Volume 45 Issue 4
Apr.  2024
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Lizhu ZHAO, Ying DONG, Yue DENG, Lihua YANG. Correlation between Epithelial Cell Related Genes and Prognosis of Patients with Ovarian Cancer based on Single Cell Sequencing[J]. Journal of Kunming Medical University, 2024, 45(4): 9-16. doi: 10.12259/j.issn.2095-610X.S20240402
Citation: Lizhu ZHAO, Ying DONG, Yue DENG, Lihua YANG. Correlation between Epithelial Cell Related Genes and Prognosis of Patients with Ovarian Cancer based on Single Cell Sequencing[J]. Journal of Kunming Medical University, 2024, 45(4): 9-16. doi: 10.12259/j.issn.2095-610X.S20240402

Correlation between Epithelial Cell Related Genes and Prognosis of Patients with Ovarian Cancer based on Single Cell Sequencing

doi: 10.12259/j.issn.2095-610X.S20240402
  • Received Date: 2024-01-04
    Available Online: 2024-03-22
  • Publish Date: 2024-04-29
  •   Objective  To construct a polygenic risk score based on the expression of epithelial cell markers to evaluate the prognosis of patients with ovarian cancer.   Methods  The single cell sequencing data of ovarian cancer were reduced and clustered to identify epithelial cell markers, malignant and non-malignant markers. Regression analysis was used to screen epithelial marker genes related to prognosis to construct a risk score model. Based on the risk score, patients were divided into high risk group and low risk group (H.Risk, L.Risk) to predict the prognosis of patients with ovarian cancer.  Results  A risk scoring model with four genes (EPCAM, CLDN4, CXCR4 and TIMP3) was constructed. Survival analysis showed that the OS of patients in H.Risk group was worse than that in L.Risk group in trial cohort and verification cohort (P < 0.05). Pathway enrichment analysis showed that the differential genes between high and low risk groups were associated with immunosuppression and malignant progression, including cell adhesion, extracellular matrix, neuroactive ligand-receptor interaction, calcium signal pathway, transforming growth factor-β.  Conclusion  Through the comprehensive analysis of bulkRNA-seq and scRNA-seq data, a risk scoring model based on epithelial cell subsets marker genes is proposed, which may provide potential therapeutic targets for patients with ovarian cancer.
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