Gene expression analysis: Regulation of key genes associated with mycophenolate mofetil treatment of symptomatic carotid artery stenosis
- Authors:
- Published online on: September 20, 2017 https://doi.org/10.3892/mmr.2017.7532
- Pages: 7450-7458
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Copyright: © Jin et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Stroke is the fourth leading cause of mortality and disability in the United States (1), and 10–20% of strokes are caused by carotid artery disease (2,3). According to epidemiological data, ~7 million adults in the United States have suffered a stroke (4), of which ischemic strokes account for ~90% (5). In addition, ~10% of ischemic strokes are caused by carotid artery stenosis (CAS) (6). CAS refers to a narrowing or constriction of the lumen of the carotid artery, usually attributed to atherosclerosis (7). The dynamic and complex process of atherosclerosis remains to be fully understood; however, it is well known that atherosclerosis is characterized by the accumulation of lipid particles and fibrous elements, associated with migration and proliferation of smooth muscle cells, in the large arteries (8–10).
Over the past decade, inflammation and the immune response in atherosclerosis have garnered attention. Previous studies have indicated that low-density lipoprotein particles and their content inside the vessel wall are susceptible to oxidation by free radicals, which may initiate the accumulation and invasion of macrophages, eventually lead to a narrowing of the major arteries (9,11).
During the progression of atherosclerosis, an imbalance between anti-inflammatory and proinflammatory cytokines serves an important role. Previous studies have attempted to identify the immune-associated genes that are involved in atherosclerosis, and achievements have been made (12,13). Superoxide dismutase, which is expressed at higher levels in regions of laminar flow, may combat oxidative stress, and hence limit vascular cell adhesion molecule-1 (VCAM-1) expression and the expression of other inflammatory pathways (12). Nitric oxide arises from endothelial nitric oxide synthase, which is known to be a shear stress-regulated gene, and can inhibit VCAM gene expression through a novel pathway involving inhibition of the activation of nuclear factor-κB, the central transcription factor in vascular inflammation (13). In addition, previous studies have reported that interleukin (IL)-35 may upregulate the expression of anti-inflammatory cytokines (14–16). Huang et al (17) investigated the effects of IL-35 on atherosclerosis and hypothesized that IL-35 could be considered a novel target for the treatment of atherosclerosis. However, the majority of genes relevant to atherosclerosis remain unknown.
Mycophenolate mofetil (MMF) is an inhibitor of the enzyme inosine monophosphate dehydroxygenase (IMPDH), and exerts a powerful cytostatic effect on activated T cells by interfering with their DNA synthesis (18). In the present study, gene expression data were obtained from a Gene Expression Omnibus (GEO) dataset uploaded by van Leuven et al (19), which included 20 carotid endarterectomy samples from patients with CAS (>70% diameter stenosis on angiography) that were randomly assigned to the following treatment groups: Treatment with 1,000 mg MMF (n=9) or placebo (n=11). Patients were treated with MMF or placebo for ≥2 weeks prior to undergoing carotid endarterectomy (CEA). van Leuven et al (19) reported that the inflammatory process in human atherosclerotic plaques could be modified by short-term treatment with MMF, as determined using mRNA expression profiling. However, this previous study did not analyze the expression data in detail, nor did it determine how MMF functioned in the treatment of symptomatic CAS (SCAS) or the molecular mechanisms of SCAS.
In the present study, the gene expression data were used to identify differentially-expressed genes (DEGs) between MMF-treated and placebo-treated groups, with the aim of identifying potential genes associated with atherosclerosis, which may be considered targets for novel gene therapy. A total of 210 DEGs between the MMF and placebo groups were identified with a threshold of P<0.05. After analyzing the regulatory effects, a regulatory network was constructed based on the DEGs. Subsequently, the data were processed by bioinformatic analyses, including hierarchical clustering, Gene Ontology (GO) terms (molecular function, biological processes and cellular components) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the 19 most significant DEGs were screened; the results of these analyses indicated that apelin (APLN) and v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT) may be valuable for characterizing the mechanism underlying immunomodulatory therapy in atherosclerosis.
Materials and methods
Datasets
The GSE13922 original mRNA expression profile used in the present study was downloaded from the National Center of Biotechnology Information GEO (http://www.ncbi.nlm.nih.gov/geo/). The platform used to analyze these data was the GPL6255 Illumina humanRef-8 v2.0 expression beadchip (Illumina, San Diego, CA, USA).
