Identification of Early-Onset Preeclampsia-Related Genes and MicroRNAs by Bioinformatics Approaches

Jing, Song; Li, Yue; An, Rui

doi:10.1177/1933719115570898

Cited by 19 publications

(17 citation statements)

References 52 publications

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“…>0.7) we can identify: LEP, FLT1, INHA, ENG, PAPPA2, and CRH. There are sufficient evidences to associate these genes with PE pathogenesis or clinical manifestation [14, 52, 53, 56–60]. Our calculations also indicate that communities 6 and 2 are those with highest enrichment of genes coming from microarray data confirming our previous results using the network and consensus prioritization (Table 6).…”

Section: Discussionsupporting

confidence: 88%

Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis

et al. 2017

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BackgroundPreeclampsia is a multifactorial disease with unknown pathogenesis. Even when recent studies explored this disease using several bioinformatics tools, the main objective was not directed to pathogenesis. Additionally, consensus prioritization was proved to be highly efficient in the recognition of genes-disease association. However, not information is available about the consensus ability to early recognize genes directly involved in pathogenesis. Therefore our aim in this study is to apply several theoretical approaches to explore preeclampsia; specifically those genes directly involved in the pathogenesis.MethodsWe firstly evaluated the consensus between 12 prioritization strategies to early recognize pathogenic genes related to preeclampsia. A communality analysis in the protein-protein interaction network of previously selected genes was done including further enrichment analysis. The enrichment analysis includes metabolic pathways as well as gene ontology. Microarray data was also collected and used in order to confirm our results or as a strategy to weight the previously enriched pathways.ResultsThe consensus prioritized gene list was rationally filtered to 476 genes using several criteria. The communality analysis showed an enrichment of communities connected with VEGF-signaling pathway. This pathway is also enriched considering the microarray data. Our result point to VEGF, FLT1 and KDR as relevant pathogenic genes, as well as those connected with NO metabolism.ConclusionOur results revealed that consensus strategy improve the detection and initial enrichment of pathogenic genes, at least in preeclampsia condition. Moreover the combination of the first percent of the prioritized genes with protein-protein interaction network followed by communality analysis reduces the gene space. This approach actually identifies well known genes related with pathogenesis. However, genes like HSP90, PAK2, CD247 and others included in the first 1% of the prioritized list need to be further explored in preeclampsia pathogenesis through experimental approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-017-0286-x) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 88%

Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis

et al. 2017

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“…The hub genes with top degrees in the PPI network were FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36. FOS was identified as up-regulated in PE, which was consist with that reported by Song[ 23 ]. FOS is involved in the regulation of angiogenesis by encoding the transcription factor c-fos proto-oncogene[ 24 ].…”

Section: Discussionsupporting

confidence: 87%

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis

et al. 2017

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Preeclampsia is a leading cause of perinatal maternal–foetal mortality and morbidity. The aim of this study is to identify the key microRNAs and genes in preeclampsia and uncover their potential functions. We downloaded the miRNA expression profile of GSE84260 and the gene expression profile of GSE73374 from the Gene Expression Omnibus database. Differentially expressed miRNAs and genes were identified and compared to miRNA-target information from MiRWalk 2.0, and a total of 65 differentially expressed miRNAs (DEMIs), including 32 up-regulated miRNAs and 33 down-regulated miRNAs, and 91 differentially expressed genes (DEGs), including 83 up-regulated genes and 8 down-regulated genes, were identified. The pathway enrichment analyses of the DEMIs showed that the up-regulated DEMIs were enriched in the Hippo signalling pathway and MAPK signalling pathway, and the down-regulated DEMIs were enriched in HTLV-I infection and miRNAs in cancers. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses of the DEGs were performed using Multifaceted Analysis Tool for Human Transcriptome. The up-regulated DEGs were enriched in biological processes (BPs), including the response to cAMP, response to hydrogen peroxide and cell-cell adhesion mediated by integrin; no enrichment of down-regulated DEGs was identified. KEGG analysis showed that the up-regulated DEGs were enriched in the Hippo signalling pathway and pathways in cancer. A PPI network of the DEGs was constructed by using Cytoscape software, and FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36 were identified as the hub genes. The current study illustrates a characteristic microRNA profile and gene profile in preeclampsia, which may contribute to the interpretation of the progression of preeclampsia and provide novel biomarkers and therapeutic targets for preeclampsia.

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“…Besides, it can also occur in bone tissues in other sites, such as vertebral column, skeleton and upper femur. OS is a primary malignant bone tumor that is frequently seen in children and adolescent, and lung metastasis is responsible for the major cause of death (7). OS cell invasion and metastasis is the interaction between cells and extracellular matrix, which is a complicated and multi-step process involving the effects of multiple oncogenes (8).…”

Section: Discussionmentioning

confidence: 99%

MicroRNA-152 inhibits cell proliferation of osteosarcoma by directly targeting Wnt/β-catenin signaling pathway in a DKK1-dependent manner

Zhao

Sun²,

et al. 2018

Oncol Rep

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The function of microRNA‑152 for a cohort of patients with osteosarcoma and the influence on cell growth of osteosarcoma were studied. The expression of microRNA‑152 was downregulated in patients with osteosarcoma. The downregulation of microRNA‑152 promotes cell proliferation, decreases apoptosis, and suppresses LDH activity, caspase-3/9 activities and Bax/Bcl-2 and p53 protein expression levels of osteosarcoma through activation of the Wnt/β-catenin signaling pathway by targeting DKK1. Whereas, overexpression of microRNA‑152 targets DKK1 to inhibit cell proliferation, induce apoptosis, and promote LDH activity, caspase-3/9 activities and Bax/Bcl-2 and p53 protein expression levels of osteosarcoma through inactivation of the Wnt/β-catenin signaling pathway. The promotion of DKK1 reversed the anticancer function of microRNA‑152 over-expression through Wnt/β-catenin signaling pathway. We demonstrated that microRNA‑152 inhibits cell proliferation of osteosarcoma through DKK1 by directly targeting Wnt/β‑catenin signaling pathway.

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Identification of Early-Onset Preeclampsia-Related Genes and MicroRNAs by Bioinformatics Approaches

Abstract: The current study identified several regulators in EOPET, which may contribute to interpret the molecular mechanism of EOPET and develop novel biomarkers and therapeutic targets for EOPET.

Cited by 19 publications

References 52 publications

Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis

Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis

MicroRNA-152 inhibits cell proliferation of osteosarcoma by directly targeting Wnt/β-catenin signaling pathway in a DKK1-dependent manner

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