Dataset Information

Identification of Differentially Expressed Genes and Signaling Pathways in Placenta Tissue of Early-Onset and Late-Onset Pre-Eclamptic Pregnancies by Integrated Bioinformatics Analysis.

ABSTRACT: BACKGROUND Pre-eclampsia (PE) can be divided into 2 sub-groups: early-onset and late-onset PE. Although these sub-groups show overlapping molecular and cellular mechanisms and similar clinical manifestations, they are regarded as 2 different phenotypes with heterogeneous manifestations. The pathophysiological mechanisms underlying early-onset and late-onset PE still remain unclear. Therefore, the present study aimed to identify the key genes and pathways related to early-onset and late-onset PE, and to investigate the molecular mechanisms that are involved in gene regulation. MATERIAL AND METHODS Our analysis involved the Gene Expression Series (GSE) 74341 and GSE22526 from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus Database. These 2 microarray datasets included 15 patients with early-onset PE and 15 patients with late-onset PE. RESULTS Our analyses identified 15 differentially expressed genes (DEGs), including CGA, EGR1, HBB, HBA2, LEP, and LHB. Gene Ontology (GO) functional annotation showed that the biological functions of these DEGs were mainly associated with steroid biosynthetic, oxidative stress, angiogenesis, and sex differentiation. Signaling pathway analyses showed that these DEGs were mainly involved in the prolactin signaling pathway, hormone metabolism, the AMPK signaling pathway, and the FoxO signaling pathway. Protein-protein interaction (PPI) network analysis identified 4 genes with the highest degree of interaction. The hub genes for this selection of DEGS were EGR1, LEP, and HBB. CONCLUSIONS Integrated bioinformatic analyses provide us with a new approach to further understand the pathophysiology and molecular mechanisms underlying early-onset and late-onset PE. The DEGs identified in this study represent potential biomarkers for the early diagnosis of PE and may provide significant options the treatment of these 2 subtypes of PE.

SUBMITTER: Liu J

PROVIDER: S-EPMC7294845 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Identification of Differentially Expressed Genes and Signaling Pathways in Placenta Tissue of Early-Onset and Late-Onset Pre-Eclamptic Pregnancies by Integrated Bioinformatics Analysis.

Liu Jing J Song Guang G Meng Tao T Zhao Ge G

Medical science monitor : international medical journal of experimental and clinical research 20200604

BACKGROUND Pre-eclampsia (PE) can be divided into 2 sub-groups: early-onset and late-onset PE. Although these sub-groups show overlapping molecular and cellular mechanisms and similar clinical manifestations, they are regarded as 2 different phenotypes with heterogeneous manifestations. The pathophysiological mechanisms underlying early-onset and late-onset PE still remain unclear. Therefore, the present study aimed to identify the key genes and pathways related to early-onset and late-onset PE, ...[more]

PMID: 32497025

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Project description:Nasopharyngeal carcinoma (NPC) is a common malignancy of the head and neck. The aim of the present study was to conduct an integrated bioinformatics analysis of differentially expressed genes (DEGs) and to explore the molecular mechanisms of NPC. Two profiling datasets, GSE12452 and GSE34573, were downloaded from the Gene Expression Omnibus database and included 44 NPC specimens and 13 normal nasopharyngeal tissues. R software was used to identify the DEGs between NPC and normal nasopharyngeal tissues. Distributions of DEGs in chromosomes were explored based on the annotation file and the CYTOBAND database of DAVID. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied. Additionally, a protein-protein interaction (PPI) network, constructed using the STRING database and visualized by Cytoscape, was used to identify hub genes, key modules and important transcription factors (TFs). A total of 906 DEGs were identified; 434 (47.90%) DEGs were upregulated and 472 (52.10%) were downregulated. The DEGs were demonstrated to be enriched in chromosome 7p15-p14, 2q31, 1q21-q22, 1q21, 4q21 and 1p31-p22. DEGs were mainly enriched for the following GO terms: 'Cilium movement', 'microtubule bundle formation' and 'axoneme assembly'. KEGG pathway enrichment analysis revealed that pathways for 'cell cycle', 'DNA replication', 'interleukin-17 signaling', 'amoebiasis' and 'glutathione metabolism' were enriched. In addition, a PPI network comprising 867 nodes and 1,241 edges was constructed. Finally, five hub genes (aurora kinase A, cell division cycle 6, mitotic arrest deficient 2-like 1, DNA topoisomerase 2α and TPX2 microtubule nucleation factor), 8 modules, and 14 TFs were identified. Modules analysis revealed that cyclin-dependent kinase 1 and exportin 1 were involved in the pathway of Epstein-Barr virus infection. In summary, the hub genes, key modules and TFs identified in this study may promote our understanding of the pathogenesis of NPC and require further in-depth investigation.

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Dataset Information

Identification of Differentially Expressed Genes and Signaling Pathways in Placenta Tissue of Early-Onset and Late-Onset Pre-Eclamptic Pregnancies by Integrated Bioinformatics Analysis.

Publications

Identification of Differentially Expressed Genes and Signaling Pathways in Placenta Tissue of Early-Onset and Late-Onset Pre-Eclamptic Pregnancies by Integrated Bioinformatics Analysis.

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