Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches

Abstract

Background Ovarian cancer is the second fatal malignancy of the female reproductive system. Based on the cancer stem cell (CSC) theory, its poor prognosis of ovarian cancer attributed to tumor recurrence caused by CSCs. A variety of cell surface-specific markers have been employed to identify ovarian cancer stem cells (OCSCs). In this study, we attempted to explore the common feature in ovarian cancer stem cells sorted by multiple approaches. Methods We collected the gene expression profiles of OCSCs were from 5 public cohorts and employed R software and Bioconductor packages to establish differently expressed genes (DEGs) between OCSCs and parental cells. We extracted the integrated DEGs by protein-protein interaction (PPI) network construction and explored potential treatment by the Cellminer database. Results We identified and integrated the DEGs of OCSCs sorted by multiple isolation approaches. Besides, we identified OCSCs share characteristics in the lipid metabolism and extracellular matrix changes. Moreover, we obtained 16 co-expressed core genes, such as FOXQ1, MMP7, AQP5, RBM47, ETV4, NPW, SUSD2, SFRP2, IDO1, ANPEP, CXCR4, SCNN1A, SPP1 and IFI27 (upregulated) and SERPINE1, DUSP1, CD40, and IL6 (downregulated). Through correlation analysis, we screened out ten potential drugs to target the core genes. Conclusion Based on the comprehensive analysis of the genomic datasets with different sorting methods of OCSCs, we figured out the common driving genes to regulating OCSC and obtained ten new potential therapies for eliminating ovarian cancer stem cells. Hence, the findings of our study might have potential clinical significance.

Prediction of Key Candidate Genes for Platinum Resistance in Ovarian Cancer

“…Researchers have observed through a series of basic experiments that the overexpression of IFI27 induced epithelial-mesenchymal transition and promoted the migration, invasion, tumorigenicity, stemness and drug resistance of epithelial ovarian cancer cells. 10 In addition, some scientists have collected the gene expression profiles of ovarian cancer stem cells from 5 public cohorts, and obtained IFI27 (up-regulated), one of the core genes that co-expressed using bioinformatics methods, 15 and pointed out that IFI27 belongs to one of the most widely up-regulated genes in cancer, and is involved in apoptosis, metabolism, cell cycle, tumor growth and suppression. 16 Kim et al have used RT-PCR based on the annealing controlled primer system to identify differentially expressed genes in patients with stage III serous ovarian cancer, and found IFI27 was up-regulated in most stage III patients.…”

Landscape of Metabolite-Protein Interaction Networks Reveals Prognostic Subtypes of Ovarian Cancer

“…After comprehensive consideration, 5 genes were ltered to construct the MPIscore model. Speci cally, C1QTNF3 is a novel adipokine that regulates hepatic glucose output [36] and was found to be upregulated in bowel metastasis samples compared with primary samples in OV [37]; SFRP2 is correlated with recurrence and overall survival outcomes [38] and is upregulated in stem cells of OV [39]; FZD1 is an independent prognosticator in OV [40]; CILP2 plays an important role in regulating hepatic glucose production [41], and its overexpression correlates with tumour progression and poor prognosis in colorectal cancer patients [42], and high expression of MFAP4 predicts primary platinum-based chemoresistance and is associated with adverse prognosis in serous ovarian cancer patients [43]. Subsequently, the performance and effectiveness of the MPIscore in survival prediction were tested and con rmed by the TCGA-OV and GEO validation datasets, suggesting that a high MPIscore acted as an independent prognostic factor and is associated with poor prognosis.…”

SCNN1A Overexpression Correlates with Poor Prognosis and Immune Infiltrates in Ovarian Cancer

“…In ovarian cancer, whether SCNN1A is involved in tumor progression and tumor immunity remains to be studied. Although some studies have found that SCNN1A is overexpression and is a potential biomarker of OV, 12 , 25 the prognostic value and the potential function of SCNN1A in OV were unclear and not fully understood.…”