Table_6_Ferroptosis-Related Long Noncoding RNAs as Prognostic Biomarkers for Ovarian Cancer.xlsx

Ovarian cancer (OC) is a highly malignant gynecologic tumor with few treatments available and poor prognosis with the currently available diagnostic markers and interventions. More effective methods for diagnosis and treatment are urgently needed. Although the current evidence implicates ferroptosis in the development and therapeutic responses of various types of tumors, it is unclear to what extent ferroptosis affects OC. To explore the potential of ferroptosis-related genes as biomarkers and molecular targets for OC diagnosis and intervention, this study collected several datasets from The Cancer Genome Atlas-OC (TCGA-OC), analyzed and identified the coexpression profiles of 60 ferroptosis-related genes and two subtypes of OC with respect to ferroptosis and further examined and analyzed the differentially expressed genes between the two subtypes. The results indicated that the expression levels of ferroptosis genes were significantly correlated with prognosis in patients with OC. Single-factor Cox and LASSO analysis identified eight lncRNAs from the screened ferroptosis-related genes, including lncRNAs RP11-443B7.3, RP5-1028K7.2, TRAM2-AS1, AC073283.4, RP11-486G15.2, RP11-95H3.1, RP11-958F21.1, and AC006129.1. A risk scoring model was constructed from the ferroptosis-related lncRNAs and showed good performance in the evaluation of OC patient prognosis. The high- and low-risk groups based on tumor scores presented obvious differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration, indicating that the risk score has a good ability to predict the benefit of immunotherapy and may provide data to support the implementation of precise immunotherapy for OC. Although in vivo tests and research are needed in the future, our bioinformatics analysis powerfully supported the effectiveness of the risk signature of ferroptosis-related lncRNAs for prognosis prediction in OC. The findings suggest that these eight identified lncRNAs have great potential for development as diagnostic markers and intervention targets for OC and that patients with high ferroptosis-related lncRNA expression will receive greater benefits from conventional chemotherapy or treatment with ferroptosis inducers.

卵巢癌（Ovarian Cancer, OC）是一类恶性程度极高的妇科肿瘤，当前可用的诊断标志物与干预手段有限，患者预后不佳，临床亟需更为有效的诊断与治疗方法。尽管现有研究证据表明铁死亡（ferroptosis）参与多种肿瘤的发生发展及治疗应答过程，但铁死亡对卵巢癌的具体影响程度仍不明确。为探究铁死亡相关基因作为卵巢癌诊断与干预生物标志物及分子靶点的潜力，本研究从癌症基因组图谱-卵巢癌队列（TCGA-OC）中采集了多组数据集，分析并鉴定了60个铁死亡相关基因的共表达谱，以及两类与铁死亡相关的卵巢癌亚型；进一步对两类亚型间的差异表达基因进行了检测与分析。研究结果显示，铁死亡相关基因的表达水平与卵巢癌患者的预后显著相关。通过单因素Cox回归与最小绝对收缩和选择算子（LASSO）分析，从筛选出的铁死亡相关基因中鉴定出8个长链非编码RNA（lncRNAs），分别为RP11-443B7.3、RP5-1028K7.2、TRAM2-AS1、AC073283.4、RP11-486G15.2、RP11-95H3.1、RP11-958F21.1及AC006129.1。基于上述铁死亡相关长链非编码RNA构建的风险评分模型，在评估卵巢癌患者预后方面表现良好。根据肿瘤评分划分的高风险组与低风险组患者，在临床特征、肿瘤突变负荷及肿瘤免疫细胞浸润方面均存在显著差异，提示该风险评分可有效预测免疫治疗获益情况，可为卵巢癌精准免疫治疗的实施提供数据支持。尽管未来仍需开展体内实验与相关研究，但本研究的生物信息学分析有力证实了铁死亡相关长链非编码RNA风险特征用于卵巢癌预后预测的有效性。研究结果表明，本次鉴定出的8个长链非编码RNA具备开发为卵巢癌诊断标志物与干预靶点的巨大潜力，且铁死亡相关长链非编码RNA高表达的患者可从常规化疗或铁死亡诱导剂治疗中获得更大获益。