Table2_Integrated Analysis of Ferroptosis-Related Biomarker Signatures to Improve the Diagnosis and Prognosis Prediction of Ovarian Cancer.XLSX

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.

卵巢癌仍是致死率最高的妇科恶性肿瘤。铁死亡（Ferroptosis）是一种特殊的铁依赖性非凋亡细胞死亡形式，在多种癌症中发挥关键作用。然而，目前学界对铁死亡在卵巢癌中的贡献尚不明晰。本研究通过分析癌症基因组图谱（The Cancer Genome Atlas）与基因表达综合数据库（Gene Expression Omnibus）的转录组数据，系统解析了铁死亡相关基因在卵巢癌中的诊断、预后及治疗价值。本研究成功筛选出一套可用于卵巢癌诊断的、包含10个铁死亡相关基因的可靠特征基因集（HIC1、ACSF2、MUC1等）。值得注意的是，本研究构建并验证了一套包含3个铁死亡相关基因（Ferroptosis-related genes, FRGs）的新型预后特征基因集，涉及HIC1、LPCAT3与DUOX1。此外，本研究基于这3个基因构建了风险评分模型，可将卵巢癌患者划分为高风险组与低风险组。功能富集分析显示，高风险组显著富集免疫应答及免疫相关通路。与此同时，两组患者的肿瘤微环境存在显著差异：高风险组的M2巨噬细胞浸润程度更高，关键免疫检查点分子的表达水平也显著高于低风险组。低风险组患者对免疫治疗与化疗的应答效果更佳。本研究认为，铁死亡与免疫之间的交互调控可能是高风险组患者预后较差的潜在原因。尤为关键的是，HIC1在卵巢癌中同时具备诊断与预后评估价值。体外实验证实，抑制HIC1的表达可通过诱导铁死亡，增强卵巢癌细胞对化疗与免疫治疗药物的敏感性。本研究结果为铁死亡相关基因在卵巢癌患者的早期筛查、预后预测及个体化治疗决策中的潜在应用价值提供了全新的研究视角。