Identification of DEGs
Background correction and quartile data normalization of the downloaded data were performed using the robust multi-array average (RMA) algorithm (20). Probes without a corresponding gene symbol were filtered and the average value of gene symbols with numerous probes was calculated. The expression profile dataset, including 13,985 genes for the 20 samples, was subsequently obtained. Student's t-test was used to identify DEGs between the MMF and placebo groups using the R software LIMMA package (version 3.3.1; www.r-project.org) (21). Genes with P<0.05 were considered DEGs and genes with P<0.01 were considered the most significant DEGs between the two treatment groups. The most significant DEGs were screened between the MMF and placebo groups using principal components analysis (PCA). Cluster analysis of the most significant DEGs was applied to generate a heat map, which allowed for visualization of the differential gene expression between the two groups.
Protein-protein interaction (PPI) network construction and analysis
The PPI network was constructed from 210 DEGs using the STRING online database (http://www.string-db.org/). PPI pairs with an interaction score >0.4 were used to construct the PPI network. Subsequently, the regulatory relationships between genes were analyzed according to the topological properties of the network. With a threshold of P<0.05 and |logFC|≥0.5, the key genes in the network were further screened.
Functional analysis of various DEGs
In order to identify biological functions associated with the pathogenesis of atherosclerosis, bioinformatics analyses, including hierarchical clustering, GO (22) terms (molecular function, biological processes, cellular components) analysis and KEGG (23) pathway analysis, were conducted for the most significant DEGs, using the online Database for Annotation, Visualization and Integrated Discovery tool (24), based on the method of Expression Analysis Systemic Explorer (EASE) test (25). The enrichment threshold was an EASE score of 0.1.
Results
Data processing
A total of 13,985 genes in 20 samples were obtained after preprocessing of the expression profile. The original expression datasets were processed into expression estimates using the RMA method. As presented in the box plot in Fig. 1, the median of different samples was almost the same following normalization, which indicated a great degree of standardization.
Identification of DEGs
The DEGs between the MMF and placebo groups were identified using LIMMA package (21) in R software. A total of 210 DEGs were identified with the threshold of P<0.05, including 19 most significant DEGs with the threshold of P<0.01 (Table I). Analysis of the most significant DEGs revealed that there were 14 up- and 5 downregulated genes (Fig. 2). As presented in Fig. 3, all of the selected DEGs were screened using PCA to distinguish between the MMF and placebo groups. In the first principal components, 50.82% of variances were explained, whereas in the second principal component, 9.73% of variances were explained. In total, the resolution degree of variances was 60.55%.
PPI network construction and analysis
A total of 189 PPI pairs were obtained from the STRING database. After wiping out the pairs isolated from the major network, the PPI network composed of 172 edges and 105 nodes (Fig. 4). In the network, nodes represent genes and edges represent the interaction between genes. The PPI network of DEGs was in a state of high aggregation, which is an essential property of biological networks. With a threshold degree ≥3, a total of 43 genes were selected (Table II). As shown in Fig. 4, tumor protein p53 (degree, 33) and E1A binding protein P300 (degree, 18) had more degrees than the other DEGs.
GO functional analysis
Using a threshold of P<0.05, a total of 401 significant GO terms were enriched and the top 10 enriched terms for each category are presented in Fig. 5; only 8 terms were enriched in cellular components. The most enriched GO terms of the DEGs were mainly associated with tyrosine phosphorylation of signal transducer and activator of transcription-5 (Stat5) protein, which is closely associated with the activation of T cells.
KEGG pathway enrichment analysis
Using a threshold of P<0.05, a total of 6 significant KEGG pathways were enriched (Fig. 6). The most enriched KEGG pathways of the DEGs were mainly associated with the pharmacological functioning of MMF in activated T cells, including purine metabolism, glutathione metabolism and pyrimidine metabolism.
Discussion
The treatment of CAS includes three modalities: Medical management, carotid artery angioplasty and stenting, and CEA (26). However, there are doubts regarding the efficacy of carotid artery angioplasty and stenting, and CEA, in specific patients (27–29). Previous studies have aimed to identify novel treatments and medications for atherosclerosis. Following construction of the hypercholesterolaemic apolipoprotein E-deficient murine model, Chen et al (30) demonstrated that preimplantation factor could prevent atherosclerosis via its immunomodulatory effects without affecting serum lipids. In addition, Sun et al (31) developed trifunctional Simian virus 40 (SV40)-based nanoparticles for in vivo targeting and imaging of atherosclerotic plaques, and targeted SV40 virus-like nanoparticles were revealed to deliver a greater concentration of the anticoagulant drug Hirulog to atherosclerotic plaques.
