{"title":"NEAT1/miR-124-3p/CCL2轴在慢性肾脏疾病进展中的作用：综合生物信息学分析和实验验证","authors":"Guanting Chen, Linqi Zhang, Yaoxian Wang, Jianfeng Wang, Kang Yang, Xixi Wang, Xu Chen","doi":"10.1080/17501911.2025.2548762","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Chronickidney disease (CKD) is a major global health burden lacking effectivetherapies. Renal interstitial fibrosis (RIF) is a key pathological driver ofCKD progression. This study aimed to identify novel diagnostic biomarkers and therapeutictargets.</p><p><strong>Research design and methods: </strong>Weanalyzed the GEO dataset GSE137570 to identify differentially expressed genes(DEGs). Protein-protein interaction (PPI) networks were constructed to screen HubGenes. A competing endogenous RNA (ceRNA) network was predicted. Validationincluded single-cell sequencing, in vitro epithelial-mesenchymal transition(EMT) models using Transforming growth factor-β 1 (TGF-β1)-treated TCMK1 cells,clinical samples (64 CKD patients, 20 healthy controls), and dual-luciferasereporter assays (DLRA).</p><p><strong>Results: </strong>FiveHub Genes (EGF, VCAN, CXCL1, MMP7, CCL2) were identified, with CCL2 being themost central. Enrichment analyses linked them to immune/inflammatory responses.DLRA confirmed specific targeting between miR-124-3p and both NEAT1 and CCL2,supporting the NEAT1/miR-124-3p/CCL2 axis. Clinically, serum CCL2 increasedwhile miR-124-3p and NEAT1 decreased with CKD progression; all three showedgood diagnostic accuracy for staging.</p><p><strong>Conclusions: </strong>EGF,VCAN, CXCL1, MMP7, and particularly CCL2 are potential CKDbiomarkers/therapeutic targets. The NEAT1/miR-124-3p/CCL2 axis is a keyregulatory pathway in CKD. Key limitations include the moderate sample sizes inbioinformatics and clinical cohorts.</p>","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"935-952"},"PeriodicalIF":2.6000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12490396/pdf/","citationCount":"0","resultStr":"{\"title\":\"The NEAT1/miR-124-3p/CCL2 axis in chronic kidney disease progression: integrated bioinformatics analysis and experimental validation.\",\"authors\":\"Guanting Chen, Linqi Zhang, Yaoxian Wang, Jianfeng Wang, Kang Yang, Xixi Wang, Xu Chen\",\"doi\":\"10.1080/17501911.2025.2548762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Chronickidney disease (CKD) is a major global health burden lacking effectivetherapies. Renal interstitial fibrosis (RIF) is a key pathological driver ofCKD progression. This study aimed to identify novel diagnostic biomarkers and therapeutictargets.</p><p><strong>Research design and methods: </strong>Weanalyzed the GEO dataset GSE137570 to identify differentially expressed genes(DEGs). Protein-protein interaction (PPI) networks were constructed to screen HubGenes. A competing endogenous RNA (ceRNA) network was predicted. Validationincluded single-cell sequencing, in vitro epithelial-mesenchymal transition(EMT) models using Transforming growth factor-β 1 (TGF-β1)-treated TCMK1 cells,clinical samples (64 CKD patients, 20 healthy controls), and dual-luciferasereporter assays (DLRA).</p><p><strong>Results: </strong>FiveHub Genes (EGF, VCAN, CXCL1, MMP7, CCL2) were identified, with CCL2 being themost central. Enrichment analyses linked them to immune/inflammatory responses.DLRA confirmed specific targeting between miR-124-3p and both NEAT1 and CCL2,supporting the NEAT1/miR-124-3p/CCL2 axis. Clinically, serum CCL2 increasedwhile miR-124-3p and NEAT1 decreased with CKD progression; all three showedgood diagnostic accuracy for staging.</p><p><strong>Conclusions: </strong>EGF,VCAN, CXCL1, MMP7, and particularly CCL2 are potential CKDbiomarkers/therapeutic targets. The NEAT1/miR-124-3p/CCL2 axis is a keyregulatory pathway in CKD. Key limitations include the moderate sample sizes inbioinformatics and clinical cohorts.</p>\",\"PeriodicalId\":11959,\"journal\":{\"name\":\"Epigenomics\",\"volume\":\" \",\"pages\":\"935-952\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12490396/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epigenomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/17501911.2025.2548762\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/8/21 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epigenomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/17501911.2025.2548762","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/21 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
The NEAT1/miR-124-3p/CCL2 axis in chronic kidney disease progression: integrated bioinformatics analysis and experimental validation.
Background: Chronickidney disease (CKD) is a major global health burden lacking effectivetherapies. Renal interstitial fibrosis (RIF) is a key pathological driver ofCKD progression. This study aimed to identify novel diagnostic biomarkers and therapeutictargets.
Research design and methods: Weanalyzed the GEO dataset GSE137570 to identify differentially expressed genes(DEGs). Protein-protein interaction (PPI) networks were constructed to screen HubGenes. A competing endogenous RNA (ceRNA) network was predicted. Validationincluded single-cell sequencing, in vitro epithelial-mesenchymal transition(EMT) models using Transforming growth factor-β 1 (TGF-β1)-treated TCMK1 cells,clinical samples (64 CKD patients, 20 healthy controls), and dual-luciferasereporter assays (DLRA).
Results: FiveHub Genes (EGF, VCAN, CXCL1, MMP7, CCL2) were identified, with CCL2 being themost central. Enrichment analyses linked them to immune/inflammatory responses.DLRA confirmed specific targeting between miR-124-3p and both NEAT1 and CCL2,supporting the NEAT1/miR-124-3p/CCL2 axis. Clinically, serum CCL2 increasedwhile miR-124-3p and NEAT1 decreased with CKD progression; all three showedgood diagnostic accuracy for staging.
Conclusions: EGF,VCAN, CXCL1, MMP7, and particularly CCL2 are potential CKDbiomarkers/therapeutic targets. The NEAT1/miR-124-3p/CCL2 axis is a keyregulatory pathway in CKD. Key limitations include the moderate sample sizes inbioinformatics and clinical cohorts.
期刊介绍：
Epigenomics provides the forum to address the rapidly progressing research developments in this ever-expanding field; to report on the major challenges ahead and critical advances that are propelling the science forward. The journal delivers this information in concise, at-a-glance article formats – invaluable to a time constrained community.
Substantial developments in our current knowledge and understanding of genomics and epigenetics are constantly being made, yet this field is still in its infancy. Epigenomics provides a critical overview of the latest and most significant advances as they unfold and explores their potential application in the clinical setting.
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