Identification of IGF-1-enhanced cytokine expressions targeted by miR-181d in glioblastomas via an integrative miRNA/mRNA regulatory network analysis.
Kuo-Hao HoPeng-Hsu ChenEdward HsiChwen-Ming ShihWei-Chiao ChangChia-Hsiung ChengCheng-Wei LinKu-Chung ChenPublished in: Scientific reports (2017)
The insulin-like growth factor (IGF)-1 signaling is relevant in regulating cell growth and cytokine secretions by glioblastomas. MicroRNAs determine the cell fate in glioblastomas. However, relationships between IGF-1 signaling and miRNAs in glioblastoma pathogenesis are still unclear. Our aim was to validate the IGF-1-mediated mRNA/miRNA regulatory network in glioblastomas. Using in silico analyses of mRNA array and RNA sequencing data from The Cancer Genome Atlas (TCGA), we identified 32 core enrichment genes that were highly associated with IGF-1-promoted cytokine-cytokine receptor interactions. To investigate the IGF-1-downregulated miRNA signature, microarray-based approaches with IGF-1-treated U87-MG cells and array data in TCGA were used. Four miRNAs, including microRNA (miR)-9-5p, miR-9-3p, miR-181d, and miR-130b, exhibited an inverse correlation with IGF-1 levels. The miR-181d, that targeted the most IGF-1-related cytokine genes, was significantly reduced in IGF-1-treated glioma cells. Statistical models incorporating both high-IGF-1 and low-miR-181d statuses better predicted poor patient survival, and can be used as an independent prognostic factor in glioblastomas. The C-C chemokine receptor type 1 (CCR1) and interleukin (IL)-1b demonstrated inverse correlations with miR-181d levels and associations with patient survival. miR-181d significantly attenuated IGF-1-upregulated CCR1 and IL-1b gene expressions. These findings demonstrate a distinct role for IGF-1 signaling in glioma progression via miR-181d/cytokine networks.
Keyphrases
- binding protein
- cell proliferation
- pi k akt
- growth hormone
- long non coding rna
- long noncoding rna
- network analysis
- cell cycle arrest
- signaling pathway
- single cell
- high resolution
- electronic health record
- gene expression
- machine learning
- cell death
- drug delivery
- big data
- deep learning
- case report
- induced apoptosis
- high density
- molecular docking
- newly diagnosed
- molecular dynamics simulations