Dataset Information

Investigation of molecular biomarker candidates for diagnosis and prognosis of chronic periodontitis by bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus (GEO).

ABSTRACT: BACKGROUND:Chronic periodontitis (CP) is a multifactorial inflammatory disease. For the diagnosis of CP, it is necessary to investigate molecular biomarkers and the biological pathway of CP. Although analysis of mRNA expression profiling with microarray is useful to elucidate pathological mechanisms of multifactorial diseases, it is expensive. Therefore, we utilized pooled microarray gene expression data on the basis of data sharing to reduce hybridization costs and compensate for insufficient mRNA sampling. The aim of the present study was to identify molecular biomarker candidates and biological pathways of CP using pooled datasets in the Gene Expression Omnibus (GEO) database. METHODS:Three pooled transcriptomic datasets (GSE10334, GSE16134, and GSE23586) of gingival tissue with CP in the GEO database were analyzed for differentially expressed genes (DEGs) using GEO2R, functional analysis and biological pathways with the Database of Annotation Visualization and Integrated Discovery database, Protein-Protein Interaction (PPI) network and hub gene with the Search Tool for the Retrieval of Interaction Genes database, and biomarker candidates for diagnosis and prognosis and upstream regulators of dominant biomarker candidates with the Ingenuity Pathway Analysis database. RESULTS:We shared pooled microarray datasets in the GEO database. One hundred and twenty-three common DEGs were found in gingival tissue with CP, including 81 upregulated genes and 42 downregulated genes. Upregulated genes in Gene Ontology were significantly enriched in immune responses, and those in the Kyoto Encyclopedia of Genes and Genomes pathway were significantly enriched in the cytokine-cytokine receptor interaction pathway, cell adhesion molecules, and hematopoietic cell lineage. From the PPI network, the 12 nodes with the highest degree were screened as hub genes. Additionally, six biomarker candidates for CP diagnosis and prognosis were screened. CONCLUSIONS:We identified several potential biomarkers for CP diagnosis and prognosis (e.g., CSF3, CXCL12, IL1B, MS4A1, PECAM1, and TAGLN) and upstream regulators of biomarker candidates for CP diagnosis (TNF and TGF2). We also confirmed key genes of CP pathogenesis such as CD19, IL8, CD79A, FCGR3B, SELL, CSF3, IL1B, FCGR2B, CXCL12, C3, CD53, and IL10RA. To our knowledge, this is the first report to reveal associations of CD53, CD79A, MS4A1, PECAM1, and TAGLN with CP.

SUBMITTER: Suzuki A

PROVIDER: S-EPMC6438035 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Investigation of molecular biomarker candidates for diagnosis and prognosis of chronic periodontitis by bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus (GEO).

Suzuki Asami A Horie Tetsuro T Numabe Yukihiro Y

BMC oral health 20190328 1

<h4>Background</h4>Chronic periodontitis (CP) is a multifactorial inflammatory disease. For the diagnosis of CP, it is necessary to investigate molecular biomarkers and the biological pathway of CP. Although analysis of mRNA expression profiling with microarray is useful to elucidate pathological mechanisms of multifactorial diseases, it is expensive. Therefore, we utilized pooled microarray gene expression data on the basis of data sharing to reduce hybridization costs and compensate for insuff ...[more]

PMID: 30922293

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Project description:BackgroundPulpitis is an inflammatory disease, the grade of which is classified according to the level of inflammation. Traditional methods of evaluating the status of dental pulp tissue in clinical practice have limitations. The rapid and accurate diagnosis of pulpitis is essential for determining the appropriate treatment. By integrating different datasets from the Gene Expression Omnibus (GEO) database, we analysed a merged expression matrix of pulpitis, aiming to identify biological pathways and diagnostic biomarkers of pulpitis.MethodsBy integrating two datasets (GSE77459 and GSE92681) in the GEO database using the sva and limma packages of R, differentially expressed genes (DEGs) of pulpitis were identified. Then, the DEGs were analysed to identify biological pathways of dental pulp inflammation with Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). Protein-protein interaction (PPI) networks and modules were constructed to identify hub genes with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape.ResultsA total of 470 DEGs comprising 394 upregulated and 76 downregulated genes were found in pulpitis tissue. GO analysis revealed that the DEGs were enriched in biological processes related to inflammation, and the enriched pathways in the KEGG pathway analysis were cytokine-cytokine receptor interaction, chemokine signalling pathway and NF-κB signalling pathway. The GSEA results provided further functional annotations, including complement system, IL6/JAK/STAT3 signalling pathway and inflammatory response pathways. According to the degrees of nodes in the PPI network, 10 hub genes were identified, and 8 diagnostic biomarker candidates were screened: PTPRC, CD86, CCL2, IL6, TLR8, MMP9, CXCL8 and ICAM1.ConclusionsWith bioinformatics analysis of merged datasets, biomarker candidates of pulpitis were screened and the findings may be as reference to develop a new method of pulpitis diagnosis.

Project description:ObjectiveMicroRNAs (miRNAs) play a vital role in the development of ovarian cancer (OC). The aim of this study to investigate the prognostic value and potential signaling pathways of hsa-miR-9-5p (miR-9) in OC through literature review and bioinformatics methods.MethodsThe expression of miR-9 in OC was assessed using the public datasets from the Gene Expression Omnibus (GEO) database. And a literature review was also performed to investigate the correlation between miR-9 expression and the OC prognosis. Two mRNA datasets (GSE18520 and GSE36668) of OC tissues and normal ovarian tissues (NOTs) were downloaded from GEO to identify the differentially expressed genes (DEGs). The target genes of hsa-miR-9-5p (TG-miR-9-5p) were predicted using miRWALK3.0 and TargetScan. Then the gene overlaps between DEGs in OC and the predicted TG-miR-9-5p were confirmed using a Venn diagram. After that, overlapping genes were subjected to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the impact of hub genes on OC prognosis was analyzed.ResultsIt was found that OC patients with miR-9 low expression had poor prognosis. A total of 107 DEGs related to both OC and miR-9 were identified. Dozens of DEGs were enriched in developmental process, extracellular matrix structural constituent, cell junction, axon guidance. In the PPI network analysis, 5 of the top 10 hub genes was significantly associated with decreased overall survival of OC patients, namely FBN1 (HR = 1.64, P < 0.05), PRRX1 (HR = 1.76, P < 0.05), SMC2 (HR = 1.22, P < 0.05), SMC4 (HR = 1.31, P < 0.05), and VCAN (HR = 1.48, P < 0.05).ConclusionLow expression of miR-9 indicates poor prognosis of OC patients. MiR-9 plays a crucial role in the biological process of OC by binding to target genes, thus affecting the prognosis of patients.

Dataset Information

Investigation of molecular biomarker candidates for diagnosis and prognosis of chronic periodontitis by bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus (GEO).

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Investigation of molecular biomarker candidates for diagnosis and prognosis of chronic periodontitis by bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus (GEO).

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