Proteomic profiling and molecular reclassification of high-grade serous ovarian cancer identifies prognostic subtypes and immunotherapy biomarkers

作者：Mengyan Tu, Sangsang Tang, Qiao Zhang, Tianchen Guo, Yixuan Cen, Xiaomeng Xu, Shenglong Wu, Xin Chen, Weiguo Lu, Chen Ding, Junfen Xu · 发表于：EBioMedicine · 年份：2026 · DOI：10.1016/j.ebiom.2026.106248 · 被引用次数：1 · 研究领域：Advanced Proteomics Techniques and Applications、Cancer Immunotherapy and Biomarkers、Ferroptosis and cancer prognosis

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most lethal histological subtype of ovarian cancer, exhibiting significant heterogeneity and limited therapeutic options. A comprehensive characterisation of proteomic landscape across disease stages is needed to identify actionable biomarkers and therapeutic targets. METHODS: We performed proteomic profiling of 116 primary HGSOC tumours, followed by integrative bioinformatics analyses incorporating clinical annotation. Key findings were validated using multiplex immunohistochemistry, in vitro and in vivo functional assays, and external datasets. FINDINGS: We identified FIGO stage IIA as a crucial turning point distinguishing early-from advanced-stage disease, marked by a transition from oxidative stress to cell cycle-driven programmes. Trajectory analysis of tumour progression revealed GOSR2 as a key regulator of stage transition. Mechanistically, GOSR2 interacted with SEC24D to inhibit the secretion of CXCL9 and CXCL12, resulting in reduced CD8+ T cell infiltration. Unsupervised clustering defined three reproducible proteomic subtypes (S-I to S-III), which were validated in TCGA and single-cell transcriptomic datasets and associated with distinct clinical outcomes. The S-III subtype was characterised by ECM-receptor interaction, immune evasion, and poor prognosis. Transcription factors network analysis identified regulators potentially driving these phenotypes. In parallel, three immune-contexture subtypes (IC1-IC3...