Translational oncology · 2026
Integrative transcriptomics and single-cell analysis identify SIX4 as a candidate epithelial target in ovarian cancer and PCOS-associated ovarian dysregulation.
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Li Xuan, Chen Gaowen, Wang Yifeng, Ha Chunfang
Аннотация
PURPOSE: Ovarian cancer is a heterogeneous solid tumor, whereas polycystic ovary syndrome (PCOS) is a distinct endocrine-metabolic ovarian disorder. Whether PCOS-associated ovarian dysregulation and ovarian cancer share convergent transcriptomic candidates remains unclear. This study aimed to identify shared transcriptomic candidates and define their cellular localization without implying a causal or clinical comorbidity relationship.
MATERIALS AND METHODS: Public bulk transcriptomic datasets from PCOS and ovarian cancer underwent platform-specific preprocessing, within-disease-arm harmonization, differential-expression analysis, robust rank aggregation, and machine-learning-based feature prioritization with SHapley Additive exPlanations. Single-cell RNA sequencing datasets were used to localize prioritized genes in PCOS-related ovarian cell populations and high-grade serous ovarian cancer (HGSOC)-derived compartments. Preliminary validation used DHEA-treated KGN cells and siRNA-mediated SIX4 knockdown in SKOV3 cells. Exploratory docking and molecular dynamics simulation assessed the structural tractability of a SIX4-centered axis.
RESULTS: Integrated analysis identified shared molecular dysregulation enriched in cell-cycle regulation, chromosome segregation, epithelial remodeling, and Wnt-related pathways. Five candidate genes were prioritized: SIX4, CCNE1, MMP7, KIF2C, and GPX3. SIX4 was the highest-ranked contributor within the computational model. Single-cell analysis showed compartment-specific localization, with SIX4 enriched in HGSOC-derived epithelial populations. DHEA increased SIX4 expression in KGN cells, whereas SIX4 knockdown suppressed SKOV3 proliferation, migration, and colony formation. Molecular dynamics suggested stable predicted engagement between SIX4 and a Benzbromarone-related scaffold.
CONCLUSION: This study identifies SIX4 as a candidate epithelial target in ovarian cancer within a shared, noncausal transcriptomic program associated with PCOS-related ovarian dysregulation.
MATERIALS AND METHODS: Public bulk transcriptomic datasets from PCOS and ovarian cancer underwent platform-specific preprocessing, within-disease-arm harmonization, differential-expression analysis, robust rank aggregation, and machine-learning-based feature prioritization with SHapley Additive exPlanations. Single-cell RNA sequencing datasets were used to localize prioritized genes in PCOS-related ovarian cell populations and high-grade serous ovarian cancer (HGSOC)-derived compartments. Preliminary validation used DHEA-treated KGN cells and siRNA-mediated SIX4 knockdown in SKOV3 cells. Exploratory docking and molecular dynamics simulation assessed the structural tractability of a SIX4-centered axis.
RESULTS: Integrated analysis identified shared molecular dysregulation enriched in cell-cycle regulation, chromosome segregation, epithelial remodeling, and Wnt-related pathways. Five candidate genes were prioritized: SIX4, CCNE1, MMP7, KIF2C, and GPX3. SIX4 was the highest-ranked contributor within the computational model. Single-cell analysis showed compartment-specific localization, with SIX4 enriched in HGSOC-derived epithelial populations. DHEA increased SIX4 expression in KGN cells, whereas SIX4 knockdown suppressed SKOV3 proliferation, migration, and colony formation. Molecular dynamics suggested stable predicted engagement between SIX4 and a Benzbromarone-related scaffold.
CONCLUSION: This study identifies SIX4 as a candidate epithelial target in ovarian cancer within a shared, noncausal transcriptomic program associated with PCOS-related ovarian dysregulation.