Zhang Dandan, Zhang Qian, Wang Yan, Zhang Ning
People's Hospital of Chongqing Banan District, Chongqing, China.
Heilongjiang University of Chinese Medicine, Harbin, China.
Medicine (Baltimore). 2025 Aug 15;104(33):e43747. doi: 10.1097/MD.0000000000043747.
This study explored the molecular patterns and diagnostic biomarkers associated with cuproptosis in cardioembolic stroke (CES) using bioinformatics tools. GSE58294 expression profile data were downloaded from the Gene Expression Synthesis Database as a training dataset, and cuproptosis-related genes were extracted for analysis. We identified differentially expressed cuproptosis-associated genes (DECAGs) between CES and control samples. In total, 11 DECAGs (MTF1, NFE2L2, DLD, ATP7B, ATP7A, SLC31A1, PDHA1, CDKN2A, DLS, DLAT, PDHB) and activated immune responses differed significantly between CES patients and non-CES controls. Two molecular clusters associated with cuproptosis were discerned in CES. Immunoinfiltration analysis revealed significant immunoheterogeneity among the different molecular clusters, and Cluster1 showed a relatively high level of immunoinfiltration. Weighted gene co-expression network analysis revealed 819 key genes related to CES, 320 key genes related to CES typing, and 37 core intersection genes were identified by Venn analysis to construct a training model. The generalized linear model showed satisfactory performance based on 2 external validation datasets. Within this model, 5 genes (FLT3LG, MAL, TNFRSF25, CASP5, and MAN1C1) were identified as the most significantly associated with CES characteristics. Clinical application columns were established based on the expression levels of 5 CES characteristic genes. Decision curve analysis and correction curves showed that the results had good prediction accuracy. The present findings highlight the crucial role of cuproptosis in the development and diagnosis of CES, indicating its potential as a key factor in understanding and identifying CES.
本研究使用生物信息学工具探索了与心源性栓塞性卒中（CES）中铜死亡相关的分子模式和诊断生物标志物。从基因表达综合数据库下载GSE58294表达谱数据作为训练数据集，并提取与铜死亡相关的基因进行分析。我们鉴定了CES与对照样本之间差异表达的铜死亡相关基因（DECAGs）。总共11个DECAGs（MTF1、NFE2L2、DLD、ATP7B、ATP7A、SLC31A1、PDHA1、CDKN2A、DLS、DLAT、PDHB）以及激活的免疫反应在CES患者和非CES对照之间存在显著差异。在CES中识别出两个与铜死亡相关的分子簇。免疫浸润分析显示不同分子簇之间存在显著的免疫异质性，并且簇1显示出相对较高的免疫浸润水平。加权基因共表达网络分析揭示了819个与CES相关的关键基因、320个与CES分型相关的关键基因，通过Venn分析确定了37个核心交集基因以构建训练模型。基于2个外部验证数据集，广义线性模型表现出令人满意的性能。在该模型中，5个基因（FLT3LG、MAL、TNFRSF25、CASP5和MAN1C1）被确定为与CES特征最显著相关。基于5个CES特征基因的表达水平建立了临床应用列。决策曲线分析和校正曲线表明结果具有良好的预测准确性。本研究结果突出了铜死亡在CES发生和诊断中的关键作用，表明其作为理解和识别CES的关键因素的潜力。
