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Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression
Published on: August 28, 2012
Single-Cell-Derived Malignant Epithelial Programs Define Prognostic Risk and Therapeutic Vulnerability in Ovarian
Jingwen Si1, Hanbo Li1, Han Zhang2
1Department of Pathology, Tianjin Central Hospital of Gynecology Obstetrics, Tianjin, China.
Journal of Cancer
|July 29, 2026
Summary
This study uses single-cell RNA sequencing to reveal ovarian cancer cell diversity and create a nine-gene prognostic model. This model accurately predicts patient outcomes and identifies PSMB1 as a potential therapeutic target for ovarian cancer.
Area of Science:
- Genomics
- Oncology
- Bioinformatics
Background:
- Ovarian cancer (OV) presents significant intratumoral heterogeneity and poor prognosis, with limited biomarkers for risk stratification.
- Bulk transcriptomic models often fail to capture the cellular origins of prognostic signals.
- Single-cell RNA sequencing (scRNA-seq) offers a powerful approach to dissect malignant epithelial diversity and identify predictive biomarkers.
Purpose of the Study:
- To construct a comprehensive epithelial landscape of ovarian cancer using integrated single-cell transcriptomic data.
- To develop and validate a prognostic model based on single-cell-derived gene signatures.
- To explore the biological and clinical relevance of the findings, including identifying potential therapeutic targets.
Main Methods:
- Integrated scRNA-seq datasets to map the epithelial landscape of ovarian cancer.
- Utilized inferCNV, Slingshot, and Monocle3 for cell identification and trajectory analysis.
- Developed a nine-gene risk model using Cox regression and LASSO on bulk RNA-seq cohorts, validated across multiple independent datasets.
Main Results:
- Identified distinct malignant epithelial subpopulations with unique evolutionary trajectories and differential clinical outcomes.
- The nine-gene risk model demonstrated robust prognostic performance and correlated with tumor progression, immune suppression, and reduced therapeutic sensitivity.
- PSMB1 was identified as a key oncogenic factor, with its knockdown inhibiting OV cell proliferation and colony formation.
Conclusions:
- Established a single-cell-informed prognostic framework for ovarian cancer, linking epithelial heterogeneity to clinical outcomes and treatment response.
- The proposed model offers biologically interpretable risk stratification for ovarian cancer.
- Highlighted PSMB1 as a potential therapeutic target, advancing precision oncology for ovarian cancer.
