Xu Youzheng, Shen Keng
Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Eastern District, Beijing 100730, China,
Cancer Manag Res. 2018 Nov 8;10:5461-5470. doi: 10.2147/CMAR.S187156. eCollection 2018.
Ovarian cancer is the major cause of death from cancer among females worldwide. Ovarian clear cell carcinoma (OCCC) is considered a distinct histopathologic subtype with worse prognosis and resistance to conventional chemotherapy.
We analyzed five microarray datasets derived from the Gene Expression Omnibus database. GEO2R tool was used to screen out differentially expressed genes (DEGs) between OCCC tumor and normal ovary tissue. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using the g:Profiler database and Cytoscape. Based on Search Tool for the Retrieval of Interacting Genes, we performed protein-protein interaction (PPI) network analysis on the DEGs. Real-time PCR (RT-PCR) and Western blotting in frozen samples of normal ovary and OCCC were performed to verify the expression difference of hub genes in OCCC patients.
Thirty upregulated DEGs and 13 downregulated DEGs were identified by cross referencing. Six were chosen as hub genes with high connectivity degree via PPI network analysis, including two upregulated and four downregulated. RT-PCR and Western blotting results showed significant expression difference of the two upregulated genes, and , between tumor and normal tissues.
Our research suggests that and are overexpressed in OCCC compared with normal ovary tissue. Clinical study of large sample is required to evaluate the value of and in the precision treatment and prognostic influence on OCCC in the future.
卵巢癌是全球女性癌症死亡的主要原因。卵巢透明细胞癌（OCCC）被认为是一种独特的组织病理学亚型，预后较差且对传统化疗耐药。
我们分析了来自基因表达综合数据库的五个微阵列数据集。使用GEO2R工具筛选出OCCC肿瘤组织与正常卵巢组织之间的差异表达基因（DEGs）。利用g:Profiler数据库和Cytoscape进行基因本体论和京都基因与基因组百科全书通路富集分析。基于检索相互作用基因的搜索工具，我们对DEGs进行了蛋白质-蛋白质相互作用（PPI）网络分析。对正常卵巢和OCCC的冷冻样本进行实时PCR（RT-PCR）和蛋白质印迹分析，以验证OCCC患者中枢纽基因的表达差异。
通过交叉引用鉴定出30个上调的DEGs和13个下调的DEGs。通过PPI网络分析选择了6个具有高连接度的枢纽基因，其中2个上调，4个下调。RT-PCR和蛋白质印迹结果显示，肿瘤组织和正常组织中两个上调基因，即 和 ，存在显著的表达差异。
我们的研究表明，与正常卵巢组织相比， 和 在OCCC中过表达。未来需要进行大样本的临床研究，以评估 和 在OCCC精准治疗及预后影响方面的价值。
