中国组织工程研究 ›› 2022, Vol. 26 ›› Issue (18): 2881-2887.doi: 10.12307/2022.698

• 骨科植入物相关基础实验 Basic experiments of orthopedic implant • 上一篇    下一篇

骨关节炎滑膜组织差异表达基因筛选及关键基因的验证结果

姚佳炜1,徐雄峰1,易  鹏1,邱  波2   

  1. 1武汉大学,湖北省武汉市   430000;2武汉大学人民医院骨二科,湖北省武汉市   430000
  • 收稿日期:2021-01-13 接受日期:2021-04-12 出版日期:2022-06-28 发布日期:2022-01-30
  • 通讯作者: 邱波,博士,主任医师,武汉大学人民医院骨二科,湖北省武汉市 430000
  • 作者简介:姚佳炜,男,1997年生,湖北省黄冈市人,汉族,武汉大学在读硕士。
  • 基金资助:
    国家自然科学基金(81071494),项目负责人:邱波

Screening of differential genes and validation of key genes in synovial tissue of osteoarthritis

Yao Jiawei1, Xu Xiongfeng1, Yi Peng1, Qiu Bo2   

  1. 1Wuhan University, Wuhan 430000, Hubei Province, China; 2Second Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan 430000, Hubei Province, China
  • Received:2021-01-13 Accepted:2021-04-12 Online:2022-06-28 Published:2022-01-30
  • Contact: Qiu Bo, MD, Chief physician, Second Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan 430000, Hubei Province, China
  • About author:Yao Jiawei, Master candidate, Wuhan University, Wuhan 430000, Hubei Province, China
  • Supported by:
    the National Natural Science Foundation of China, No. 81071494 (to QB)

摘要:

文题释义:
骨关节炎:是一种常见的退行性疾病,临床表现为关节疼痛、僵硬及活动受限等,特别在长时间的活动后,上述症状更为明显。好发于50岁以上的女性,此疾病不同程度影响患者的生活质量,严重者可导致残疾。目前骨关节炎除手术外尚无有效的治疗方案。
Hub基因:又称为关键基因,是指在某疾病或某生物学过程中发挥至关重要作用的基因,在相关通路中其他基因的调控常常受到该基因的表达影响,因此Hub基因常是某疾病重要的作用靶点和研究热点。

背景:骨关节炎的发生与多种危险因素相关,目前除手术治疗外尚无有效的治疗方案,与骨关节炎相关的调控基因参与骨关节炎的发生与发展,而骨关节炎的基因调控网络尚未建立完全。
目的:对骨关节炎基因芯片数据集进行生物信息学分析,寻找骨关节炎新型生物学标志物并对MYC和JUN基因进行实验验证。
方法:采用GEO数据库在线分析工具GEO2R对GSE55457和GSE55235芯片数据集进行差异基因的筛选,取2个数据集共同差异基因进行GO功能富集分析和通路富集分析,运用String数据库构建蛋白互作网络,并以Cytoscape 3.8.0软件得到关键基因,最后以RT-PCR及Western blot法检测骨关节炎与正常滑膜组织(滑膜标本取自于武汉大学人民医院就诊的6例关节疾病患者的滑膜标本,3例骨关节炎患者标本归为骨关节炎组,3例半月板损伤患者标本归为对照组)MYC,JUN基因的mRNA和蛋白的表达情况。
结果与结论:①GSE55457数据集上调基因704个,下调基因113个;GSE55235数据集上调基因492个,下调基因723个;两者共同上调基因89个,下调基因30个;②功能富集解析显示差异基因主要发挥应答巨噬细胞集落刺激、结合糖皮质激素受体等功能,通路富集分析显示差异基因主要参与MAPK信号通路、氨基酸代谢等途径;③根据PPI蛋白互作网络得到10个关键靶基因:MYC,JUN,MCL1,CDKN1A,HNRNPA1,VEGFA,NCOA3,ATF3,BTG2和CD44;④根据PPI互作网络图算法评分较高和蛋白互作线数量得到2个关键基因MYC和JUN;⑤RT-PCR和Western blot检测结果表明,MYC和JUN在骨关节炎组滑膜组织相比对照组的mRNA、蛋白表达水平显著增高(mRNA:MYC P=0.035 2,JUN P=0.015 6;蛋白:MYC P=0.027 2,JUN P=0.026 6);⑥结果证实,综合多种生物信息数据库和R语言分析筛选的差异基因均涉及骨关节炎的发生与发展,找出的10个关键基因均参与骨关节炎发生的关键环节,其中上调MYC与JUN可促进骨关节炎的发生,已在RT-PCR和Western blot实验结果中得到了验证。

https://orcid.org/0000-0001-5596-8877 (邱波)

中国组织工程研究杂志出版内容重点:人工关节;骨植入物;脊柱;骨折;内固定;数字化骨科;组织工程

关键词: 骨关节炎, 生物信息学, 生物学标志物, 滑膜组织, 差异基因, 关键基因, MYC, JUN

Abstract: BACKGROUND: Osteoarthritis is a common degenerative disease. Its occurrence is related to a variety of risk factors. At present, there is no effective treatment plan other than surgical treatment. The regulatory genes related to osteoarthritis are involved in the occurrence and development of osteoarthritis. However, the gene regulatory network of osteoarthritis has not been established completely.
OBJECTIVE: To carry out the bioinformatics analysis of osteoarthritis gene chip data set, so as to find new biomarkers of osteoarthritis and experimentally verify MYC and JUN genes. 
METHODS: GEO database online analysis tool GEO2R was used to screen the differential genes of GSE55457 and GSE55235 chip data. The common differential genes of the two data sets were taken for GO function enrichment analysis and pathway enrichment analysis. String database was then used to construct protein interaction network, and Cytoscape3.8.0 software was applied to obtain the key genes. Finally RT-PCR and western blot were used to detect the mRNA and protein expression of MYC and JUN genes in osteoarthritic and normal synovial tissue. Synovial specimens were taken from the synovial tissues of three patients with osteoarthritis and three patients with meniscal injuries in the Renmin Hospital of Wuhan University. 
RESULTS AND CONCLUSION: The GSE55457 dataset had 704 up-regulated genes and 113 down-regulated genes; the GSE55235 dataset had 492 up-regulated genes and 723 down-regulated genes; the two together had 89 up-regulated genes and 30 down-regulated genes. Functional enrichment showed that differential genes mainly played a role in response to macrophage colony stimulation and binding glucocorticoid receptors. Pathway enrichment analysis showed that differential genes were mainly involved in the MAPK signaling pathway and amino acid metabolism. Ten key target genes were identified based on the protein-protein interaction network, including MYC, JUN, MCL1, CDKN1A, HNRNPA1, VEGFA, NCOA3, ATF3, BTG2, and CD44. Two key genes, MYC and JUN, were obtained based on the higher score of the protein-protein interaction network graph algorithm and the number of protein interaction lines. The results of RT-PCR and western blot experiments showed that the expression of MYC and JUN at mRNA and protein levels was significantly increased in osteoarthritic synovial tissue compared with the control group (mRNA: MYC P=0.035 2, JUN P=0.015 6, protein: MYC P=0.027 2, JUN P=0.026 6). To conclude, the differential genes screened by comprehensive multiple biological information databases and R language analysis are involved in the occurrence and development of osteoarthritis. The 10 key genes identified are all involved in the key link of osteoarthritis. Up-regulation of MYC and JUN can promote the occurrence of osteoarthritis, which has been verified in the RT-PCR and western blot detections.

Key words: osteoarthritis, bioinformatics, biomarkers, synovial tissue, differential gene, key gene, MYC, JUN

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