Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer

Shivakumar, Manu; Lee, Younghee; Bang, Lisa; Garg, Tullika; Sohn, Kyung-Ah; Kim, Dokyoon

doi:10.1186/s12920-017-0269-y

Cited by 55 publications

(43 citation statements)

References 70 publications

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“…TCGA (The Cancer Genome Atlas, https://cancergenome.nih.gov/) is a public repository for data storage that is freely available to users. A variety of human cancer and tumor subtype genomic mutation profiles (11), transcriptomic data (12), and clinical data (13) have been generated, providing a systematic characterization of methylation (14), miRNA expression (15), and oncogenic processes (16). Gene expression profiles of GBM were downloaded from the TCGA dataset, which contains 529 GBM samples and 10 normal samples.…”

Section: Methodsmentioning

confidence: 99%

ZWINT: A potential therapeutic biomarker in patients with glioblastoma correlates with cell proliferation and invasion

et al. 2020

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Glioblastoma (GBM) is the most aggressive primary intracranial tumor in adults. Chemoradiotherapy resistance and recurrence after surgery are the main malignant progression factors, leading to a high mortality rate. Therefore, the exploration of novel biomarkers and molecular mechanisms of GBM is urgent. Differentially expressed genes (DEGs) of GBM were screened in a TCGA dataset. Homo sapiens ZW10 interacting kinetochore protein (ZWINT) was found to be upregulated in GBM, which was confirmed by immunohistochemical staining of a tissue microarray. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. A protein-protein interaction (PPI) network was established by the STRING database, and hub genes were visualized by Cytoscape. The correlation results were verified with the GSE15824 dataset. Bioinformatic analysis confirmed that ZWINT was significantly positively correlated with kinetochore protein NDC80 homolog (NDC80), serine/threonine-protein kinase PLK1 (PLK1) and spindle and kinetochore associated complex subunit 1 (SKA1) and together are involved in regulating mitosis and the cell cycle of GBM. ZWINT expression was knocked down in U251 and U87 MG GBM cells by lentiviral vectors carrying a small hairpin RNA (shRNA) targeting ZWINT. The effect of ZWINT silencing on cell proliferation, invasion and apoptosis was determined by the Celigo assay, MTT assay, Transwell assay, flow cytometry and caspase-3/7 assay in vitro. A subcutaneous xenograft tumor model was established to explore the influence of ZWINT knockdown on GBM growth in vivo. Our preliminary study demonstrated that ZWINT knockdown effectively inhibited proliferation and invasion and induced apoptosis of GBM cells and notably suppressed GBM growth in vivo. Therefore, we speculate that ZWINT may be a potential therapeutic biomarker for GBM, with NDC80 and PLK1 conjointly involved in regulating cell division and the mitotic cell cycle.

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Section: Methodsmentioning

confidence: 99%

ZWINT: A potential therapeutic biomarker in patients with glioblastoma correlates with cell proliferation and invasion

et al. 2020

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“…DNA methylation is crucial for mammalian embryo development which is dynamically regulated by the action of the DNA methyltransferases (DNMTs) and ten eleven translocation enzymes (TETs) (Ambrosi, Manzo, & Baubec, ; Li & Zhang, ; Lim, Knowles, Solter, & Messerschmidt, ). As both targets and effectors of DNMTs and TETs, miRNAs play pivotal roles in regulating DNA methylation (Hua et al., ; Jin, Li, Ouyang, Tan, & Jiang, ; Shivakumar et al., ). DNA methylation can inhibit the transcription of miRNAs by methylating the CpG islands in the promoter regions of miRNAs, and certain miRNAs can directly target DNA methylation‐related enzymes, thereby affecting the whole genome methylation pattern (Chhabra, ).…”

Section: Introductionmentioning

confidence: 99%

MicroRNA‐29b regulatesDNAmethylation by targeting Dnmt3a/3b and Tet1/2/3 in porcine early embryo development

et al. 2018

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MicroRNA-29b (miR-29b) is a member of the miR-29 family, which targets DNA methyltransferases (DNMTs) and ten eleven translocation enzymes (TETs), thereby regulating DNA methylation. However, the role of miR-29b in porcine early embryo development has not been reported. In this study, we examined the effects of miR-29b in porcine in vitro fertilization (IVF) embryos to investigate the mechanism by which miR-29b regulated DNA methylation. The interference of miR-29b by its special miRNA inhibitor significantly up-regulated Dnmt3a/b and Tet1 but downregulated Tet2/3; meanwhile it increased DNA methylation levels of the global genome and Nanog promoter region but decreased global DNA demethylation levels. The inhibition of miR-29b also resulted in a decrease in the development rate and quality of blastocysts. In addition, the pluripotency genes Nanog and Sox2 were significantly downregulated, and the apoptosis genes Bax and Casp3 were upregulated, but anti-apoptosis gene Bcl-2 was downregulated in blastocysts. Our study indicated that miR-29b could regulate DNA methylation mediated by miR29b- Dnmt3a/b - Tet1/2/3 signaling during porcine early embryo development.

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“…CEACAM1 is expressed on a variety of immune cells (42, 157), including neutrophils (158) and is a key receptor involved in binding of these cells to endothelial cells during the process of exvagination from the periphery into tissue locations (159,160). CDADC1 (cytidine and dCMP deaminase domain containing 1) is reportedly a testis-specific protein involved in testis development (161), however it may play a role in regulating the cell cycle and proliferation (162,163). Its role in disease processes in the context of this study is very unclear.…”

Section: Gpr84mentioning

confidence: 99%

Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome

et al. 2020

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Sepsis is defined as dysregulated host response caused by systemic infection, leading to organ failure. It is a life-threatening condition, often requiring admission to an intensive care unit (ICU). The causative agents and processes involved are multifactorial but are characterized by an overarching inflammatory response, sharing elements in common with severe inflammatory response syndrome (SIRS) of non-infectious origin. Sepsis presents with a range of pathophysiological and genetic features which make clinical differentiation from SIRS very challenging. This may reflect a poor understanding of the key gene inter-activities and/or pathway associations underlying these disease processes. Improved understanding is critical for early differential recognition of sepsis and SIRS and to improve patient management and clinical outcomes. Judicious selection of gene biomarkers suitable for development of diagnostic tests/testing could make differentiation of sepsis and SIRS feasible. Here we describe a methodologic framework for the identification and validation of biomarkers in SIRS, sepsis and septic shock patients, using a 2-tier gene screening, artificial neural network (ANN) data mining technique, using previously published gene expression datasets. Eight key hub markers have been identified which may delineate distinct, core disease processes and which show potential for informing underlying immunological and pathological processes and thus patient stratification and treatment. These do not show sufficient fold change differences between the different disease states to be useful as primary diagnostic biomarkers, but are instrumental in identifying candidate pathways and other associated biomarkers for further exploration.

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Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer

Cited by 55 publications

References 70 publications

ZWINT: A potential therapeutic biomarker in patients with glioblastoma correlates with cell proliferation and invasion

ZWINT: A potential therapeutic biomarker in patients with glioblastoma correlates with cell proliferation and invasion

MicroRNA‐29b regulatesDNAmethylation by targeting Dnmt3a/3b and Tet1/2/3 in porcine early embryo development

Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome

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