Bioinformatics analysis reveals CCR7 as a potential biomarker for predicting CKD progression
Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict...
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Published in | Medicine (Baltimore) Vol. 103; no. 30; p. e33705 |
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Main Authors | , , , , , |
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Language | English |
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Lippincott Williams & Wilkins
26.07.2024
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Abstract | Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein-protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein-protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21, have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD. |
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AbstractList | Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein–protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein–protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21 , have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD. Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein–protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein–protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21 , have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD. Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein-protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein-protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21, have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD.Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein-protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein-protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21, have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD. |
Author | Xiao, Lingfeng Huang, Xiaowen Shan, Huizhi Lai, Junju Cui, Sini Xiao, Yun |
Author_xml | – sequence: 1 givenname: Junju orcidid: 0000-0002-5972-6872 surname: Lai fullname: Lai, Junju organization: Division of Nephrology, Dongguan People's Hospital, Dongguan, China – sequence: 2 givenname: Huizhi surname: Shan fullname: Shan, Huizhi organization: Guangdong Key Laboratory of Urology, Division of Urology Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China – sequence: 3 givenname: Sini surname: Cui fullname: Cui, Sini organization: Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China – sequence: 4 givenname: Lingfeng surname: Xiao fullname: Xiao, Lingfeng organization: Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China – sequence: 5 givenname: Xiaowen surname: Huang fullname: Huang, Xiaowen organization: Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China – sequence: 6 givenname: Yun surname: Xiao fullname: Xiao, Yun organization: Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China |
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Cites_doi | 10.1111/eci.12585 10.3892/ijmm.2016.2743 10.1053/j.ajkd.2011.12.009 10.1016/j.immuni.2004.06.014 10.1073/pnas.0511200103 10.1038/75556 10.1001/jama.2014.6634 10.1038/ki.2008.661 10.1038/ki.1997.260 10.1093/nar/gkw937 10.1016/j.cytogfr.2013.03.001 10.1111/1440-1681.13371 10.1016/S0140-6736(76)91974-7 10.1681/ASN.2013070758 10.2215/CJN.00730111 10.2215/CJN.03530708 10.1016/j.vetmic.2017.03.002 10.1016/j.transproceed.2012.10.042 10.1186/1752-0509-8-S4-S11 10.1001/jama.2019.14745 10.1038/nprot.2008.211 10.1159/000313553 10.1126/sciadv.aaw5075 10.1056/NEJMoa1506362 10.1093/nar/gkv007 10.1093/nar/28.1.27 10.1038/nri.2017.52 10.1038/nrneph.2011.86 10.1016/j.immuni.2012.05.008 10.1101/gr.1239303 10.1038/nri2297 10.4110/in.2019.19.e36 10.1016/S0140-6736(12)60033-6 10.1161/JAHA.116.005281 10.1136/gutjnl-2011-301272 10.1074/jbc.273.12.7118 |
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Snippet | Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in... |
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Title | Bioinformatics analysis reveals CCR7 as a potential biomarker for predicting CKD progression |
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