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Updated: Jul 26, 2026

A Proinflammatory, Degenerative Organ Culture Model to Simulate Early-Stage Intervertebral Disc Disease.
Published on: February 14, 2021
Identification of cellular senescence-related genes and immune cell infiltration characteristics in intervertebral
Muyi Wang1,2, Hao Wang1,2, Xin Wang1,2
1Department of Orthopedics, Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, Jiangsu, China.
Background:
Intervertebral disc degeneration (IDD) progression involves multiple factors, including loss of nucleus pulposus cells and extracellular matrix as the basic pathological mechanism of degeneration, and is closely related to cellular senescence and immune cell infiltration. The aim of study was to identify critical cellular senescence-related genes and immune cell infiltration characteristics in IDD.
Methods:
Four datasets, including GSE70362, GSE112216, GSE114169, and GSE150408, were downloaded from the Gene Expression Omnibus database. The senescence-related genes were acquired from the CellAge Database and intersected with differentially expressed genes (DEGs) between IDD and control samples for senescence-related DEGs (SRDEGs). Protein-protein interaction (PPI) network analysis was performed to obtain ten hub SRDEGs. A consensus cluster analysis based on these hub genes was performed to divide the patients into clusters. The functional enrichment, and immune infiltration statuses of the clusters were compared. Weighted gene co-expression network analysis was used to identified key gene modules. The overlapping genes from key modules, DEGs of clusters and hub SRDEGs were intersected to obtain potential biomarkers. To verify the expression of potential biomarkers, quantitative polymerase chain reaction (qPCR) and immunohistochemistry were performed by using human intervertebral disc tissues.
Results:
In the GSE70362 dataset, a total of 364 DEGs were identified, of which 150 were upregulated and 214 were downregulated, and 35 genes were selected as SRDEGs. PPI analysis revealed ten hub SRDEGs and consensus cluster analysis divided the patients into two clusters. Compared to Cluster 2, Cluster 1 was highly enriched in extracellular matrix organization and various metabolic process. The level of Follicular T helper cells in the Cluster 1 was significantly higher than that in the Cluster 2. IGFBP3 and NQO1 were identified as potential biomarkers. The remaining 3 datasets, and the result of qPCR and immunohistochemistry showed that the expression levels of NQO1 and IGFBP3 in the degenerated group were higher than those in the control or treatment groups.
Conclusion:
Senescence-related genes play a key role in the development and occurrence of IDD. IGFBP3 and NQO1 are strongly correlated with immune infiltration in the IDD and could become novel therapeutic targets that prevent the progression of IDD.
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