Chang Xiaoying, Li Dan, Liu Chang, Zhang Zhe, Wang Tao
Department of Pathology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping, Shenyang, 110004, China.
Department of Pathology, Shenyang KingMed Center for Clinical Laboratory Co., Ltd, Shenyang, 110164, China.
Cancer Cell Int. 2021 Apr 6;21(1):193. doi: 10.1186/s12935-021-01854-7.
Ovarian epithelial cancer is one of the leading malignant tumors in gynecology and lacks effective diagnostic and prognostic markers. Our study aims to screen and verify ovarian epithelial cancer biomarkers.
GSE18520 and GSE26712 were downloaded from the GEO database. The "limma" and "WGCNA" packages were used to explore hub genes. The Kaplan-Meier Plotter database was used for survival analysis of the hub genes. Immunohistochemical analysis was used to identify the expression level of Pentraxin 3 in ovarian epithelial cancer samples.
In this study, we integrated and analyzed two datasets, GSE18520 and GSE26712, and a total of 238 differentially expressed genes (DEGs) were screened out. Enrichment analysis showed that these DEGs were related to collagen-containing extracellular matrix and other pathways. Further application of WGCNA (weighted gene coexpression network analysis) identified 15 gene modules, with the purple module showing the highest correlation with ovarian epithelial cancer. Twenty-five genes were shared between the purple module and DEGs, 13 genes were related to the prognosis of ovarian epithelial cancer patients, and the PTX3 gene had the highest hazardous risk (HR) value. We performed immunohistochemical analyses on the 255 Pentraxin-3 (PTX3)-based clinical samples. PTX3 was found to be overexpressed in ovarian epithelial cancer and related to the degree of differentiation. The Cox proportional hazard model indicates that high PTX3 expression is an independent risk factor for the prognosis of ovarian epithelial cancer patients.
In conclusion, through WGCNA and a series of comprehensive bioinformatics analyses, PTX3 was first identified as a novel diagnostic and prognostic biomarker for ovarian epithelial cancer.
卵巢上皮癌是妇科主要恶性肿瘤之一,缺乏有效的诊断和预后标志物。本研究旨在筛选并验证卵巢上皮癌生物标志物。
从基因表达综合数据库(GEO数据库)下载GSE18520和GSE26712数据集。使用“limma”和“WGCNA”软件包探索枢纽基因。利用Kaplan-Meier Plotter数据库对枢纽基因进行生存分析。采用免疫组织化学分析确定卵巢上皮癌样本中五聚体3的表达水平。
在本研究中,我们整合并分析了两个数据集GSE18520和GSE26712,共筛选出238个差异表达基因(DEGs)。富集分析表明,这些差异表达基因与含胶原蛋白的细胞外基质等途径相关。进一步应用加权基因共表达网络分析(WGCNA)确定了15个基因模块,其中紫色模块与卵巢上皮癌的相关性最高。紫色模块和差异表达基因之间共有25个基因,13个基因与卵巢上皮癌患者的预后相关联,且五聚体3(PTX3)基因的风险比(HR)值最高。我们对255份基于五聚体3(PTX3)的临床样本进行了免疫组织化学分析。结果发现,PTX3在卵巢上皮癌中过表达,且与分化程度相关。Cox比例风险模型表明,PTX3高表达是卵巢上皮癌患者预后的独立危险因素。
总之,通过WGCNA和一系列综合生物信息学分析,首次确定PTX3为卵巢上皮癌一种新的诊断和预后生物标志物。