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pmid:31173251

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

Zihao Wang · Lu Gao · Xiaopeng Guo · Chenzhe Feng · Kan Deng · Wei Lian · Bing Xing

Oncology reports · 2019 doi:10.3892/or.2019.7173

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

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title
Identification of microRNAs associated with the aggressiveness of prolactin pituitary tumors using bioinformatic analysis.
doi
10.3892/or.2019.7173
pmid
31173251
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Zihao Wang
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Lu Gao
[2]
Xiaopeng Guo
[3]
Chenzhe Feng
[4]
Kan Deng
[5]
Wei Lian
[6]
Bing Xing
journal
Oncology reports
year
2019
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.
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Integrative miRnome and transcriptome analysis in human malignant prolactin pituitary tumors identify miR-183 as driving gene for tumor progression to malignancy.
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