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Updated: Dec 7, 2025
Evaluation of Stem Cell Properties in Human Ovarian Carcinoma Cells Using Multi and Single Cell-based Spheres Assays
Published on: January 3, 2015
Bioinformatics analysis and verification of molecular targets in ovarian cancer stem-like cells
Abhijeet Behera1, Rahail Ashraf1, Amit Kumar Srivastava2
1Division of Biology, Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati, Andhra Pradesh, India.
Background:
Epithelial ovarian cancer (EOC) is a lethal and aggressive gynecological malignancy. Despite recent advances, existing therapies are challenged by a high relapse rate, eventually resulting in disease recurrence and chemoresistance. Emerging evidence indicates that a subpopulation of cells known as cancer stem-like cells (CSLCs) exists with non-tumorigenic cancer cells (non-CSCs) within a bulk tumor and is thought to be responsible for tumor recurrence and drug-resistance. Therefore, identifying the molecular drivers for cancer stem cells (CSCs) is critical for the development of novel therapeutic strategies for the treatment of EOC.
Methods:
Two gene datasets were downloaded from the Gene Expression Omnibus (GEO) database based on our search criteria. Differentially expressed genes (DEGs) in both datasets were obtained by the GEO2R web tool. Based on log2 (fold change) >2, the top thirteen up-regulated genes and log2 (fold change) < -1.5 top thirteen down-regulated genes were selected, and the association between their expressions and overall survival was analyzed by OncoLnc web tool. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathways analysis, and protein-protein interaction (PPI) networks were performed for all the common DEGs found in both datasets. SK-OV-3 cells were cultured in an adherent culture medium and spheroids were generated in suspension culture with CSCs specific medium. RNA from both cell population was extracted to validate the selected DEGs expression by q-PCR. Growth inhibition assay was performed in SK-OV-3 cells after carboplatin treatment.
Results:
A total of 200 DEGs, 117 up-regulated and 83 down-regulated genes were commonly identified in both datasets. Analysis of pathways and enrichment tests indicated that the extracellular matrix part, cell proliferation, tissue development, and molecular function regulation were enriched in CSCs. Biological pathways such as interferon-alpha/beta signaling, molecules associated with elastic fibers, and synthesis of bile acids and bile salts were significantly enriched in CSCs. Among the top 13 up-regulated and down-regulated genes, MMP1 and PPFIBP1 expression were associated with overall survival. Higher expression of ADM, CXCR4, LGR5, and PTGS2 in carboplatin treated SK-OV-3 cells indicate a potential role in drug resistance.
Conclusions:
The molecular signature and signaling pathways enriched in ovarian CSCs were identified by bioinformatics analysis. This analysis could provide further research ideas to find the new mechanism and novel potential therapeutic targets for ovarian CSCs.
Insights
This study identifies key genes and pathways in ovarian cancer stem-like cells (CSLCs), crucial for understanding tumor recurrence and chemoresistance. Findings offer potential new therapeutic targets for epithelial ovarian cancer (EOC).
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Epithelial ovarian cancer (EOC) is a lethal malignancy with high relapse rates.
- Cancer stem-like cells (CSLCs) are implicated in EOC recurrence and chemoresistance.
- Identifying molecular drivers of CSLCs is critical for novel therapeutic strategies.
Purpose of the Study:
- To identify the molecular signature and enriched signaling pathways in ovarian CSLCs.
- To uncover potential therapeutic targets for EOC treatment.
Main Methods:
- Downloaded and analyzed two Gene Expression Omnibus (GEO) datasets using GEO2R.
- Identified differentially expressed genes (DEGs) and analyzed their association with overall survival.
- Performed Gene Ontology (GO), KEGG, Reactome pathway, and protein-protein interaction (PPI) network analyses.
- Validated key DEGs in SK-OV-3 cells and assessed their role in carboplatin resistance.
Main Results:
- Identified 200 common DEGs (117 up-regulated, 83 down-regulated) between datasets.
- Enriched pathways in CSLCs include extracellular matrix, cell proliferation, tissue development, and molecular function regulation.
- Interferon-alpha/beta signaling, elastic fibers, and bile acid synthesis pathways were significantly enriched in CSLCs.
- MMP1 and PPFIBP1 expression correlated with overall survival; ADM, CXCR4, LGR5, and PTGS2 expression linked to carboplatin resistance.
Conclusions:
- Bioinformatics analysis revealed a distinct molecular signature and signaling pathways in ovarian CSLCs.
- These findings provide a foundation for further research into mechanisms of ovarian CSCs.
- Identified potential novel therapeutic targets for targeting ovarian CSLCs and overcoming chemoresistance.
