Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods

Wang,Weiguo; Liu,Rongjun; Xu,Zhanwang; Niu,Xiufeng; Mao,Zhaohu; Meng,Qingxi; Cao,Xuecheng

doi:10.3892/mmr.2015.4442

Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods

Authors:
- Weiguo Wang
- Rongjun Liu
- Zhanwang Xu
- Xiufeng Niu
- Zhaohu Mao
- Qingxi Meng
- Xuecheng Cao
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Affiliations: Department of Orthopaedic Surgery, General Hospital of Jinan Military Command, Jinan, Shandong 250031, P.R. China, Department of Emergency Surgery, General Hospital of Jinan Military Command, Jinan, Shandong 250031, P.R. China, Department of Orthopedics, First Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250014, P.R. China, Department of Hepatobiliary Surgery, General Hospital of Jinan Military Command, Jinan, Shandong 250031, P.R. China, Department of Spinal Cord Injury, General Hospital of Jinan Military Command, Jinan, Shandong 250031, P.R. China
Published online on: October 14, 2015 https://doi.org/10.3892/mmr.2015.4442
Pages: 7851-7858
Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to explore the molecular mechanisms underlying the development of thoracic spinal cord injury (SCI). The gene expression profile of GSE20907, which included 12 thoracic non‑injured spinal cord control samples and 12 thoracic transected spinal cord samples at different stages of SCI, was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package in R/Bioconductor. DEG‑associated pathways were analyzed using the Kyoto encyclopedia of genes and genomes database. A protein‑protein interaction (PPI) network was constructed and transcription factors (TFs) were predicted using cytoscape. Compared with the control samples, there were 1,942, 396, 188 and 396 DEGs identified at day 3 (d3), week 1 (wk1), wk2 and month 1 (m1), respectively. Cluster analysis indicated that the DEGs at m1 were similar to those in the control group. Downregulated DEGs were enriched in nervous system disease pathways, such as Parkinson's disease. Upregulated DEGs were enriched in immune response‑associated pathways, such as Fc γ R‑mediated phagocytosis at early stages (d3 and wk1). Upregulated DEGs were enriched in pathways associated with cancer and pyrimidine metabolism at wk2 and m1, respectively. In the PPI network, nodes including RAC2, CD4, STAT3 and JUN were identified. Furthermore, ATF3, JUN and EGR1 were identified as TFs associated with SCI. In conclusion, the results of the present study showed that the number of DEGs decreased in a time‑dependent manner following SCI. OLIG1, ATF3 and JUN may represent SCI regeneration‑associated genes. Immune-associated inflammation was shown to be important in SCI, and SCI exhibits causal associations with other diseases, including cardiovascular disease and cancers. The present study provided novel insight into the molecular mechanisms of SCI regeneration, which may aid in the development of strategies to enhance recovery following SCI.

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