Gene Expression Profiling of the Optic Nerve Head of Patients with Primary Open-Angle Glaucoma.
ABSTRACT: Background. The pressure-induced axonal injury of the vulnerable ONH has led many researchers to view glaucoma from the perspective of the genetic basis of the angle of the ONH. However, genetic studies on POAG from this perspective are limited. Methods. Microarray dataset GSE45570 of the ONH of healthy individuals and POAG patients were downloaded from the Gene Expression Omnibus. After screening for the DEGs using the limma package, enrichment analysis was performed using DAVID. The DEG interaction network was constructed using cancer spider at BioProfiling.de. Thereafter, DEG-related TFs were predicted using TRANSFAC, and TF-DEG regulatory networks were visualized using Cytoscape. Results. Thirty-one DEGs were identified including 11 upregulated and 20 downregulated DEGs. Thereafter, gene ontology terms of nucleosome assembly, sensory perception and cognition, and pathway of signaling by GPCR were found to be enriched among the DEGs. Furthermore, DEG interaction and TF-DEG networks were constructed. NEUROD1 was present in both the DEG network and the TF-DEG network as the node with the highest degree and was predicted as a marker gene in the ONH of patients with POAG. Conclusion. NEUROD1 may contribute greatly to the ONH of patients with POAG and was found to be involved in eye development and diseases.
Project description:Osteosarcoma (OS) is the most frequently occurring primary bone malignancy with a rapid progression and poor survival. In the present study, in order to examine the molecular mechanisms of OS, we analyzed the microarray of GSE28425. GSE28425 was downloaded from Gene Expression Omnibus, which also included the miRNA expression profile, GSE28423, and the mRNA expression profile, GSE28424. Each of the expression profiles included 19 OS cell lines and 4 normal bones. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) were screened using the limma package in Bioconductor. The DEGs associated with tumors were screened and annotated. Subsequently, the potential functions of the DEGs were analyzed by Gene Ontology (GO) and pathway enrichment analyses. Furthermore, the protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software. Furthermore, modules of the PPI network were screened using the ClusterOne plugin in Cytoscape. Additionally, the transcription factor (TF)-DEG regulatory network, DE-miRNA-DEG regulatory network and miRNA-function collaborative network were separately constructed to obtain key DEGs and DE-miRNAs. In total, 1,609 DEGs and 149 DE-miRNAs were screened. Upregulated FOS-like antigen 1 (FOSL1) also had the function of an oncogene. MAD2 mitotic arrest deficient-like 1 (MAD2L1; degree, 65) and aurora kinase A (AURKA; degree, 64) had higher degrees in the PPI network of the DEGs. In the TF-DEG regulatory network, the TF, signal transducer and activator of transcription 3 (STAT3) targeted the most DEGs. Moreover, in the DE-miRNA-DEG regulatory network, downregulated miR?1 targeted many DEGs and estrogen receptor 1 (ESR1) was targeted by several highly expressed miRNAs. Moreover, in the miRNA-function collaborative networks of upregulated miRNAs, miR?128 targeted myeloid dendritic associated functions. On the whole, our data indicate that MAD2L1, AURKA, STAT3, ESR1, FOSL1, miR?1 and miR?128 may play a role in the development and/or progressio of OS.
Project description:As an invasive malignant tumor, osteosarcoma (OS) has high mortality. Parathyroid hormone receptor 1 (PTHR1) contributes to maintaining proliferation and undifferentiated state of OS. This study is designed to reveal the action mechanisms of PTHR1 in OS.Microarray dataset GSE46861, which included six PTHR1 knockdown OS samples and six control OS samples, was obtained from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified and then performed with enrichment analysis separately using the limma package and DAVID online tool. Then, protein-protein interaction (PPI) network and module analyses were conducted using Cytoscape software. Using the WebGestalt tool, microRNAs (miRNAs) were predicted for the DEGs involved in the PPI network. Following this, transcription factors (TFs) were predicted and an integrated network was constructed by Cytoscape software.There were 871 DEGs in the PTHR1 knockdown OS samples compared with the control OS samples. Besides, upregulated ZFPM2 was involved in the miRNA-DEG regulatory network. Moreover, TF LEF1 was predicted for the miRNA-DEG regulatory network of the downregulated genes. In addition, LEF1, NR4A2, HAS2, and RHOC had higher degrees in the integrated network.ZFPM2, LEF1, NR4A2, HAS2, and RHOC might be potential targets of PTHR1 in OS.
Project description:Sepsis is a type of systemic inflammatory response caused by infection. The present study aimed to identify novel targets for the treatment of sepsis. We conducted bioinformatic analysis of the microarray Gene Expression Omnibus dataset GSE12624, which includes data on 34 patients with sepsis and 36 healthy individuals without sepsis. Differentially expressed genes (DEGs) in sepsis patients were identified using Bayesian methods included in the limma package in R. Correlations among the expression values of DEGs were analyzed using the weighted gene co?expression network analysis (WGCNA) to construct a co?expression network. Subsequently, the generated co?expression network was visualized using Cytoscape 3.3 software. Additionally, a protein?protein interaction (PPI) network was constructed based on all the DEGs using STRING. Finally, the integrated regulatory network was constructed based on DEGs, microRNAs (miRNAs) and transcription factors (TFs). A total of 407 DEGs were identified in the sepsis samples, including 227 upregulated DEGs and 180 downregulated DEGs. WGCNA grouped the DEGs into 13 co?expressed modules. Additionally, MAP3K8 and RPS6KA5 in the MEyellow module were enriched in the MAPK and TNF signaling pathways. In addition, the PPI network comprised 48 nodes and 112 edges, which included the pairs MAP3K8?RPS6KA5, MAP3K8?IL10, RPS6KA5?EXOSC4 and EXOSC4?EXOSC5. Lastly, the TF?miRNA?target DEG regulatory network was constructed based on eight TFs (NF??B), seven miRNAs (miR152, miR?148A/B), and 52 TF?miRNA?target gene triplets (17 upregulated genes, including MAP3K8, and 10 downregulated genes, including RPS6KA5). Our analysis showed that the members of the miR?148 family (miR?148A/B and miR?152) are candidate biomarkers for sepsis.
Project description:PURPOSE:To assess optic nerve head (ONH) and peripapillary microvasculature in primary open-angle glaucoma (POAG) of mild to moderate severity using swept-source optical coherence tomography angiography (OCTA). MATERIALS AND METHODS:In a cross-sectional study, swept-source OCTA images were analyzed for 1 eye from each of 30 POAG patients with glaucomatous Humphrey visual field loss and 16 controls. The anatomic boundary of ONH was manually delineated based on Bruch's membrane opening and large vessels were removed from en face angiography images to measure vessel density (VD) and the integrated OCTA by ratio analysis signal (IOS), suggestive of flow, in the ONH and peripapillary region. POAG subgroup analysis was performed based on a history of disc hemorrhage (DH) matched by visual field mean deviation (MD). RESULTS:POAG (mean MD±SD, -3.3±3.0?dB) and control groups had similar demographic characteristics and intraocular pressure on the day of imaging. Groups did not differ in superficial ONH VD or flow indicated by IOS (P?0.28). POAG eyes showed significantly lower VD (39.4%±4.0%) and flow (38.8%±5.6%) in deep ONH, peripapillary VD (37.9%±2.9%) and flow (43.6%±4.0%) compared with control eyes (44.1%±5.1%, 44.7%±6.9%, 40.7%±1.7%, 47.8%±2.5%, respectively; P?0.007 for all). In the subgroup analysis, POAG eyes with (n=14) and without DH (n=16) had similar measured OCTA parameters (P>0.99 for all). CONCLUSIONS:The image processing methodology based on the anatomic boundary of ONH demonstrated compromised microvasculature in the deep ONH and peripapillary region in eyes with mild to moderate POAG, regardless of the history of DH.
Project description:BACKGROUND:Neonatal sepsis is an inflammatory systemic syndrome, which is a major cause of morbidity and mortality in premature infants. We analyzed the expression profile data of E-MTAB-4785 to reveal the pathogenesis of the disease. METHODS:The expression profile dataset E-MTAB-4785, which contained 17 sepsis samples and 19 normal samples, was obtained from the ArrayExpress database. The differentially expressed genes (DEGs) were analyzed by the Bayesian testing method in limma package. Based on the DAVID online tool, enrichment analysis was conducted for the DEGs. Using STRING database and Cytoscape software, protein-protein interaction (PPI) network and module analyses were performed. Besides, transcription factor (TF)-DEG regulatory network was also constructed by Cytoscape software. Additionally, miRNA-DEG pairs were searched using miR2Disease and miRWalk 2.0 databases, followed by miRNA-DEG regulatory network was visualized by Cytoscape software. RESULTS:A total of 275 DEGs were identified from the sepsis samples in comparison to normal samples. TSPO, MAPK14, and ZAP70 were the hub nodes in the PPI network. Pathway enrichment analysis indicated that CEBPB and MAPK14 were enriched in TNF signaling pathway. Moreover, CEBPB and has-miR-150 might function in neonatal sepsis separately through targeting MAPK14 and BCL11B in the regulatory networks. These genes and miRNA might be novel targets for the clinical treatment of neonatal sepsis. CONCLUSION:TSPO, ZAP70, CEBPB targeting MAPK14, has-miR-150 targeting BCL11B might affect the pathogenesis of neonatal sepsis. However, their roles in neonatal sepsis still needed to be confirmed by further experimental researches.
Project description:This study was designed to explore the effects of tobacco smoke on gene expression through bioinformatics analyses. Gene expression profile GSE17913 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) in buccal mucosa tissues between 39 active smokers and 40 never smokers were identified. Gene Ontology Specifically, the DEG distribution in the pathway of Metabolism of xenobiotics by cytochrome P450 was shown in Fig 2[corrected] were performed, followed by protein-protein interaction (PPI) network, transcriptional regulatory network as well as miRNA-target regulatory network construction. In total, 88 up-regulated DEGs and 106 down-regulated DEGs were identified. Among these DEGs, cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) and CYP1B1 were enriched in the Metabolism of xenobiotics by cytochrome P450 pathway. In the PPI network, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), and CYP1A1 were hub genes. In the transcriptional regulatory network, transcription factors of MYC associated factor X (MAX) and upstream transcription factor 1 (USF1) regulated many overlapped DEGs. In addition, protein tyrosine phosphatase, receptor type, D (PTPRD) was regulated by multiple miRNAs in the miRNA-DEG regulatory network. CYP1A1, CYP1B1, YWHAZ and PTPRD, and TF of MAX and USF1 may have the potential to be used as biomarkers and therapeutic targets in tobacco smoke-related pathological changes.
Project description:Sepsis is a type of systemic inflammatory response syndrome caused by infection. The present study aimed to examine key genes and microRNAs (miRNAs) involved in the pathogenesis of sepsis. The GSE13205 microarray dataset, downloaded from the Gene Expression Omnibus was analyzed using bioinformatics tools, and included muscle biopsy specimens of 13 patients with sepsis and eight healthy controls. The differentially expressed genes (DEGs) in samples from patients with sepsis were identified using the Linear Models for Microarray package in R language. Using the Database for Annotation, Visualization and Integration Discovery tool, functional and pathway enrichment analyses were performed to examine the potential functions of the DEGs. The protein?protein interaction (PPI) network was constructed with the DEGs using the Search Tool for the Retrieval of Interacting Genes, and the network topology was analyzed using CytoNCA. Subsequently, MCODE in Cytoscape was used to identify modules in the PPI network. Finally, the integrated regulatory network was constructed based on the DEGs, miRNAs and transcription factors (TFs). A total of 259 upregulated DEGs (MYC and BYSL) and 204 downregulated DEGs were identified in the patients with sepsis. NOP14, NOP2, AATF, GTPBP4, BYSL and TRMT6 were key genes in the MCODE module. In the integrated DEG?miRNA?TF regulatory network, hsa?miR?150 (target gene MYLK3) and 21 TFs, comprising 14 upregulated DEGs (including MYC) and seven downregulated DEGs, were identified. The results suggested that NOP14, NOP2, AATF, GTPBP4, BYSL, MYC, MYLK3 and miR?150 may be involved in the pathogenesis of sepsis.
Project description:Epidemiological and genetic studies indicate that ethnic/genetic background plays an important role in susceptibility to primary open angle glaucoma (POAG). POAG is more prevalent among the African-descent population compared to the Caucasian population. Damage in POAG occurs at the level of the optic nerve head (ONH) and is mediated by astrocytes. Here we investigated differences in gene expression in primary cultures of ONH astrocytes obtained from age-matched normal and glaucomatous donors of Caucasian American (CA) and African American (AA) populations using oligonucleotide microarrays.Gene expression data were obtained from cultured astrocytes representing 12 normal CA and 12 normal AA eyes, 6 AA eyes with POAG and 8 CA eyes with POAG. Data were normalized and significant differential gene expression levels detected by using empirical Bayesian shrinkage moderated t-statistics. Gene Ontology analysis and networks of interacting proteins were constructed using the BioGRID database. Network maps included regulation of myosin, actin, and protein trafficking. Real-time RT-PCR, western blots, ELISA, and functional assays validated genes in the networks.Cultured AA and CA glaucomatous astrocytes retain differential expression of genes that promote cell motility and migration, regulate cell adhesion, and are associated with structural tissue changes that collectively contribute to neural degeneration. Key upregulated genes include those encoding myosin light chain kinase (MYLK), transforming growth factor-beta receptor 2 (TGFBR2), rho-family GTPase-2 (RAC2), and versican (VCAN). These genes along with other differentially expressed components of integrated networks may reflect functional susceptibility to chronic elevated intraocular pressure that is enhanced in the optic nerve head of African Americans.
Project description:Heart failure (HF) is a global pandemic cardiovascular disease with increasing prevalence, but the pathogenesis remains to be elucidated. The present study aimed to investigate the underlying mechanism in heart failure (HF) using bioinformatics and experimental validation. A HF-associated dataset GSE84796 was downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) were screened for using Bayes method in the Limma package. Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to perform pathway enrichment analysis of these DEGs using The Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of DEG-encoded proteins was subsequently constructed using the Search tool for the Retrieval of Interacting Genes/Proteins, and a transcription factor (TF)/miRNA-target network was constructed according to the WEB-based Gene SeT AnaLysis Tookit. The expression levels of microRNA (miRNA/miR)-155, G-protein coupled receptor 18 (GRP18) and E26 transformation-specific transcription factor 2 (ETS2) were analyzed in clinical HF samples, and functional validations were performed in H9c2 (2-1) cells. A total of 419 DEGs were identified, including 366 upregulated genes and 53 downregulated genes. The upregulated DEGs were significantly enriched in the pathways of 'cytokine-cytokine receptor interaction', 'natural killer cell mediated cytotoxicity' and 'primary immunodeficiency'. A total of two functional modules were identified in the PPI network: Module A was enriched in 3 KEGG pathways and module B was enriched in 15 KEGG pathways. Furthermore, a total of three miRNAs and eight TFs were identified in the TF/miRNA-target network. Specifically, GPR18 was discovered to be targeted by both ETS2 and miR-155. Clinical validation revealed that the expression levels of miR-155 were significantly decreased in the HF samples, whereas the expression levels of ETS2 and GPR18 were significantly increased in HF samples. In conclusion, the present study suggested that GPR18 may be a target of ETS2 and miR-155, and miR-155 may regulate cell viability and apoptosis in H9c2 (2-1) cells through targeting and regulating GPR18.
Project description:The present study aimed to screen potential genes implicated in epithelial ovarian cancer (EOC) and to further understand the molecular pathogenesis of EOC. In order to do this, datasets GSE14407 (containing 12 human ovarian cancer epithelia samples and 12 normal epithelia samples) and GSE29220 (containing 11 salivary transcriptomes from ovarian cancer patients with serous papillary adenocarcinoma and 11 matched controls) were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) within these datasets were screened using the Linear Models for Microarray Data package, and potential gene functions were predicted by functional and pathway enrichment analyses. Additionally, module analysis of protein-protein interaction networks was performed using MCODE software in Cytoscape. The potential microRNAs (miRNAs/miRs) and transcription factors (TFs) regulating DEGs were also analyzed, and the integrated TF-DEG and miRNA-DEG regulatory networks were visualized with Cytoscape. In total, 31 upregulated DEGs and 64 downregulated DEGs were screened. The upregulated DEGs, such as centromere protein F (CENPF) and ubiquitin like with PHD and ring finger domains 1 (UHRF1), were significantly associated with the cell cycle and were regulated by the TF nuclear transcription factor Y (NF-Y). CENPF was modulated by miR-373, and UHRF1 was regulated by miR-146a. The downregulated DEGs, such as aldehyde dehydrogenase 1 family member A2 (ALDH1A2), were distinctly involved in the response to estrogen stimulus and modulated by tumor protein 53 (TP53); protocadherin 9 (PCDH9) was regulated by TP53, miR-92b-3p and miR-137. The DEGs, including CENPF, UHRF1, ALDH1A2 and PCDH9, and a set of gene regulators, including all NFY genes, TP53, miR-373, miR-146a, miR-92b-3p and miR-137, may be involved in the pathogenesis of EOC.