Dataset Information

Identification of microRNAs associated with the aggressiveness of prolactin pituitary tumors using bioinformatic analysis.

ABSTRACT: Aggressive prolactin pituitary tumors, which exhibit aggressive behaviors and resistance to conventional treatments, are a huge challenge for neurosurgeons. Many studies have investigated the roles of microRNAs (miRNAs) in pituitary tumorigenesis, invasion and metastasis, but few have explored aggressiveness‑associated miRNAs in aggressive pituitary tumors. Differentially expressed miRNAs (DEMs) between aggressive and nonaggressive prolactin pituitary tumors were screened using the GSE46294 miRNA expression profile downloaded from the GEO database. The potential target genes of the top three most highly upregulated and downregulated DEMs were predicted by miRTarBase, and potential functional annotation and pathway enrichment analysis were performed using the DAVID database. Protein‑protein interaction (PPI) and miRNA‑hub gene interaction networks were constructed by Cytoscape software. A total of 43 DEMs were identified, including 19 upregulated and 24 downregulated miRNAs, between aggressive and nonaggressive prolactin pituitary tumors. One hundred and seventy and 680 target genes were predicted for the top three most highly upregulated and downregulated miRNAs, respectively, and these genes were involved in functional enrichment pathways, such as regulation of transcription from RNA polymerase II promoter, DNA‑templated transcription, Wnt signaling pathway, protein binding, and transcription factor activity (sequence‑specific DNA binding). In the PPI network, the top 10 genes with the highest degree of connectivity of the upregulated and downregulated DEMs were selected as hub genes. By constructing an miRNA‑hub gene network, it was found that most hub genes were potentially modulated by hsa‑miR‑489 and hsa‑miR‑520b. Targeting hsa‑miR‑489 and hsa‑miR‑520b may provide new clues for the diagnosis and treatment of aggressive prolactin pituitary tumors.

SUBMITTER: Wang Z

PROVIDER: S-EPMC6609352 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most lethal cancer, mainly attributing to its high tendency to metastasis. Vascular invasion provides a direct path for solid tumor metastasis. Mounting evidence has demonstrated that microRNAs (miRNAs) are related to human cancer onset and progression including invasion and metastasis.MethodsIn search of invasion-metastasis-associated miRNAs in HCC, microarray dataset GSE67140 was downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE-miRNAs) were obtained by R software package and the potential target genes were predicted by miRTarBase. The database for annotation, visualization and integrated discovery (DAVID) was introduced to perform functional annotation and pathway enrichment analysis for these potential targets of DE-miRNAs. Protein-protein interaction (PPI) network was established by STRING database and visualized by Cytoscape software. The effects of the miR-494-3p and miR-126-3p on migration and invasion of HCC cell lines were evaluated by conducting wound healing assay and transwell assay.ResultsA total of 138 DE-miRNAs were screened out, including 57 upregulated miRNAs and 81 downregulated miRNAs in human HCC tumors with vascular invasion compared with human HCC tumors without vascular invasion. 762 target genes of the top three upregulated and downregulated miRNAs were predicted, and they were involved in HCC-related pathways, such as pathway in cancer, focal adhesion and MAPK signaling pathway. In the PPI network, the top 10 hub nodes with higher degrees were identified as hub genes, such as TP53 and MYC. Through constructing the miRNA-hub gene network, we found that most of hub genes could be potentially modulated by miR-494-3p and miR-126-3p. Of note, miR-494-3p and miR-126-3p was markedly upregulated and downregulated in HCC cell lines and tissues, respectively. In addition, overexpression of miR-494-3p could significantly promote HCC migration and invasion whereas overexpression of miR-126-3p exerted an opposite effect.ConclusionsTargeting miR-494-3p and miR-126-3p may provide effective and promising approaches to suppress invasion and metastasis of HCC.

Project description:PurposeTo investigate the potential pathophysiological association between tuberculosis (TB) and diabetes mellitus (DM) using bioinformatic analyses.Patients and methodsGene expression datasets for healthy controls (HCs), TB patients, DM patients, TB+DM patients (GSE114192), and metformin-treated cells (GSE102677) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified from pairwise dataset comparisons TB vs HCs and DM vs HCs. DEGs were verified by comparing them to DEGs for TB+DM vs HCs. Enrichment analysis of DEGs common to all three dataset comparisons was conducted using DAVID. The protein-protein interaction (PPI) network was established via STRING and visualised in Cytoscape. Hub genes were identified using the Cytoscape plug-in cytoHubba and then were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. Targeted miRNA prediction analysis identified metformin treatment-induced gene expression changes in peripheral blood mononuclear cells.ResultsA total of 422 DEGs were common to all three dataset comparisons. Functional enrichment analysis revealed these DEGs were enriched for functional terms of type I interferon signaling pathway, innate immune response, inflammatory response, and infectious diseases. Ten hub genes identified using PPI network analysis were screened for interactions with metformin target gene INS using cytoHubba based on maximal clique centrality (MCC) score. Subsequently, five hub genes were predicted to functionally interact with INS, including STAT1, IFIT3, RSAD2, IFI44L, and XAF1, as verified by RT-qPCR. Meanwhile, seven miRNAs (miR-3680-3p, miR-3059-5p, miR-629-3p, miR-29b-2-5p, miR-514b-5p, miR-4755-5p, miR-4691-3p) were associated with regulation of hub genes. Notably, six hub genes (STAT1, IFIT3, RSAD2, ISG15, IFI44, IFI6) were down-regulated in cells exposed to both metformin and Mycobacterium tuberculosis antigens.ConclusionNetwork hub genes hold promise as disease status biomarkers and as metformin treatment targets for alleviating TB and DM. This study describes a strategy for exploring pathogenic mechanisms of diseases such as TB and DM.

Dataset Information

Identification of microRNAs associated with the aggressiveness of prolactin pituitary tumors using bioinformatic analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets