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

  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 (P<0.05). qRT-PCR confirmed that seven key genes (BUB1, CDC20, CCNB2, DLGAP5, KIF4A, 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.