Gene expression analysis: Regulation of key genes associated with mycophenolate mofetil treatment of symptomatic carotid artery stenosis

Jin,Feng; Wang,Kai; Sun,Xiaochuan; Zhang,Zhanpu; Han,Ping

doi:10.3892/mmr.2017.7532

Gene expression analysis: Regulation of key genes associated with mycophenolate mofetil treatment of symptomatic carotid artery stenosis

Authors:
- Feng Jin
- Kai Wang
- Xiaochuan Sun
- Zhanpu Zhang
- Ping Han
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Affiliations: Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China, Department of Neurosurgery, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia 010050, P.R. China, Department of Neurosurgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 630014, P.R. China
Published online on: September 20, 2017 https://doi.org/10.3892/mmr.2017.7532
Pages: 7450-7458
Copyright: © Jin 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 analyzed gene expression arrays to identify differentially-expressed genes (DEGs) between mycophenolate mofetil (MMF)‑treated and placebo‑treated patients with symptomatic carotid artery stenosis (SCAS). In addition, the key genes involved in the pharmacology of MMF treatment in patients with SCAS were identified. The gene expression dataset was obtained from a Gene Expression Omnibus database, which included 9 MMF‑treated and 11 placebo‑treated samples. The DEGs were identified between MMF and placebo groups using R software. Furthermore, a protein‑protein interaction (PPI) network of the identified DEGS was constructed. The Database for Annotation, Visualization and Integrated Discovery was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the 19 most significant DEGs. A total of 210 DEGs between the MMF and placebo groups were screened and their PPI was constructed. GO function analysis revealed that the 19 DEGs were predominantly involved in the tyrosine phosphorylation of signal transducer and activator of transcription‑5 protein, which is closely associated with the activation of T cells. The KEGG pathway analysis suggested that the main metabolic pathways of the 19 DEGs were associated with the pharmacological functioning of MMF in activated T cells. In conclusion, the present study identified numerous key DEGs associated with SCAS, and the results suggested that v‑kit Hardy‑Zuckerman 4 feline sarcoma viral oncogene homolog and apelin may serve important roles in the MMF treatment of SCAS.

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