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Werner L, Ittner E, Swenson H, Rönnerman EW, Mateoiu C, Kovács A, Dahm-Kähler P, Karlsson P, Thorsell A, Rekabdar E, Esmaeili P, Levander F, Forssell-Aronsson E, Tullberg AS, Saed G, Parris TZ, Helou K
Mol Ther Oncol 33 (3) 201019 [2025-09-18; online 2025-07-16]
Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy, yet clinical tools for diagnosis, prognosis, and treatment remain limited, and molecular profiling of histotypes is lacking. Here, we leverage proteomic data to further stratify four main EOC histotypes, borderline (BL) and benign (B) tumors, and identify candidate prognostic and diagnostic biomarkers. Using proteomic data from 300 patient samples, we identified differentially abundant proteins (DAPs) such as SNCG, S100A1, VWA2, AGR2, CTH, and SPINK1 and biomarker panels to stratify the tissues. Enrichment of biological processes profiled histotypes and involvement of DAPs. Survival analysis identified candidate biomarkers predicting overall- and disease-specific survival with histotype-specificity. Of these, GLYR1, RPL12, GDPGP1, and POLR2M were associated with favorable outcomes, while SDF4, PPP3CC, EIF2AK2, and STX6 were linked to unfavorable outcomes. Collectively, these findings provide histotype-specific attributes for known and EOC biomarkers that may serve as clinical tools for EOC diagnosis and treatment decisions.
Glycoproteomics and MS Proteomics [Collaborative]
PubMed 40778374
DOI 10.1016/j.omton.2025.201019
Crossref 10.1016/j.omton.2025.201019
pmc: PMC12328698
pii: S2950-3299(25)00088-8