Department of Ophthalmology, The Tongnan District People's Hospital, Chongqing, China.
Department of Ophthalmology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Sci Rep. 2023 Dec 20;13(1):22804. doi: 10.1038/s41598-023-50205-1.
The goal of this study was to develop a ferroptosis-based molecular signature that can predict recurrence-free survival (RFS) in patients with prostate cancer (PCa). In this study, we obtained ferroptosis-related genes (FRGs) in FerrDb database and clinical transcriptome data in TCGA database and GEO database. Consensus cluster analysis was used to identify three molecular markers of ferroptosis in PCa with differential expression of 40 FRGs, including PD-L1 expression levels. We conducted a new ferroptosis-related signature for PCa RFS using four FRGs identified through univariate and multivariate Cox regression analyses. The signature was validated in the training, testing, and validation cohorts, and it demonstrated remarkable results in the area under the time-dependent receiver operating characteristic (ROC) curve of 0.757, 0.715, and 0.732, respectively. Additionally, we observed that younger patients, those with stage T III and stage T IV, stage N0, cluster 1, and cluster 2 PCa were more accurately predicted by the signature as independent predictors of RFS. DU-145 and RWPE-1 cells were successfully analyzed by qRT-PCR and Western blot for ASNS, GPT2, RRM2, and NFE2L2. In summary, we developed a novel ferroptosis-based signature for RFS in PC, utilizing four FRGs identified through univariate and multivariate Cox regression analyses. This signature was rigorously validated across training, testing, and validation cohorts, demonstrating exceptional performance as evidenced by its ROC curves. Notably, our findings indicate that this signature is particularly effective as an independent predictor of RFS in younger patients or those with stage T III and T IV, stage N0, and in clusters 1 and 2. Finally, we confirmed the expression of these four FRGs in DU-145 and RWPE-1 cell lines.
本研究旨在开发一种基于铁死亡的分子特征,以预测前列腺癌(PCa)患者的无复发生存率(RFS)。在本研究中,我们从 FerrDb 数据库中获取铁死亡相关基因(FRGs),并从 TCGA 数据库和 GEO 数据库中获取临床转录组数据。采用共识聚类分析方法,鉴定出 40 个 FRGs 差异表达的 PCa 中三种铁死亡分子标志物,包括 PD-L1 表达水平。我们通过单因素和多因素 Cox 回归分析,确定了四个 FRGs 构建了新的 PCa RFS 相关的铁死亡特征。该特征在训练、测试和验证队列中进行了验证,在时间依赖的接收器操作特征(ROC)曲线下面积(AUC)分别为 0.757、0.715 和 0.732,验证效果显著。此外,我们观察到年轻患者、T 分期为 III 期和 IV 期、N 分期为 N0、聚类 1 和聚类 2 的 PCa 患者,该特征作为 RFS 的独立预测因子,预测效果更为准确。通过 qRT-PCR 和 Western blot 分析,成功验证了 DU-145 和 RWPE-1 细胞中 ASNS、GPT2、RRM2 和 NFE2L2 的表达。总之,我们开发了一种新的基于铁死亡的 PCa RFS 预测特征,利用单因素和多因素 Cox 回归分析确定了四个 FRGs。该特征在训练、测试和验证队列中得到了严格验证,ROC 曲线证明了其优异的性能。值得注意的是,我们的研究结果表明,该特征在年轻患者或 T 分期为 III 期和 IV 期、N 分期为 N0、聚类 1 和聚类 2 的患者中,作为 RFS 的独立预测因子具有较高的预测价值。最后,我们还在 DU-145 和 RWPE-1 细胞系中验证了这四个 FRGs 的表达。