基于加权基因共表达网络分析（WGCNA）探索在反复种植失败（RIF）中具有预后能力的铁死亡相关生物标志物。
Exploration of ferroptosis-related biomarkers with prognostic capability in RIF based on WGCNA.
作者信息
Zhou Tingting, Zhang Qian, Yu Wenhao, Cui Yuqian, Yan Junhao, Ni Tianxiang, Fu Xiaohua, Li Junwei
机构信息
Center for Reproductive Medicine, Department of Reproductive Endocrinology, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Center for Reproductive Medicine, Shandong University, Jinan, Shandong, China.
出版信息
J Assist Reprod Genet. 2025 Mar;42(3):949-959. doi: 10.1007/s10815-024-03370-9. Epub 2024 Dec 23.
PURPOSE
To explore the association of ferroptosis with repeated implantation failure (RIF) and prognostic capability of ferroptosis-related genes.
METHODS
Data in GSE106602 from the GEO database were used for gene co-expression network construction to confirm ferroptosis-related genes compared to gene sets that were downloaded from FerrDB. Then these genes were analyzed for functional enrichment and validated using endometrium samples from our center. ImplantScore and ROC curve were constructed for prognostic correlation analysis.
RESULTS
We observed that ferroptosis probably participated in RIF according to bioinformatics analysis on a gene set which exhibited a strong association with RIF from WGCNA. Fifty-four ferroptosis-related genes in the gene set were subsequently verified, and the PPI network was established for underlying interactions among them. There were 23 hub genes with differential expression in RIF and six of them (PML, LCN2, PRKAA1, BACH1, SLC7A11, and CAMKK2) showed significant correlation with implantation outcomes using samples collected from our center. Therefore, we combined the six genes and constructed an ImplantScore whose AUC reached 0.891, higher than the AUC of each single gene, respectively. ImplantScore of six genes with down-regulated expression in the group with failed implantation were much lower than that with successful outcome.
CONCLUSION
Our results demonstrated the potential prognostic functions of ferroptosis-related biomarkers in RIF, which will provide novel perspectives for further research and clinical applications.
目的
探讨铁死亡与反复种植失败（RIF）的关联以及铁死亡相关基因的预后能力。
方法
使用来自GEO数据库的GSE106602数据构建基因共表达网络，以确认与从FerrDB下载的基因集相比的铁死亡相关基因。然后对这些基因进行功能富集分析，并使用我们中心的子宫内膜样本进行验证。构建ImplantScore和ROC曲线进行预后相关性分析。
结果
根据对来自WGCNA的与RIF有强关联的基因集的生物信息学分析，我们观察到铁死亡可能参与了RIF。随后验证了基因集中54个铁死亡相关基因，并建立了它们之间潜在相互作用的PPI网络。在RIF中有23个枢纽基因存在差异表达，其中6个基因（PML、LCN2、PRKAA1、BACH1、SLC7A11和CAMKK2）使用我们中心收集的样本显示与种植结局有显著相关性。因此，我们将这6个基因组合构建了一个ImplantScore，其AUC达到0.891，分别高于每个单个基因的AUC。种植失败组中6个表达下调基因的ImplantScore远低于种植成功组。
结论
我们的结果证明了铁死亡相关生物标志物在RIF中的潜在预后功能，这将为进一步研究和临床应用提供新的视角。
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