[通过加权基因共表达网络分析鉴定具有卵巢癌干细胞特性的关键基因]

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

作者信息

Luo Meng, Zeng Hao, Ma Xin-Yu, Ma Xue-Lei

机构信息

Department of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China.

State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China.

出版信息

Sichuan Da Xue Xue Bao Yi Xue Ban. 2021 Mar;52(2):248-258. doi: 10.12182/20210360205.

DOI:10.12182/20210360205

PMID:33829699

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10408925/

Abstract

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 pRRophetic. 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 G2M 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 ( <0.05). qRT-PCR confirmed that seven key genes ( 1, 20, 2, 5, 4 , 2, 1) in the WGCNA results were highly expressed in ovarian cancer stem cells, and 1 might have played a core role.

CONCLUSION

Seven hub genes, especially 1, were identified by constructing gene co-expression network, which may become potential biomarkers of ovarian cancer gene.

摘要

目的

探讨干性相关基因在卵巢癌诊断和治疗中的意义。

方法

采用加权基因共表达网络分析（WGCNA）鉴定关键模块和基因。通过基因集富集分析（GSEA）和单细胞测序数据分析关键基因高表达的信号通路。用pRRophetic评估卵巢癌对化疗药物的化疗敏感性。采用流式细胞术检测SKOV3细胞和癌干细胞中CD44、CD117的表达。通过qRT-PCR验证卵巢癌干细胞中关键基因的表达。通过GeneMANIA分析鉴定核心基因。

结果

根据WGCNA结果，在转录水平鉴定出15个关键基因，均在多种肿瘤中高表达。它们参与细胞周期、DNA修复、E2靶标和G2M检查点通路，且与化疗敏感性显著相关。SKOV3细胞和卵巢癌干细胞中CD44、CD117双阳性细胞的比例分别为（1.20±0.34）%和（37.17±1.80）%，差异有统计学意义（P<0.05）。qRT-PCR证实WGCNA结果中的7个关键基因（1、20、2、5、4、2、1）在卵巢癌干细胞中高表达，且1可能发挥核心作用。