important role in the occurrence and development of neuropathic pain. Basic experiments provided crucial evidence that the 3 NRDEGs in DRG served as important regulators of neuropathic pain.

CONCLUSION

The prediction signature based on 3 key NRDEGs showed promise in predicting the presence of neuropathic pain, which may open up new avenues for the development of novel therapies for neuropathic pain.

摘要

背景

近期研究表明,坏死性凋亡可能在炎症相关性疼痛的发生发展中起作用。然而,关于背根神经节(DRG)中坏死性凋亡相关基因与神经性疼痛之间相关性的研究有限。本研究旨在确定DRG中与坏死性凋亡相关的基因特征,以预测神经性疼痛。

方法

从基因表达综合数据库(GEO)获取与神经性疼痛相关的mRNA表达谱(GSE24982和GSE30691)。在GSE24982数据库中进行最小绝对收缩和选择算子(Lasso)及支持向量机递归特征消除(SVM-RFE)回归分析,以构建与神经性疼痛相关的坏死性凋亡差异表达基因(NRDEGs)特征。使用列线图、受试者工作特征曲线(ROC)、GSE30691数据库分析及基础实验来验证该特征的准确性。运用基因本体论(Go)和京都基因与基因组百科全书(KEGG)分析、相互作用网络及免疫浸润分析该特征的生物学功能。

结果

基于3个NRDEGs(TLR4、CAPN2、RIPK3)开发了一种通过多种方法验证准确性的针对大鼠DRG神经性疼痛的预测特征。KEGG和Go通路显著富集,与该特征相关的药物靶点预测及非编码RNA为深入了解潜在治疗途径和神经性疼痛的潜在机制提供了希望。免疫浸润分析揭示了与NRDEGs特征相关的免疫细胞类型在神经性疼痛的发生发展中起重要作用。基础实验提供了关键证据,证明DRG中的3个NRDEGs是神经性疼痛的重要调节因子。

结论

基于3个关键NRDEGs的预测特征在预测神经性疼痛方面显示出前景,这可能为开发神经性疼痛新疗法开辟新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9352/11720641/5bd8f0eded96/JIR-18-147-g0001.jpg

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