Chen Yan, Zhu Yanmei, Huang Cong, Qu Youyang, Zhu Yulan
Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150080, People's Republic of China.
Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150080, People's Republic of China.
Int J Gen Med. 2024 Dec 19;17:6377-6392. doi: 10.2147/IJGM.S485612. eCollection 2024.
This research utilized a combination of gene databases associated with ferroptosis and online gene expression data from ischemic stroke samples to pinpoint ferroptosis-related genes (FRGs) in ischemic stroke cases.
By employing Random Forest (RF) and Support Vector Machine (SVM) models based on these genes, an overlap of genes from both models was identified as "Hub" genes. Through consensus clustering analysis using Hub genes, two distinct clusters of FRGs were revealed in ischemic stroke samples. Examination of the correlation between these molecular subtypes and the immune microenvironment highlighted a close link between gene expression levels and immune cell infiltration. Significantly different gene expression and functions within the FRG clusters underscored the pivotal role of Hub genes in the immune microenvironment. A gene diagnostic model related to ferroptosis was developed and validated to elucidate the significance of the identified genes.
The results demonstrated that the Hub gene-based classification model effectively differentiated between ischemic stroke patients and normal samples, achieving an AUC of 0.900, signifying clinical relevance.
This study successfully identified ferroptosis-related genes in ischemic stroke, offering insights that could contribute to the formulation of future comprehensive treatment approaches.
本研究利用与铁死亡相关的基因数据库以及缺血性中风样本的在线基因表达数据,以确定缺血性中风病例中铁死亡相关基因(FRGs)。
通过基于这些基因构建随机森林(RF)和支持向量机(SVM)模型,将两个模型中的重叠基因确定为“枢纽”基因。利用枢纽基因进行一致性聚类分析,在缺血性中风样本中揭示了两种不同的铁死亡相关基因簇。对这些分子亚型与免疫微环境之间的相关性进行研究,结果表明基因表达水平与免疫细胞浸润之间存在密切联系。铁死亡相关基因簇内显著不同的基因表达和功能强调了枢纽基因在免疫微环境中的关键作用。开发并验证了一种与铁死亡相关的基因诊断模型,以阐明所鉴定基因的意义。
结果表明,基于枢纽基因的分类模型能够有效区分缺血性中风患者和正常样本,曲线下面积(AUC)为0.900,具有临床相关性。
本研究成功鉴定了缺血性中风中铁死亡相关基因,为未来制定综合治疗方案提供了参考依据。