Biological Gene Ontology Terms Research Articles

Screening Key Genes and Biological Pathways in Nasopharyngeal Carcinoma by Integrated Bioinformatics Analysis.

The purpose of this study was to identify the hub genes and biological pathways of nasopharyngeal carcinoma (NPC) through bioinformatics analysis and potential new therapeutic targets. In this study, three datasets were downloaded from the Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) between NPC and normal tissues were analyzed using the GEO2R online tool. Volcano and heat maps of the DEGs were visualized using the hiplot database. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the upregulated and downregulated DEGs were performed using the DAVID database. Finally, we established a protein-protein interaction (PPI) network using the STRING database and showed the differential expression of hub genes between the normal and tumor tissues. In all, 109,371,221 upregulated DEGs and 139,226,520 downregulated DEGs were obtained in datasets GSE40290, GSE61218, and GSE53819, respectively, and 18 common differential genes, named co-DEGs, were screened in the three datasets. The most abundant biological GO terms of the co-DEGs were inflammatory response et al. The KEGG pathway enrichment analysis showed that co-DEGs mainly participated in the interleukin (IL)-17 signaling pathway et al. Finally, we identified four hub genes using PPI analysis and observed that three of them were highly expressed in tumor tissues. In this study, the hub genes of NPC, such as PTGS2, and pathways such as IL-17 signaling, were identified through bioinformatics analysis, which may be potential new therapeutic targets for NPC.

Transcriptomic Analyses Reveal Gene Expression Profiles and Networks in Nasopharyngeal Carcinoma.

Background Nasopharyngeal carcinoma (NPC) is a rare but highly aggressive tumor that is predominantly encountered in Southeast Asia and China in particular. Aside from radiotherapy, no effective therapy that specifically treats NPC is available, including targeted drugs. Finding more sensitive biomarkers is important for new drug discovery and for evaluating patient prognosis. Methods mRNA expression datasets from the Gene Expression Omnibus database (GSE53819, GSE64634, and GSE40290) were selected. After all samples in each dataset were subjected to quality control using principal component analyses, the qualified samples were used for additional analyses. The genes that were significantly expressed in each dataset were intersected to identify the most significant of these. Gene functional enrichment analyses were performed on these genes, using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses. The protein–protein interaction network of selected genes was analyzed using the Search Tool for the Retrieval of Interacting Genes database. Significantly, differentially expressed genes were further verified with two RNA-seq datasets (GSE68799 and GSE12452), as well as in clinical samples. Results In all, 34 (8 upregulated genes and 26 downregulated) genes were identified as significantly differentially expressed. The immune response and the regulation of cell proliferation were the most enriched biological GO terms. Using reverse transcription quantitative real-time PCR (RT-qPCR), the genes MMP1, AQP9, and TNFAIP6 were detected to be upregulated, and FAM3D, CR2, and LTF were downregulated in NPC tissue samples. Conclusion This study provides information on the genes that may be involved in the development of NPC and suggests possible druggable targets and biomarkers for diagnosing and evaluating the prognosis of NPC.

Gene profiles of THP-1 macrophages after in vitro exposure to respiratory (non-)sensitizing chemicals: Identification of discriminating genetic markers and pathway analysis

It is recognized that respiratory sensitization is a hazard of high concern. Despite international regulatory requirements there is no established protocol for the identification of chemical respiratory sensitizers. New tests should be based on mechanistic understanding and should be preferentially restricted to in vitro assays. The major goal of this study was to investigate the genetic response of human THP-1 macrophages after contact with respiratory (non-)sensitizers, and to identify genes that are able to discriminate between both groups. THP-1 macrophages were exposed during different time points to 3 respiratory sensitizers, 2 irritants, and 1 skin sensitizer. Gene expression changes were evaluated using Agilent Whole Human Genome arrays. Fisher Linear Discriminant Analysis was used to obtain a ranking of genes that reflects their potential to discriminate between respiratory (non-)sensitizing chemicals. Among the 20 most discriminating genes which were categorized into molecular and biological Gene Ontology (GO) terms, EIF4E, PDGFRB, SEMA7A, and ZFP36L2 could be associated with respiratory sensitization. When categorizing the top-1000 genes into biological GO terms, 24 genes were associated with immune function. Using a pathway analysis tool, platelet-derived growth factor signaling was observed to be activated in THP-1 macrophages in the context of respiratory sensitization.

Gene profiles of a human alveolar epithelial cell line after in vitro exposure to respiratory (non-)sensitizing chemicals: Identification of discriminating genetic markers and pathway analysis

There are currently no accepted biological prediction models for assessing the potential of a substance to cause respiratory sensitization. New tests should be based on mechanistic understanding and should be preferentially restricted to in vitro assays. The major goal of this study was to investigate the alterations in gene expression of human alveolar epithelial (A549) cells after exposure to respiratory sensitizing and non-respiratory sensitizing chemicals, and to identify genes that are able to discriminate between both groups of chemicals. A549 cells were exposed during 6, 10, and 24 h to the respiratory sensitizers ammonium hexachloroplatinate IV, hexamethylene diisocyanate, and trimellitic anhydride, the irritants acrolein and methyl salicylate, and the skin sensitizer 1-chloro-2,4-dinitrobenzene. Overall changes in gene expression were evaluated using Agilent Whole Human Genome 4x44K oligonucleotide arrays. A Fisher linear discriminant analysis was used to obtain a ranking of genes that reflects their potential to discriminate between respiratory sensitizing and respiratory non-sensitizing chemicals. Among the 20 most discriminating genes, which were categorized into molecular and biological gene ontology (GO) terms, CTLA4 could be associated with asthma and/or respiratory sensitization. When categorizing the top-1000 genes into biological GO terms, 22 genes were associated with immune function. Using a pathway analysis tool to identify possible underlying mechanisms of respiratory sensitization, no known canonical signaling pathway was observed to be activated in the A549 cell line.