Shi Can, Zhang Zhenyu
Department of Obstetrics and Gynecology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Oncol Lett. 2017 Jul;14(1):725-732. doi: 10.3892/ol.2017.6183. Epub 2017 May 17.
The present study aimed to screen potential genes implicated in epithelial ovarian cancer (EOC) and to further understand the molecular pathogenesis of EOC. In order to do this, datasets GSE14407 (containing 12 human ovarian cancer epithelia samples and 12 normal epithelia samples) and GSE29220 (containing 11 salivary transcriptomes from ovarian cancer patients with serous papillary adenocarcinoma and 11 matched controls) were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) within these datasets were screened using the Linear Models for Microarray Data package, and potential gene functions were predicted by functional and pathway enrichment analyses. Additionally, module analysis of protein-protein interaction networks was performed using MCODE software in Cytoscape. The potential microRNAs (miRNAs/miRs) and transcription factors (TFs) regulating DEGs were also analyzed, and the integrated TF-DEG and miRNA-DEG regulatory networks were visualized with Cytoscape. In total, 31 upregulated DEGs and 64 downregulated DEGs were screened. The upregulated DEGs, such as centromere protein F () and ubiquitin like with PHD and ring finger domains 1 (), were significantly associated with the cell cycle and were regulated by the TF nuclear transcription factor Y (NF-Y). was modulated by miR-373, and was regulated by miR-146a. The downregulated DEGs, such as aldehyde dehydrogenase 1 family member A2 (), were distinctly involved in the response to estrogen stimulus and modulated by tumor protein 53 (); protocadherin 9 () was regulated by , miR-92b-3p and miR-137. The DEGs, including , , and , and a set of gene regulators, including all genes, , miR-373, miR-146a, miR-92b-3p and miR-137, may be involved in the pathogenesis of EOC.
本研究旨在筛选与上皮性卵巢癌（EOC）相关的潜在基因，并进一步了解EOC的分子发病机制。为此，从基因表达综合数据库中获取了数据集GSE14407（包含12个人类卵巢癌上皮样本和12个正常上皮样本）和GSE29220（包含11例浆液性乳头状腺癌卵巢癌患者的唾液转录组和11个匹配对照）。使用微阵列数据线性模型软件包筛选这些数据集中的差异表达基因（DEG），并通过功能和通路富集分析预测潜在基因功能。此外，使用Cytoscape中的MCODE软件对蛋白质-蛋白质相互作用网络进行模块分析。还分析了调控DEG的潜在微小RNA（miRNA/miR）和转录因子（TF），并用Cytoscape可视化整合的TF-DEG和miRNA-DEG调控网络。总共筛选出31个上调的DEG和64个下调的DEG。上调的DEG，如着丝粒蛋白F（）和含PHD和环指结构域1的泛素样蛋白（），与细胞周期显著相关，并受TF核转录因子Y（NF-Y）调控。受miR-373调控，受miR-146a调控。下调的DEG，如醛脱氢酶1家族成员A2（），明显参与对雌激素刺激的反应并受肿瘤蛋白53（）调控；原钙黏蛋白9（）受、miR-92b-3p和miR-137调控。包括、、和在内的DEG，以及一组基因调节因子，包括所有基因、、miR-373、miR-146a、miR-92b-3p和miR-137，可能参与EOC的发病机制。
