Wang Kaili, Mei Shanshan, Cai Mengcheng, Zhai Dongxia, Zhang Danying, Yu Jin, Ni Zhexin, Yu Chaoqin
Department of Traditional Chinese Gynecology, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Department of Gynecology of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Front Oncol. 2022 Jun 9;12:888699. doi: 10.3389/fonc.2022.888699. eCollection 2022.
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 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(OC)是一种高度恶性的妇科肿瘤,可用的治疗方法很少,且使用目前可用的诊断标志物和干预措施时预后较差。迫切需要更有效的诊断和治疗方法。尽管目前的证据表明铁死亡与各种类型肿瘤的发生发展及治疗反应有关,但铁死亡在多大程度上影响卵巢癌尚不清楚。为了探索铁死亡相关基因作为卵巢癌诊断和干预的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(TCGA-OC)收集了多个数据集,分析并确定了60个铁死亡相关基因的共表达谱以及卵巢癌关于铁死亡的两种亚型,进一步检测并分析了两种亚型之间的差异表达基因。结果表明,铁死亡基因的表达水平与卵巢癌患者的预后显著相关。单因素Cox分析和LASSO分析从筛选出的铁死亡相关基因中鉴定出8个lncRNA,包括lncRNAs RP11-443B7.3、RP5-1028K7.2、TRAM2-AS1、AC073283.4、RP11-486G15.2、RP11-95H3.1、RP11-958F21.1和AC006129.1。基于铁死亡相关lncRNAs构建了一个风险评分模型,该模型在评估卵巢癌患者预后方面表现良好。基于肿瘤评分的高风险组和低风险组在临床特征、肿瘤突变负担和肿瘤免疫细胞浸润方面存在明显差异,表明风险评分具有良好的预测免疫治疗获益的能力,可能为卵巢癌精准免疫治疗的实施提供数据支持。尽管未来还需要进行更多的试验和研究,但我们的生物信息学分析有力地支持了铁死亡相关lncRNAs风险特征对卵巢癌预后预测的有效性。研究结果表明,这8个鉴定出的lncRNA作为卵巢癌诊断标志物和干预靶点具有很大的开发潜力,并且铁死亡相关lncRNA表达高的患者将从传统化疗或铁死亡诱导剂治疗中获得更大益处。