Department of Reproductive Medicine, Haidian District Maternal and Child Health Care Hospital, Beijing, China.
Department of Obstetrics, Haidian District Maternal and Child Health Care Hospital, Beijing, China.
Medicine (Baltimore). 2024 Jul 26;103(30):e38907. doi: 10.1097/MD.0000000000038907.
Recurrent implantation failure (RIF), a major issue in assisted reproductive technology (ART), may be influenced by necroptosis, a form of cell death linked to several diseases. This study was aimed at investigating the involvement of necroptosis in RIF. Using RNA-sequencing data from the Gene Expression Omnibus database, we identified differentially expressed necroptosis-related genes (DENRGs) in RIF patients compared with those in controls. Functional enrichment, protein-protein interaction (PPI) networks, and transcription factor (TF) regulatory networks were analyzed to identify key genes. Immune cell infiltration was analyzed using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Finally, potential therapeutic drugs targeting key genes were explored using a Drug Gene Interaction Database. In total, 20 DENRGs associated with RIF were identified, with a focus on 6 key genes (MLKL, FASLG, XIAP, CASP1, BIRC3, and TLR3) implicated in necroptosis and immune processes. These genes were used to develop a predictive model for RIF, which was validated in 2 datasets. The model and TF network analysis underscored the importance of TLR3. Immune infiltration analysis showed reduced levels of 16 immune cells in RIF patients, highlighting immune system alterations. Several drugs targeting CASP1, such as nivocasan and emricasan, were identified as potential treatments. The study sheds light on the role of necroptosis in RIF, identifying key genes and immune alterations that could serve as biomarkers and therapeutic targets. These findings pave the way for future experimental research and clinical applications targeting necroptosis in RIF treatment.
复发性植入失败(RIF)是辅助生殖技术(ART)中的一个主要问题,可能受到细胞死亡形式之一的坏死性凋亡的影响,坏死性凋亡与多种疾病有关。本研究旨在探讨坏死性凋亡在 RIF 中的作用。我们使用基因表达综合数据库中的 RNA 测序数据,鉴定了 RIF 患者与对照组相比差异表达的坏死性凋亡相关基因(DENRGs)。进行功能富集、蛋白质-蛋白质相互作用(PPI)网络和转录因子(TF)调控网络分析,以确定关键基因。使用单样本基因集富集分析(ssGSEA)算法分析免疫细胞浸润。最后,使用药物基因相互作用数据库探索针对关键基因的潜在治疗药物。总共鉴定出 20 个与 RIF 相关的 DENRGs,重点关注与坏死性凋亡和免疫过程相关的 6 个关键基因(MLKL、FASLG、XIAP、CASP1、BIRC3 和 TLR3)。这些基因用于开发 RIF 的预测模型,并在 2 个数据集进行验证。模型和 TF 网络分析强调了 TLR3 的重要性。免疫浸润分析显示 RIF 患者 16 种免疫细胞水平降低,突出了免疫系统的改变。几种针对 CASP1 的药物,如 nivocasan 和 emricasan,被确定为潜在的治疗药物。该研究揭示了坏死性凋亡在 RIF 中的作用,确定了关键基因和免疫改变,它们可以作为生物标志物和治疗靶点。这些发现为未来针对 RIF 治疗中坏死性凋亡的实验研究和临床应用铺平了道路。