Co‑expression network analysis of differentially expressed genes associated with metastasis in prolactin pituitary tumors

Zhang,Wei; Zang,Zhenle; Song,Yechun; Yang,Hui; Yin,Qing

doi:10.3892/mmr.2014.2152

Co‑expression network analysis of differentially expressed genes associated with metastasis in prolactin pituitary tumors

Authors:
- Wei Zhang
- Zhenle Zang
- Yechun Song
- Hui Yang
- Qing Yin
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Affiliations: Department of Neurosurgery, Xinqiao Hospital, Third Military Medical University, Chongqing 400037, P.R. China, Department of Rehabilitation and Physical Therapy, Southwest Hospital, Third Military Medical University, Chongqing 400038, P.R. China
Published online on: April 15, 2014 https://doi.org/10.3892/mmr.2014.2152
Pages: 113-118

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Abstract

The aim of the present study was to construct a co‑expression network of differently expressed genes (DEGs) in prolactin pituitary (PRL) tumor metastasis. The gene expression profile, GSE22812 was downloaded from the Gene Expression Omnibus database, and including five non‑invasive, two invasive and six aggressive‑invasive PRL tumor samples. Compared with non‑invasive samples, DEGs were identified in invasive and aggressive‑invasive samples using a limma package in R language. The expression values of DEGs were hierarchically clustered. Next, Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis of DEGs were performed via The Database for Annotation, Visualization and Integrated Discovery. Finally, gene pairs of DEGs between non‑invasive and aggressive‑invasive samples were identified using the Spearman cor( ) function in R language. Compared with the non‑invasive samples, 61 and 89 DEGs were obtained from invasive and aggressive‑invasive samples, respectively. Cluster analysis showed that four genes were shared by the two samples, including upregulated solute carrier family 2, facilitated glucose transporter member 11 (SLC2A11) and teneurin transmembrane protein 1 (TENM1) and downregulated importin 7 (IPO7) and chromogranin B (CHGB). In the invasive samples, the most significant GO terms responded to cyclic adenosine monophosphate and a glucocorticoid stimulus. However, this occurred in the cell cycle, and was in response to hormone stimulation in aggressive‑invasive samples. The co‑expression network of DEGs showed different gene pairs and modules, and SLC2A11 and CHGB occurred in two co‑expression networks within different co‑expressed pairs. In the present study, the co‑expression network was constructed using bioinformatics methods. SLC2A11, TENM1, IPO7 and CHGB are hypothesized to be closely associated with metastasis of PRL. Furthermore, CHGB and SLC2A11 may be significant in PRL tumor progression and serve as molecular biomarkers for PRL tumors. However, further investigation is required to confirm the current results.

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