Zhang Wei, Zang Zhenle, Song Yechun, Yang Hui, Yin Qing
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.
Mol Med Rep. 2014 Jul;10(1):113-8. doi: 10.3892/mmr.2014.2152. Epub 2014 Apr 15.
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.
本研究的目的是构建催乳素垂体（PRL）肿瘤转移中差异表达基因（DEG）的共表达网络。基因表达谱GSE22812从基因表达综合数据库下载，包括5个非侵袭性、2个侵袭性和6个侵袭性强的PRL肿瘤样本。使用R语言中的limma包，与非侵袭性样本相比，在侵袭性和侵袭性强的样本中鉴定出DEG。对DEG的表达值进行层次聚类。接下来，通过注释、可视化和综合发现数据库对DEG进行基因本体（GO）功能富集和京都基因与基因组百科全书通路分析。最后，使用R语言中的Spearman cor()函数鉴定非侵袭性和侵袭性强的样本之间DEG的基因对。与非侵袭性样本相比，分别从侵袭性和侵袭性强的样本中获得了61个和89个DEG。聚类分析表明，两个样本共有4个基因，包括上调的溶质载体家族2、促进葡萄糖转运蛋白成员11（SLC2A11）和腱蛋白跨膜蛋白1（TENM1）以及下调的importin 7（IPO7）和嗜铬粒蛋白B（CHGB）。在侵袭性样本中，最显著的GO术语响应环磷酸腺苷和糖皮质激素刺激。然而，这发生在细胞周期中，并且在侵袭性强的样本中是对激素刺激的响应。DEG的共表达网络显示出不同的基因对和模块，并且SLC2A11和CHGB出现在不同共表达对中的两个共表达网络中。在本研究中，使用生物信息学方法构建了共表达网络。假设SLC2A11、TENM1、IPO7和CHGB与PRL的转移密切相关。此外，CHGB和SLC2A11可能在PRL肿瘤进展中具有重要意义，并可作为PRL肿瘤的分子生物标志物。然而，需要进一步研究来证实目前的结果。
