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Article Open Access

Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas

  • Authors:
    • Ziming Hou
    • Jun Yang
    • Gang Wang
    • Changjiang Wang
    • Hongbing Zhang
  • View Affiliations / Copyright

    Affiliations: Department of Neurosurgery, Beijing Luhe Hospital, Capital Medical University, Beijing 101149, P.R. China
    Copyright: © Hou et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 1655-1663
    |
    Published online on: November 30, 2017
       https://doi.org/10.3892/ol.2017.7505
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Abstract

The aim of the present study was to identify genes, microRNAs (miRNAs/miRs) or pathways associated with the development of pituitary gonadotroph adenomas. The array data of GSE23207, which included 16 samples of multiple endocrine neoplasia-associated rat pituitary homozygous mutations and 5 pituitary tissue samples from healthy rats, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were analyzed prior to functional enrichment analysis and protein-protein interaction (PPI) network construction. miRNAs associated with DEGs were predicted, and an miRNA-target regulatory network was constructed. A total of 187 upregulated and 370 downregulated DEGs were identified in the pituitary gonadotroph adenoma group compared with the healthy (control) group. Cyclin-dependent kinase (Cdk) 1 exhibited the highest degree in the PPI network. The upregulated DEGs were predominately enriched in ‘neuroactive ligand-receptor interaction’ pathway, and downregulated DEGs were mainly enriched in ‘cell cycle’. The DEGs in module were predominately enriched in the ‘cell cycle’, whereas DEGs in module b and c were enriched in ‘neuroactive ligand-receptor interaction’. miR-374, -153, -145 and -33 were identified as important miRNAs in the regulation of the DEGs. Cdk1, cyclin (Ccn) A2, Ccnb1, ‘cell cycle’ and ‘neuroactive ligand-receptor interaction’ pathways may serve important roles in the development of pituitary gonadotroph adenomas; Ccna2 and Ccnb1 may contribute to this development via an effect on the ‘cell cycle’ pathway. Furthermore, miR-374 and -145 may contribute to the development of pituitary gonadotroph adenomas via regulation of the expression of target genes.
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Copy and paste a formatted citation
Spandidos Publications style
Hou Z, Yang J, Wang G, Wang C and Zhang H: Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas. Oncol Lett 15: 1655-1663, 2018.
APA
Hou, Z., Yang, J., Wang, G., Wang, C., & Zhang, H. (2018). Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas. Oncology Letters, 15, 1655-1663. https://doi.org/10.3892/ol.2017.7505
MLA
Hou, Z., Yang, J., Wang, G., Wang, C., Zhang, H."Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas". Oncology Letters 15.2 (2018): 1655-1663.
Chicago
Hou, Z., Yang, J., Wang, G., Wang, C., Zhang, H."Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas". Oncology Letters 15, no. 2 (2018): 1655-1663. https://doi.org/10.3892/ol.2017.7505
Copy and paste a formatted citation
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Spandidos Publications style
Hou Z, Yang J, Wang G, Wang C and Zhang H: Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas. Oncol Lett 15: 1655-1663, 2018.
APA
Hou, Z., Yang, J., Wang, G., Wang, C., & Zhang, H. (2018). Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas. Oncology Letters, 15, 1655-1663. https://doi.org/10.3892/ol.2017.7505
MLA
Hou, Z., Yang, J., Wang, G., Wang, C., Zhang, H."Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas". Oncology Letters 15.2 (2018): 1655-1663.
Chicago
Hou, Z., Yang, J., Wang, G., Wang, C., Zhang, H."Bioinformatic analysis of gene expression profiles of pituitary gonadotroph adenomas". Oncology Letters 15, no. 2 (2018): 1655-1663. https://doi.org/10.3892/ol.2017.7505
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