LTF induces senescence and degeneration in the meniscus via the NF-kappa B signaling pathway: A study based on integrated bioinformatics analysis and experimental validation

作者全名："Zhang, Jun; Zhu, Jiayong; Zhao, Boming; Nie, Daibang; Wang, Wang; Qi, Yongjian; Chen, Liaobin; Li, Bin; Chen, Biao"

作者地址："[Zhang, Jun; Zhu, Jiayong; Zhao, Boming; Chen, Liaobin; Li, Bin; Chen, Biao] Wuhan Univ, Zhongnan Hosp, Dept Orthoped Surg, Div Joint Surg & Sports Med, Wuhan, Hubei, Peoples R China; [Nie, Daibang; Wang, Wang] Chongqing Med Univ, Coll Basic Med, Dept Immunol, Chongqing, Peoples R China; [Nie, Daibang; Wang, Wang] Chongqing Med Univ, Chongqing Key Lab Basic & Translat Res Tumor Immun, Chongqing, Peoples R China; [Qi, Yongjian] Wuhan Univ, Zhongnan Hosp, Dept Spine Surg & Musculoskeletal Tumor, Dept Orthoped Surg, Wuhan, Hubei, Peoples R China"

通信作者："Chen, LB; Li, B; Chen, B (通讯作者)，Wuhan Univ, Zhongnan Hosp, Dept Orthoped Surg, Div Joint Surg & Sports Med, Wuhan, Hubei, Peoples R China."

来源：FRONTIERS IN MOLECULAR BIOSCIENCES

ESI学科分类：BIOLOGY & BIOCHEMISTRY

WOS号：WOS:000982636500001

JCR分区：Q2

影响因子：3.9

年份：2023

卷号：10

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：LTF; osteoarthritis; bioinformatics; NF-kappa B; nuclear factor kappa B; meniscal senescence and degeneration

摘要："Background: The functional integrity of the meniscus continually decreases with age, leading to meniscal degeneration and gradually developing into osteoarthritis (OA). In this study, we identified diagnostic markers and potential mechanisms of action in aging-related meniscal degeneration through bioinformatics and experimental verification.Methods: Based on the GSE98918 dataset, common differentially expressed genes (co-DEGs) were screened using differential expression analysis and the WGCNA algorithm, and enrichment analyses based on Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were further performed. Next, the co-DEGs were imported into the STRING database and Cytoscape to construct a protein-protein interaction (PPI) network and further validated by three algorithms in cytoHubba, receiver operating characteristic (ROC) curve analysis and the external GSE45233 dataset. Moreover, the diagnostic marker lactotransferrin (LTF) was verified in rat models of senescence and replicative cellular senescence via RT-qPCR, WB, immunohistochemistry and immunofluorescence, and then the potential molecular mechanism was explored by loss of function and overexpression of LTF.Results: According to the analysis of the GSE98918 dataset, we identified 52 co-DEGs (42 upregulated genes and 10 downregulated genes) in the OA meniscus. LTF, screened out by Cytoscape, ROC curve analysis in the GSE98918 dataset and another external GSE45233 dataset, might have good predictive power in meniscal degeneration. Our experimental results showed that LTF expression was statistically increased in the meniscal tissue of aged rats (24 months) and senescent passage 5th (P5) meniscal cells. In P5 meniscal cells, LTF knockdown inhibited the NF-?B signaling pathway and alleviated senescence. LTF overexpression in passage 0 (P0) meniscal cells increased the expression of senescence-associated secretory phenotype (SASP) and induced senescence by activating the NF-?B signaling pathway. However, the senescence phenomenon caused by LTF overexpression could be reversed by the NF-?B inhibitor pyrrolidine dithiocarbamate (PDTC).Conclusion: For the first time, we found that increased expression of LTF was observed in the aging meniscus and could induce meniscal senescence and degeneration by activating the NF-?B signaling pathway. These results revealed that LTF could be a potential diagnostic marker and therapeutic target for age-related meniscal degeneration."

基金机构："National Natural Science Foundation of China [81871779]; Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund [znpy2019043]; Program of Excellent Doctoral (Postdoctoral) of Zhongnan Hospital of Wuhan University [ZNYB2019001]"

基金资助正文："Funding This work was supported by grants from the National Natural Science Foundation of China (No. 81871779), Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund (No. znpy2019043), and the Program of Excellent Doctoral (Postdoctoral) of Zhongnan Hospital of Wuhan University (No. ZNYB2019001)."