Pan Xue, Chen Ying, Gao Song
Department of Gynecological Tumors, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Department of Ultrasound, Jiangnan Hospital Affiliated to Zhejiang University of Traditional Chinese Medicine, Hangzhou, Zhejiang, China.
Cancer Biomark. 2020;29(2):169-178. doi: 10.3233/CBM-191162.
Ovarian cancer is the common tumor in female, the prognostic of which is influenced by a series of factors. In this study, 4 genes relevant to pathological grade in ovarian cancer were screened out by the construction of weighted gene co-expression network analysis.
GSE9891 with 298 ovarian cancer cases had been used to construct co-expression networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses was used to analyze the possible mechanism of genes involved in the malignant process of ovarian cancer. Hub genes were validated in other independent datasets, such as GSE63885, GSE26193 and GSE30161. Survival analysis based on the hub genes was performed by website of Kaplan Meier-plotter.
The result based on weighted gene co-expression network analysis indicated that turquoise module has the highest association with pathological grade. Gene Ontology enrichment analysis revealed that the genes in turquoise module main enrichment in inflammatory response and immune response. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that the genes in turquoise module main enrichment in cytokine-cytokine receptor interaction and chemokine signaling pathway. In turquoise module, a total of 4 hub genes (MS4A4A, CD163, CPR65, MS4A6A) were identified. Then, 4 hub genes were effectively verified in the test datasets (GSE63885, GSE26193 and GSE30161) and tissue samples from Shengjing Hospital of China Medical University. Survival analysis indicated that the 4 hub genes were associated with poor progression-free survival of ovarian cancer.
In conclusion, 4 hub genes (MS4A4A, CD163, CPR65, MS4A6A) were verified associated with pathological grade of ovarian cancer. Moreover, MS4A4A, CD163, MS4A6A may serve as a surface marker for M2 macrophages. Targeting the 4 hub genes may can improve the prognosis of ovarian cancer.
卵巢癌是女性常见肿瘤，其预后受一系列因素影响。本研究通过构建加权基因共表达网络分析筛选出4个与卵巢癌病理分级相关的基因。
使用包含298例卵巢癌病例的GSE9891构建共表达网络。采用基因本体论和京都基因与基因组百科全书富集分析来分析参与卵巢癌恶性过程的基因的可能机制。在其他独立数据集如GSE63885、GSE26193和GSE30161中验证枢纽基因。通过Kaplan Meier-plotter网站基于枢纽基因进行生存分析。
基于加权基因共表达网络分析的结果表明，绿松石模块与病理分级的关联度最高。基因本体论富集分析显示，绿松石模块中的基因主要富集于炎症反应和免疫反应。京都基因与基因组百科全书富集分析显示，绿松石模块中的基因主要富集于细胞因子-细胞因子受体相互作用和趋化因子信号通路。在绿松石模块中，共鉴定出4个枢纽基因（MS4A4A、CD163、CPR65、MS4A6A）。然后，在测试数据集（GSE63885、GSE26193和GSE30161）以及中国医科大学盛京医院的组织样本中有效验证了这4个枢纽基因。生存分析表明，这4个枢纽基因与卵巢癌无进展生存期差相关。
总之，验证了4个枢纽基因（MS4A4A、CD163、CPR65、MS4A6A）与卵巢癌病理分级相关。此外，MS4A4A、CD163、MS4A6A可能作为M2巨噬细胞的表面标志物。靶向这4个枢纽基因可能改善卵巢癌的预后。
