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Ovarian cancer remains the most lethal gynecological malignancy. Ferroptosis, a specialized form of iron-dependent, nonapoptotic cell death, plays a crucial role in various cancers. However, the contribution of ferroptosis to ovarian cancer is poorly understood. Here, we characterized the diagnostic, prognostic, and therapeutic value of ferroptosis-related genes in ovarian cancer by analyzing transcriptomic data from The Cancer Genome Atlas and Gene Expression Omnibus databases. A reliable 10-gene ferroptosis signature (HIC1, ACSF2, MUC1, etc.) for the diagnosis of ovarian cancer was identified. Notably, we constructed and validated a novel prognostic signature including three FRGs: HIC1, LPCAT3, and DUOX1. We also further developed a risk score model based on these three genes which divided ovarian cancer patients into two risk groups. Functional analysis revealed that immune response and immune-related pathways were enriched in the high-risk group. Meanwhile, the tumor microenvironment was distinct between the two groups, with more M2 Macrophage infiltration and higher expression of key immune checkpoint molecules in the high-risk group than in the other group. Low-risk patients exhibited more favorable immunotherapy and chemotherapy responses. We conclude that crosstalk between ferroptosis and immunity may contribute to the worse prognosis of patients in the high-risk group. In particular, HIC1 showed both diagnostic and prognostic value in ovarian cancer.  In vitro  experiments demonstrated that inhibition of HIC1 improved drug sensitivity of chemotherapy and immunotherapy agents by inducing ferroptosis. Our findings provide new insights into the potential role of FRGs in the early detection, prognostic prediction, and individualized treatment decision-making for ovarian cancer patients.

Integrated Analysis of Ferroptosis-Related Biomarker Signatures to Improve the Diagnosis and Prognosis Prediction of Ovarian Cancer