Identification of novel hub gene and biological pathways associated with ferroptosis in In-Stent Restenosis

The current study aims to reveal the molecular targets for neointimal hyperplasia through integrated analysis of data from gene expression omnibus (GEO) databases and single-cell sequencing (scRNA-Seq). The gene expression data used for the study and analysis were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/). The GSE46560 dataset included mRNA sequencing data from 11 restenosis human samples and 11 non-restenosis human samples of blood. The GSE60959 dataset included mircoRNA (miRNA) sequencing data from 10 plasma samples of patients with ISR. The GSE182225 dataset included lncRNA sequencing data from serum samples of 3 restenosis patients and 3 non-restenosis donors. The list of ferroptosis related genes was obtained from Ferr Db V2 database (http://www.zhounan.org/ferrdb/current/). Using a rat carotid artery balloon injury model to simulate restenosis after PCI. The common carotid arteries were collected for single-cell sequencing. We screened ten common differentially expressed genes (Co-DEGs) including BID, SP1, NCF2, HERPUD1, RICTOR, LAMP2, CAT, ACSL1, CS, and ANO6 from the GEO and FerrDb V2. GO/KEGG analyses indicated that metabolic reactions, particularly glyoxylate and dicarboxylate metabolism pathways, are the main molecular events. Immune infiltration analysis showed significant correlations between the expression of Co-DEGs and the infiltration of macrophages, dendritic cells, eosinophils, and neutrophils. Moreover, we identified SP1 as a potential therapeutic target associated with ferroptosis in ISR and constructed a lncRNA-miRNA-SP1 regulatory network. Using scRNA-Seq data to validate the expression of Co-DEGs in the neointima, we found that metabolic pathways such as carbon metabolism, peroxisomes, and reactive oxygen species were enriched. Immune infiltration examined the relationship between Co-DEGs and immune cells, revealing negative correlation between SP1 and neutrophils, and positive correlation between BID and macrophages.本研究旨在通过整合分析基因表达综合数据库（Gene Expression Omnibus，GEO）与单细胞RNA测序（single-cell RNA sequencing，scRNA-Seq）的数据，揭示内膜增生的分子靶点。本研究所用的基因表达数据均取自GEO数据库（https://www.ncbi.nlm.nih.gov/）。其中GSE46560数据集包含11例人类再狭窄血液样本与11例人类非再狭窄血液样本的mRNA测序数据；GSE60959数据集包含10例支架内再狭窄（in-stent restenosis，ISR）患者血浆样本的微小RNA（microRNA，miRNA）测序数据；GSE182225数据集包含3例再狭窄患者与3例非再狭窄供者血清样本的长链非编码RNA（long non-coding RNA，lncRNA）测序数据。铁死亡相关基因集取自FerrDb V2数据库（http://www.zhounan.org/ferrdb/current/）。本研究采用大鼠颈动脉球囊损伤模型模拟经皮冠状动脉介入治疗（percutaneous coronary intervention，PCI）术后再狭窄过程，采集颈总动脉组织进行单细胞测序。我们从GEO数据库与FerrDb V2数据库中筛选得到10个共有差异表达基因（common differentially expressed genes，Co-DEGs），分别为BID、SP1、NCF2、HERPUD1、RICTOR、LAMP2、CAT、ACSL1、CS及ANO6。GO/KEGG富集分析结果显示，代谢反应尤其是乙醛酸与二羧酸代谢通路为主要的分子事件。免疫浸润分析表明，共有差异表达基因的表达水平与巨噬细胞、树突状细胞、嗜酸性粒细胞及中性粒细胞的浸润程度存在显著相关性。此外，我们确定SP1为支架内再狭窄中与铁死亡（ferroptosis）相关的潜在治疗靶点，并构建了lncRNA-miRNA-SP1调控网络。利用单细胞测序数据验证共有差异表达基因在新生内膜中的表达情况，我们发现碳代谢、过氧化物酶体及活性氧等代谢通路显著富集。免疫浸润分析进一步揭示了共有差异表达基因与免疫细胞的关联：SP1与中性粒细胞呈负相关，BID与巨噬细胞呈正相关。