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Published on: January 12, 2020
Identification of key genes for guiding chemotherapeutic management in ovarian cancer using translational
Danni Yuan1, Haohan Zhou1, Hongyu Sun1
1Key Laboratory of Pathobiology, Department of Pathophysiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, Changchun, Jilin 130021, P.R. China.
Abstract:
The emergence of resistance to chemotherapy drugs in patients with ovarian cancer is still the main cause of low survival rates. The present study aimed to identify key genes that may provide treatment guidance to reduce the incidence of drug resistance in patients with ovarian cancer. Original data of chemotherapy sensitivity and chemoresistance of ovarian cancer were obtained from the Gene Expression Omnibus dataset GSE73935. Differentially expressed genes (DEGs) between sensitive and resistant ovarian cancer cell lines were screened by Empirical Bayes methods. Overlapping DEGs between four chemoresistant groups were identified by Venn map analysis. Protein-protein interaction networks were also constructed, and hub genes were identified. The hub genes were verified by in vitro experiments as well as The Cancer Genome Atlas data. Results from the present study identified eight important genes that may guide treatment decisions regarding chemotherapy regimens for ovarian cancer, including epidermal growth factor-like repeats and discoidin I-like domains 3, NRAS proto-oncogene, hyaluronan and proteoglycan link protein 1, activated protein C receptor, CD53, cyclin-dependent kinase inhibitor 2A, insulin-like growth factor 1 receptor and roundabout guidance receptor 2 genes. Their expressions were found to have an impact on the prognosis of different treatment groups (cisplatin, paclitaxel, cisplatin + paclitaxel, cisplatin + doxorubicin and cisplatin + topotecan). The results indicated that these genes may minimise the occurrence of ovarian cancer drug resistance and may provide effective treatment options for patients with ovarian cancer.
Insights
Identifying key genes can help reduce chemotherapy drug resistance in ovarian cancer patients. This study found eight genes impacting treatment prognosis, potentially improving patient outcomes and minimizing resistance.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Ovarian cancer drug resistance significantly lowers patient survival rates.
- Identifying molecular targets is crucial for overcoming treatment resistance.
Purpose of the Study:
- To identify key genes associated with chemotherapy resistance in ovarian cancer.
- To provide potential therapeutic guidance for improving ovarian cancer treatment outcomes.
Main Methods:
- Analyzed Gene Expression Omnibus dataset GSE73935 for differentially expressed genes (DEGs) between sensitive and resistant ovarian cancer cell lines.
- Utilized Venn map analysis and protein-protein interaction networks to identify overlapping DEGs and hub genes.
- Validated hub genes through in vitro experiments and The Cancer Genome Atlas (TCGA) data.
Main Results:
- Eight significant genes were identified, including EGFR-like repeats and discoidin I-like domains 3, NRAS, HAPLN1, PROCR, CD53, CDKN2A, IGF1R, and ROBO2.
- Gene expression levels correlated with patient prognosis across various chemotherapy regimens (cisplatin, paclitaxel, etc.).
Conclusions:
- The identified genes may serve as biomarkers to predict and potentially overcome ovarian cancer drug resistance.
- These findings offer a basis for developing more effective chemotherapy strategies for ovarian cancer patients.
