C Liu1, H-D Fei, Z-Y Sun, J-W Tian. 1. Shanghai Jiao Tong University School of Medicine, Shanghai Jiaotong University Affiliated First People's Hospital, Shanghai, China. tjw609@163.com.
Abstract
OBJECTIVE: We performed a bioinformatic analysis of the microarray data on the gene expression profiles of degenerative intervertebral disc cells after exposure to tumor necrosis factor-α (TNF-α) to uncover the key genes that were differentially expressed between cells with and without exposure, and to explore the related signaling pathways and interaction networks, providing clues for future investigations on the molecular mechanisms of disc degeneration. MATERIALS AND METHODS: The microarray data for degenerative intervertebral disc cells after stimulation with TNF-α were downloaded from a public database, the GEO (Gene Expression Omnibus), in order to identify the genes that were differentially expressed between untreated degenerative disc cells and those stimulated with TNF-α, and then analyses of the gene ontology, signaling pathways and interaction networks for the differentially expressed genes were conducted using the DAVID, STRING and other online tools. RESULTS: A total of 753 differentially expressed genes were found in the degenerative annulus fibrosus disci intervertebralis cells after stimulation with TNF-α, including 458 upregulated genes and 295 downregulated genes. The Gene Ontology annotation analysis showed that these differentially expressed genes were mainly associated with the extracellular matrix, damage reactions, inflammatory reactions, and the regulation of apoptosis. A signaling pathway analysis showed that these differentially expressed genes were mainly involved in the interactions of cytokines, apoptosis, NOD-like receptors, chemokines, and other signal transduction pathways. The interaction network analysis indicated that JUN, CCL3, ANHK and other genes may play key roles in intervertebral disc degeneration. CONCLUSIONS: The bioinformatic analysis of the gene expression profiles of degenerative intervertebral disc cells stimulated with TNF-α showed that CCL3 and other genes may play a role in the development of the disc degeneration induced by inflammatory reactions. This suggests that bioinformatics methods can be used to identify potential therapeutic target genes, and to provide new insight into intervertebral disc degeneration.
OBJECTIVE: We performed a bioinformatic analysis of the microarray data on the gene expression profiles of degenerative intervertebral disc cells after exposure to tumor necrosis factor-α (TNF-α) to uncover the key genes that were differentially expressed between cells with and without exposure, and to explore the related signaling pathways and interaction networks, providing clues for future investigations on the molecular mechanisms of disc degeneration. MATERIALS AND METHODS: The microarray data for degenerative intervertebral disc cells after stimulation with TNF-α were downloaded from a public database, the GEO (Gene Expression Omnibus), in order to identify the genes that were differentially expressed between untreated degenerative disc cells and those stimulated with TNF-α, and then analyses of the gene ontology, signaling pathways and interaction networks for the differentially expressed genes were conducted using the DAVID, STRING and other online tools. RESULTS: A total of 753 differentially expressed genes were found in the degenerative annulus fibrosus disci intervertebralis cells after stimulation with TNF-α, including 458 upregulated genes and 295 downregulated genes. The Gene Ontology annotation analysis showed that these differentially expressed genes were mainly associated with the extracellular matrix, damage reactions, inflammatory reactions, and the regulation of apoptosis. A signaling pathway analysis showed that these differentially expressed genes were mainly involved in the interactions of cytokines, apoptosis, NOD-like receptors, chemokines, and other signal transduction pathways. The interaction network analysis indicated that JUN, CCL3, ANHK and other genes may play key roles in intervertebral disc degeneration. CONCLUSIONS: The bioinformatic analysis of the gene expression profiles of degenerative intervertebral disc cells stimulated with TNF-α showed that CCL3 and other genes may play a role in the development of the disc degeneration induced by inflammatory reactions. This suggests that bioinformatics methods can be used to identify potential therapeutic target genes, and to provide new insight into intervertebral disc degeneration.