中国组织工程研究

中国组织工程研究 ›› 2026, Vol. 30 ›› Issue (30): 8018-8023.doi: 10.12307/2026.403

• 组织工程相关大数据分析 Big data analysis in tissue engineering • 上一篇    

膝骨关节炎铁死亡特征基因竞争性内源RNA网络构建及免疫表现

尹逊龙，张  璇，黄嘉煜，刘  渊    

  1. 广西中医药大学，广西壮族自治区南宁市   530001
  • 收稿日期:2025-10-28 修回日期:2026-03-27 出版日期:2026-10-28 发布日期:2026-09-15
  • 通讯作者: 刘渊，博士，副教授，硕士生导师，广西中医药大学，广西壮族自治区南宁市 530001
  • 作者简介:尹逊龙，男，2000年生，山东省新泰市人，汉族，广西中医药大学在读硕士，主要从事骨伤教学方面的研究。
  • 基金资助:
    广西自然科学基金项目(2026GXNSFAA00640032)，项目负责人：刘渊；“国医大师韦贵康学术思想与临床诊疗传承发展研究中心”资助项目(2022V001)，项目负责人：刘渊；广西自然科学基金项目(2021GXNSFAA196033)，项目负责人：张璇；广西中医药大学2022年国家级大学生创新创业训练计划项目(202210600037)，项目负责人：黄嘉煜

Construction of a competitive endogenous RNA network of ferroptosis characteristic genes in knee osteoarthritis and immune expression

Yin Xunlong, Zhang Xuan, Huang Jiayu, Liu Yuan   

  1. Guangxi University of Chinese Medicine, Nanning 530001, Guangxi Zhuang Autonomous Region, China
  • Received:2025-10-28 Revised:2026-03-27 Online:2026-10-28 Published:2026-09-15
  • Contact: Liu Yuan, PhD, Associate professor, Master’s supervisor, Guangxi University of Chinese Medicine, Nanning 530001, Guangxi Zhuang Autonomous Region, China
  • About author:Yin Xunlong, MS candidate, Guangxi University of Chinese Medicine, Nanning 530001, Guangxi Zhuang Autonomous Region, China
  • Supported by:
    Natural Science Foundation of Guangxi Zhuang Autonomous Region, No. 2026GXNSFAA00640032 (to LY); “Research Center for Inheritance and Development of Academic Thoughts and Clinical Diagnosis and Treatment of National Medical Master Wei Guikang” Project, No. 2022V001 (to LY); Natural Science Foundation of Guangxi Zhuang Autonomous Region, No. 2021GXNSFAA196033 (to ZX); 2022 National Innovation and Entrepreneurship Training Program for College Students from Guangxi University of Chinese Medicine, No. 202210600037 (to HJY).

PDF

6

摘要：



文题释义：
铁死亡：是一种新型的细胞死亡方式，依赖铁离子并受小分子物质的诱导，铁死亡发生机制与细胞内脂质活性氧的生成和清除失衡有关。铁死亡诱导剂通过干扰谷胱甘肽过氧化物酶，减少细胞的抗氧化防御，导致活性氧积累，最终引发细胞死亡。 
膝骨关节炎：是一种常见的骨科疾病，主要表现为滑膜炎、软骨退化及软骨下骨损伤，典型症状包括膝关节疼痛、活动受限和晨僵，常见于老年人，尤其是女性。 

背景：铁死亡在膝骨关节炎发病中作用显著，但铁死亡的免疫特征及竞争性内源RNA网络研究不足。
目的：利用机器学习和生物信息学筛选膝骨关节炎铁死亡特征基因，分析免疫浸润特征，构建铁死亡特征基因的竞争性内源RNA网络。 
方法：从GEO数据库(GSE117999、GSE98918)获取膝骨关节炎基因表达数据，采用R语言筛选铁死亡相关差异表达基因。通过LASSO回归和SVM-RFE算法筛选疾病特征基因，受试者工作特征曲线评估诊断性能。CIBERSORT算法分析免疫浸润差异，构建竞争性内源RNA网络并验证基因功能。
结果与结论：筛选出413个显著差异表达基因(167个上调、246个下调)，基因本体、京都基因与基因组百科全书分析显示差异表达基因涉及氧化应激和细胞响应。机器学习算法确认KLF2和KDM6B为疾病特征基因，基因集富集分析显示疾病特征基因调控核糖体和自噬通路。免疫分析显示膝骨关节炎与16种免疫细胞相关，B细胞和T细胞高表达。竞争性内源RNA网络包含21个长链非编码RNA。结果表明：铁死亡相关基因通过竞争性内源RNA网络和免疫调控驱动膝骨关节炎进展；构建膝骨关节炎铁死亡特征基因竞争性内源RNA网络，筛选出KLF2和KDM6B为核心基因，揭示调控核糖体和自噬通路的机制，并确认B细胞和T细胞高表达的免疫特征；靶向XIST的RNA干扰或KLF2激活可为组织工程滑膜修复提供潜在靶点。
https://orcid.org/0000-0003-0110-1789 (尹逊龙)；https://orcid.org/0000-0002-8928-7268 (刘渊)


中国组织工程研究杂志出版内容重点：干细胞；骨髓干细胞；造血干细胞；脂肪干细胞；肿瘤干细胞；胚胎干细胞；脐带脐血干细胞；干细胞诱导；干细胞分化；组织工程

关键词: 膝骨关节炎, 生物信息学, 机器学习, 铁死亡, 竞争性内源RNA网络构建

Abstract: BACKGROUND: Ferroptosis plays a crucial role in the pathogenesis of knee osteoarthritis; however, its immune characteristics and competing endogenous RNA networks are still underexplored.
OBJECTIVE: To identify ferroptosis characteristic genes in knee osteoarthritis using machine learning and bioinformatics, characterize immune infiltration profiles, and construct a competing endogenous RNA network for these genes.
METHODS: Gene expression data for knee osteoarthritis were retrieved from the GEO database (GSE117999, GSE98918). Ferroptosis-related differentially expressed genes were identified using R. Characteristic genes were selected via Least Absolute Shrinkage and Selection Operator regression and Support Vector Machine-Recursive Feature Elimination, with diagnostic performance evaluated by Receiver Operating Characteristic curves. The CIBERSORT algorithm was used to assess immune infiltration differences, and a competing endogenous RNA network was constructed to validate gene functions.
RESULTS AND CONCLUSION: A total of 413 significantly differentially expressed genes were identified (167 upregulated and 246 downregulated). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed their involvement in oxidative stress and cellular responses. Machine learning confirmed KLF2 and KDM6B as characteristic genes, with gene set enrichment analysis indicating their regulation of ribosome and autophagy pathways. Immune infiltration analysis showed associations with 16 immune cell types, with elevated expression of B cells and T cells. The competing endogenous RNA network comprised 21 long non-coding RNAs. These findings suggest that ferroptosis-related genes drive the progression of knee osteoarthritis through competing endogenous RNA networks and immune modulation. This study constructed a ferroptosis-related competing endogenous RNA network in knee osteoarthritis, identified KLF2 and KDM6B as core genes regulating ribosome and autophagy pathways, and confirmed elevated B-cell and T-cell immune signatures. Targeting XIST via RNA interference or activating KLF2 may offer potential therapeutic strategies for synovial tissue engineering in knee osteoarthritis.

Key words: knee osteoarthritis, bioinformatics, machine learning, ferroptosis, competing endogenous network construction

中图分类号: