Dataset Information

Bioinformatics analysis of microarray data to explore the key genes involved in HSF4 mutation-induced cataract.

ABSTRACT: AIM:To reveal the mechanisms of heat-shock transcription factor 4 (HSF4) mutation-induced cataract. METHODS:GSE22362, including 3 HSF4-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus database. After data preprocessing, the differentially expressed genes (DEGs) were identified using the limma package. Based on Database for Annotation, Visualization and Integrated Discovery (DAVID) tool, functional and pathway enrichment analyses were performed for the DEGs. Followed by protein-protein interaction (PPI) network was constructed using STRING database and Cytoscape software. Furthermore, the validated microRNA (miRNA)-DEG pairs were obtained from miRWalk2.0 database, and then miRNA-DEG regulatory network was visualized by Cytoscape software. RESULTS:A total of 176 DEGs were identified in HSF4-null lens compared with wild-type lens. In the PPI network, FBJ osteosarcoma oncogene (FOS), early growth response 1 (EGR1) and heme oxygenase (decycling) 1 (HMOX1) had higher degrees and could interact with each other. Besides, mmu-miR-15a-5p and mmu-miR-26a-5p were among the top 10 miRNAs in the miRNA-DEG regulatory network. Additionally, mmu-miR-26a-5p could target EGR1 in the regulatory network. CONCLUSION:FOS, EGR1, HMOX1, mmu-miR-26a-5p and mmu-miR-15a-5p might function in the pathogenesis of HSF4 mutation-induced cataract.

SUBMITTER: Tian R

PROVIDER: S-EPMC6010373 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bioinformatics analysis of microarray data to explore the key genes involved in <i>HSF4</i> mutation-induced cataract.

Tian Rui R Xu Yang Y Dou Wen-Wen WW Zhang Hui H

International journal of ophthalmology 20180618 6

<h4>Aim</h4>To reveal the mechanisms of <i>heat-shock transcription factor</i> 4 (<i>HSF4</i>) mutation-induced cataract.<h4>Methods</h4>GSE22362, including 3 <i>HSF4</i>-null lens and 3 wild-type lens, was obtained from Gene Expression Omnibus database. After data preprocessing, the differentially expressed genes (DEGs) were identified using the limma package. Based on Database for Annotation, Visualization and Integrated Discovery (DAVID) tool, functional and pathway enrichment analyses were p ...[more]

PMID: 29977800

Similar Datasets

Project description:Intracranial aneurysm (IA) is a cerebrovascular disease with a high mortality rate. The pathogenesis of IA remains unclear and the treatment limited. The purpose of the present study was to identify the key genes expressed in IAs and provide the basis for further research and treatment. The raw dataset GSE75436 was downloaded from Gene Expression Omnibus, including 15 IA samples and 15 matched superficial temporal artery (STA) samples. Then, differentially expressed genes (DEGs) were identified using the limma package in R software. Hierarchical clustering analysis was performed on the DEGs using the gplot2 package in R. Database for Annotation, Visualization, and Integrated Discovery (DAVID) online tools were used to perform gene ontology (GO) functional enrichment analysis. DAVID and gene set enrichment analysis were separately used to perform the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The intersections of the two results were selected as common KEGG pathways. Protein?protein interaction (PPI) analysis among the DEGs involved in the common KEGG pathways was performed using Search Tool for the Retrieval of Interacting Genes online tools, and visualized with Cytoscape software. A total of 782 DEGs were identified, comprising 392 upregulated and 390 downregulated DEGs. Hierarchical clustering demonstrated that the DEGs could precisely distinguish the IAs from the STAs. The GO enrichment analysis demonstrated that the upregulated DEGs were mainly involved in the inflammatory response and the management of extracellular matrix, and the downregulated DEGs were mainly involved in the process of vascular smooth muscle contraction. The KEGG pathway enrichment analysis demonstrated that the common pathways were 'leishmaniasis', 'Toll?like receptor signaling pathway' and 'vascular smooth muscle contraction'. In the PPI network, tumor necrosis factor (TNF), interleukin 8 and Toll?like receptor 4 had the highest degrees; they were associated with the inflammatory response. The Toll?like receptor signaling pathway and TNF gene may serve as targets for future research and treatment.

Project description:Pancreatitis is a type of inflammation in the pancreas, which frequently occurs due to alcohol and gallstones. The present study aimed to identify pancreatitis‑associated microRNAs (miRNAs) by analyzing the microarray of GSE24279. GSE24279 was downloaded from the Gene Expression Omnibus, composed of a collective of 27 pancreatitis and 22 normal control samples. The differentially expressed miRNAs (DE‑miRNAs) in pancreatitis samples were screened using the Limma package in Bioconductor. Subsequently, target genes of the DE‑miRNAs were predicted using the miRecords and miRWalk databases. Their potential functions were analyzed by functional and pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery online tool. Finally, pancreatitis‑associated genes among the target genes identified were searched using the Comparative Toxicogenomics Database, and a regulatory network of pancreatitis‑associated genes and their target miRNAs were constructed using Cytoscape software. A total 14 upregulated and 39 downregulated miRNAs were identified in pancreatitis samples compared with control samples and 290 target genes of DE‑miRNAs were determined. Cyclin D1 (CCND1), v‑akt murine thymoma viral oncogene homolog 2 (AKT2), cyclin‑dependent kinase 6 (CDK6) and SMAD family member 2 (SMAD2) were involved in the pathway of pancreatic cancer. Among the target genes, 279 genes were pancreatitis‑associated genes, which in turn were targeted by 37 miRNAs in the regulatory network. Hsa‑miR‑15a, hsa‑miR‑16, hsa‑miR‑155, hsa‑miR‑375 and hsa‑miR‑429 in particular may be involved in pancreatitis by targeting genes in the regulatory network, including hsa‑miR‑15a→CCND1, hsa‑miR‑16→CCND1, hsa‑miR‑155→CCND1/SMAD2, hsa‑miR‑375→AKT2/CDK6 and hsa‑miR‑429→CCND1. The above miRNAs and their targets may contribute to the pathogenesis of pancreatitis; therefore, they may be potential therapeutic targets.

Project description:Hepatocellular carcinoma (HCC) is a typical inflammation-driven cancer. Chronically unresolved inflammation may remodel the immunosuppressive tumor microenvironment, which is rich in innate immune cells. The mechanisms via which HCC progresses through the evasion of the innate immune surveillance remain unclear. The present study thus aimed to identify key genes involved in HCC immunosuppression and to establish an innate immune risk signature, with the ultimate goal of obtaining new insight into effective immunotherapies. HCC and normal liver tissue mRNA expression and clinicopathological data were obtained from the Cancer Genome Atlas database. The immunosuppressive innate immune-related genes (IIRGs) in HCC were screened using integrated bioinformatics analyses. Gene expression was then validated using the Gene Expression Omnibus database and the Human Protein Atlas database, and tissues were obtained from patients with HCC who underwent surgery. In total, 3,676 genes were identified as differentially expressed mRNAs after comparing the HCC tissues with the normal liver tissues in TCGA. Gene Set Enrichment Analyses revealed 21 highly expressed IIRGs in HCC tissues. A survival analysis and Cox regression model were used to construct an innate immune risk signature, including three IIRGs: Collectin-12 (COLEC12), matrix metalloproteinase-12 (MMP12) and mucin-12 (MUC12) genes. Univariate and multivariate Cox analyses revealed that the signature of the three IIRGs was a robust independent risk factor in relation to the overall survival (OS) of patients with HCC. The expression of the three aforementioned IIRGs was confirmed through external validation. Moreover, COLEC12 and MMP12 expression significantly correlated with that of immune checkpoint molecules or immunosuppressive cytokines. The tumor immune dysfunction and exclusion tool predicted that the increased expression of the three IIRGs in patients with HCC was significantly associated with the efficacy of relatively poor immune checkpoint blockade therapy. Conclusively, a novel innate immune-related risk signature for patients with HCC was constructed and validated. This signature may be involved in immunosuppression, and may be used to predict a poor prognosis, functioning as a potential immunotherapeutic target for patients with HCC.

Project description:Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of reproductive age. MicroRNAs (miRNAs or miRs) serve important roles in the physiological and pathological process of PCOS. To identify PCOS‑associated miRNAs, the dataset GSE84376 was extracted from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE‑miRNAs) were obtained from Gene‑Cloud Biotechnology Information and potential target genes were predicted using TargetScan, DIANA‑microT‑CDS, miRDB and miRTarBase tools. Gene Ontology enrichment analysis was performed using Metascape and a protein‑protein interaction network was constructed using Cytoscape. Transcription factors were obtained from FunRich. DE‑miRNAs were verified by reverse transcription‑quantitative PCR. At the screening phase, there were seven DE‑miRNAs in the PCOS group not present in the control group. In total, 935 target genes were identified, which are involved in the development and maturation of oocytes. Mitogen‑activated protein kinase 1, phosphatase and tensin homolog, cAMP responsive element binding protein 1, signal transducer and activator of transcription 3, interferon γ, Fms‑related tyrosine kinase 1, transcription factor p65, insulin receptor substrate 1, DnaJ homolog superfamily C member 10 and casein kinase 2 α 1 were identified as the top 10 hub genes in the protein‑protein interaction network. Specificity protein 1 was the most enriched transcription factor. At the validation phase, the levels of Homo sapiens (hsa)‑miR‑3188 and hsa‑miR‑3135b were significantly higher in the PCOS group than in the control group. In addition, the expression level of hsa‑miR‑3135b was significantly correlated with the number of oocytes retrieved, the fertilization rate and the cleavage rate (P<0.05). The present bioinformatics study on miRNAs may offer a novel understanding of the mechanism of PCOS, and may serve to identify novel miRNA therapeutic targets.

Dataset Information

Bioinformatics analysis of microarray data to explore the key genes involved in HSF4 mutation-induced cataract.

Publications

Bioinformatics analysis of microarray data to explore the key genes involved in <i>HSF4</i> mutation-induced cataract.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets