基于生物信息学分析鉴定与卵巢癌患者发展和预后相关的关键生物标志物。

BACKGROUND: Ovarian cancer (OC) is the deadliest cause in the gynecological malignancies. Most OC patients are diagnosed in advanced stages with less than 40% of women cured. However, the possible mechanism underlying tumorigenesis and candidate biomarkers remain to be further elucidated. RESULTS: Gene expression profiles of GSE18520, GSE54388, and GSE27651 were available from Gene Expression Omnibus (GEO) database with a total of 91 OC samples and 22 normal ovarian (OV) tissues. Three hundred forty-nine differentially expressed genes (DEGs) were screened between OC tissues and OV tissues via GEO2R and online Venn software, followed by KEGG pathway and gene ontology (GO) enrichment analysis. The enriched functions and pathways of these DEGs contain male gonad development, cellular response to transforming growth factor beta stimulus, positive regulation of transcription from RNA polymerase II promoter, calcium independent cell-cell adhesion via plasma membrane cell adhesion molecules, extracellular matrix organization, pathways in cancer, cell cycle, cell adhesion molecules, PI3K-AKT signaling pathway, and progesterone mediated oocyte maturation. The protein-protein network (PPI) was established and module analysis was carried out using STRING and Cytoscape. Next, with PPI network analyzed by four topological methods in Cytohubba plugin of Cytoscape, 6 overlapping genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) were eventually selected. GEPIA and Oncomine were implemented for validating the gene expression and all the six hub genes were highly expressed in OC specimens compared to normal OV tissues. Furthermore, 5 of 6 genes except for DTL were associated with worse prognosis using Kaplan Meier-plotter online tool and 3 of 6 genes were significantly related to clinical stages, including RRM2, DTL, and KIF15. Additionally, cBioPortal showed that TOP2A and RRM2 were the targets of cancer drugs in patients with OC, indicating the other four genes may also be potential drug targets. CONCLUSION: Six hub genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) present promising predictive value for the development and prognosis of OC and may be used as candidate targets for diagnosis and treatment of OC.

背景：卵巢癌（OC）是妇科恶性肿瘤中致死率最高的疾病。大多数 OC 患者在晚期被诊断出来，仅有不到 40%的女性得到治愈。然而，肿瘤发生的可能机制和候选生物标志物仍有待进一步阐明。

结果：从基因表达综合数据库（GEO）中获取了 GSE18520、GSE54388 和 GSE27651 三个数据集，其中包含 91 例 OC 样本和 22 例正常卵巢（OV）组织。通过 GEO2R 和在线 Venn 软件筛选出 OC 组织与 OV 组织之间的 349 个差异表达基因（DEGs），随后进行 KEGG 通路和基因本体（GO）富集分析。这些 DEGs 的富集功能和通路包括雄性性腺发育、细胞对转化生长因子 β 刺激的反应、RNA 聚合酶 II 启动子转录的正调控、钙非依赖性质膜细胞黏附分子细胞间黏附、细胞外基质组织、癌症通路、细胞周期、细胞黏附分子、PI3K-AKT 信号通路和孕激素介导的卵母细胞成熟。使用 STRING 和 Cytoscape 建立蛋白质-蛋白质网络（PPI）并进行模块分析。接下来，通过 Cytoscape 插件 Cytohubba 中的 4 种拓扑方法分析 PPI 网络，最终选择了 6 个重叠基因（DTL、DLGAP5、KIF15、NUSAP1、RRM2 和 TOP2A）。通过 GEPIA 和 Oncomine 验证基因表达，发现所有 6 个核心基因在 OC 标本中的表达均高于正常 OV 组织。此外，使用 Kaplan Meier-plotter 在线工具，除 DTL 外的 5 个基因与预后不良相关，并且 3 个基因与临床分期显著相关，包括 RRM2、DTL 和 KIF15。此外，cBioPortal 显示 TOP2A 和 RRM2 是 OC 患者癌症药物的靶点，表明其他四个基因也可能是潜在的药物靶点。

结论：6 个核心基因（DTL、DLGAP5、KIF15、NUSAP1、RRM2 和 TOP2A）对 OC 的发生和预后具有良好的预测价值，可作为 OC 诊断和治疗的候选靶点。