It is well known that MMF is a T cell suppressor, which is able to reduce synthesis of guanine via IMPDH inhibition, resulting in the suppression of T cell proliferation (32). van Leuven et al (19) demonstrated that treatment with MMF was able to reduce inflammatory cell infiltration, with a concomitant decrease in proinflammatory gene expression in patients with SCAS. The present study downloaded and analyzed a GEO mRNA expression profile uploaded by van Leuven et al (19). A total of 210 DEGs were identified between MMF-treated and placebo-treated groups. Subsequently, the 19 most significant DEGs were selected to undergo GO functional analysis and KEGG pathway enrichment analysis. The results revealed that the most enriched KEGG pathway was purine metabolism, indicating that suppression of inflammatory activity served an important role in the MMF treatment of patients with SCAS. Furthermore, with a threshold of degree ≥3 and |logFC|≥0.5, three genes, APLN, creatine kinase B (CKB) and KIT, were selected as the key genes.
APLN is a peptide, which was initially identified by Tatemoto et al in 1998 (33), that functions as an endogenous ligand for the orphaned G-protein-coupled receptor (APJ) (34). Previous studies have revealed that APJ deficiency can prevent oxidative stress-associated atherosclerosis and that the APLN-APJ system is a mediator of oxidative stress in vascular tissue (33,35–37). In the present study, expression of APLN was significantly different between MMF-treated and placebo-treated groups, and APLN was a key gene in the PPI network, indicating that APLN may be a target of MMF for the treatment of SCAS. According to the results of the KEGG analysis, purine metabolism was the most enriched signaling pathway, indicating that MMF modified the atherosclerotic plaque by suppressing activated T cells. Recent studies have also reported that APLN is involved in the immune response (38,39). By analyzing the expression and function of the APLN-APJ system in tumor vasculature, Kidoya et al (38) indicated that the APLN-APJ system could induce maturation of tumor vasculature and improve the efficiency of immune therapy. The results of the GO analysis suggested that terms associated with Stat5 were the most enriched, including tyrosine phosphorylation of Stat5 protein, regulation of tyrosine phosphorylation of Stat5 protein and positive regulation of tyrosine phosphorylation of Stat5 protein (Table III). Previous studies have indicated that Stat5 has a strong association with T cells. Lindahl et al (40) provided evidence to suggest that microRNA-21 is expressed in situ in cutaneous T cell lymphomas skin lesions, as induced by IL-2 and IL-15 cytokines, and is regulated by Stat5 in malignant T cells. The APLN-APJ system is also involved in the immune response and Stat3. Han et al (41) indicated that binding of phosphorylated-Stat3 to the APLN promoter is the final step underlying proinflammatory cytokine-induced enteric APLN expression during intestinal inflammation. However, whether APLN is involved in the Stat5 signaling remains to be elucidated. It may be hypothesized that APLN affects T cells through the Stat5 signaling pathway; however, further studies are required.
Mast/stem cell growth factor receptor, also known as proto-oncogene c-Kit, tyrosine-protein kinase Kit, or cluster of differentiation 117 is a receptor tyrosine kinase protein that in humans is encoded by the KIT gene (42). The GO analysis results revealed that KIT was closely associated with tyrosine phosphorylation of Stat5 protein, thus indicating that dysregulation of Stat5 may be important in the process of SCAS.
Brain-type creatine kinase is a creatine kinase encoded by the CKB gene in humans, which is associated with creatine kinase activity and cellular monovalent inorganic anion homeostasis (43). However, to the best of our knowledge, the involvement of CKB in the process of SCAS has not yet been reported.
In conclusion, APLN and KIT may serve important roles in the MMF treatment of SCAS. The results of the present study suggested that MMF may upregulate APLN to inhibit the proliferation of T cells through the Stat5 signaling pathway. Further investigation of the function of APLN and KIT in atherosclerosis is urgently required.
Acknowledgements
The present study was supported by the Youth Innovation Fund Projects of Inner Mongolia Medical University (grant no. YKD2013QNCX023), the Health Department Medical Scientific Research Projects of the Inner Mongolia Autonomous Region (grant no. 201302089) and the Health Department Medical Scientific Research Projects of the Inner Mongolia Autonomous Region (grant no. 201302090).
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