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Updated: Mar 30, 2026

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
Stroma-associated master regulators of molecular subtypes predict patient prognosis in ovarian cancer
Shengzhe Zhang1,2, Ying Jing1, Meiying Zhang3,4
1State Key Laboratory of Oncogenes and Related Genes, Renji-Med X Clinical Stem Cell Research Center, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Abstract:
High-grade serous ovarian carcinoma (HGS-OvCa) has the lowest survival rate among all gynecologic cancers and is hallmarked by a high degree of heterogeneity. The Cancer Genome Atlas network has described a gene expression-based molecular classification of HGS-OvCa into Differentiated, Mesenchymal, Immunoreactive and Proliferative subtypes. However, the biological underpinnings and regulatory mechanisms underlying the distinct molecular subtypes are largely unknown. Here we showed that tumor-infiltrating stromal cells significantly contributed to the assignments of Mesenchymal and Immunoreactive clusters. Using reverse engineering and an unbiased interrogation of subtype regulatory networks, we identified the transcriptional modules containing master regulators that drive gene expression of Mesenchymal and Immunoreactive HGS-OvCa. Mesenchymal master regulators were associated with poor prognosis, while Immunoreactive master regulators positively correlated with overall survival. Meta-analysis of 749 HGS-OvCa expression profiles confirmed that master regulators as a prognostic signature were able to predict patient outcome. Our data unraveled master regulatory programs of HGS-OvCa subtypes with prognostic and potentially therapeutic relevance, and suggested that the unique transcriptional and clinical characteristics of ovarian Mesenchymal and Immunoreactive subtypes could be, at least partially, ascribed to tumor microenvironment.
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