加权基因共表达网络分析在鉴定卵巢癌干细胞特性关键基因的应用

Identification of Hub Genes for Ovarian Cancer Stem Cell Properties with Weighted Gene Co-expression Network Analysis

目的探讨关键干细胞特性基因在卵巢癌的诊断和治疗中的意义。方法加权基因共表达网络分析(WGCNA)方法筛选出关键模块和基因;基因集富集分析(GSEA)和单细胞测序数据分析关键基因上调组高表达的信号通路;pRRophetic预测卵巢癌的化疗药物的敏感性;流式细胞术检测SKOV3细胞和肿瘤干细胞中CD44及CD117的表达情况;实时荧光定量(qRT)-PCR证实关键基因在卵巢癌干细胞中的表达;GeneMANIA分析鉴定出核心基因。结果WGCNA结果显示在转录水平上筛选出15个关键基因,其在多种肿瘤中高表达,参与细胞周期、DNA修复、E2靶点和G2M检查点通路,且与化疗药物敏感性有显著的关联性。CD44+CD117+细胞在SKOV3细胞和卵巢癌干细胞中的比例分别为(1.20±0.34)%、(37.17±1.80)%,差异有统计学意义(P<0.05)。qRT-PCR证实WGCNA结果中7个关键基因(BUB1、CDC20、CCNB2、DLGAP5、KIF4A、NEK2、NUSAP1)在卵巢癌干细胞中高表达,并且BUB1可能起着核心的作用。结论本研究通过构建基因共表达网络筛选出7个干细胞特性关键基因,尤其是BUB1,可能成为潜在的卵巢癌基因生物标志物。

Objective To investigate the significance of stemness-related genes in the diagnosis and treatment of ovarian cancer.Methods Key modules and genes were identified with weighted gene co-expression network analysis(WGCNA).The signal pathways of high expression of key genes were analyzed by gene set enrichment analysis(GSEA)and single cell sequencing data.The chemosensitivity of ovarian cancer to chemotherapy drugs was estimated with p RRophetic.Flow cytometry was used to examine the expression of CD44+CD117+in SKOV3 cells and cancer stem cells.The expression of key genes in ovarian cancer stem cells was confirmed by qRT-PCR.The core genes were identified by GeneMANIA analysis.Results According to the WGCNA results,15 key genes were identified at the transcription level,all being highly expressed in many kinds of tumors.They were involved in the cell cycle,DNA repair,E2 target and G2 M checkpoint pathway,and had significant correlation with chemosensitivity.The proportion of CD44+CD117+cells in SKOV3 cells and ovarian cancer stem cells were(1.20±0.34)%and(37.17±1.80)%respectively,with statistically significant difference(P<0.05).qRT-PCR confirmed that seven key genes(BUB1,CDC20,CCNB2,DLGAP5,KIF4 A,NEK2,NUSAP1)in the WGCNA results were highly expressed in ovarian cancer stem cells,and BUB1 might have played a core role.Conclusion Seven hub genes,especially BUB1,were identified by constructing gene co-expression network,which may become potential biomarkers of ovarian cancer gene.