Wu Yong-Hong, Sun Jing, Huang Jun-Hua, Lu Xiao-Yun
Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, Shanxi Province, China.
School of Medical Technology & Institute of Basic Translational Medicine, Xi'an Medical University, Xi'an, 710021, Shanxi Province, China.
Sci Rep. 2024 Dec 30;14(1):32096. doi: 10.1038/s41598-024-83783-9.
Promoting vascular endothelial cell regeneration can enhance recovery from cerebral ischemia reperfusion injury (CIRI), but there is a lack of bioinformatic studies on angiogenesis-related biomarkers in CIRI. In this study, we utilized the GSE97537 and GSE61616 datasets from GEO to identify 181 angiogenesis-related genes (ARGs) and analyzed differentially expressed genes (DEGs) between CIRI and control groups. We converted ARGs to 169 rat homologues and intersected them with DEGs to find DE-ARGs. RF and XGBoost models were employed to identify five biomarkers (Stat3, Hmox1, Egfr, Col18a1, Ptgs2) and conducted GSEA on these biomarkers, revealing their enrichment in pathways such as ECM-receptor interaction and hematopoietic cell lineage. We also analyzed the immune microenvironment, finding significant differences in 21 immune cells between CIRI and control groups. Furthermore, we constructed lncRNA-miRNA-mRNA networks and drug-gene networks. Finally, biomarker expression was compared between the CIRI and control groups by qRT-PCR in tissue and blood samples. Overall, our bioinformatic exploration of angiogenesis-related biomarkers in CIRI provides new insights for the diagnosis and treatment of CIRI.
促进血管内皮细胞再生可增强脑缺血再灌注损伤(CIRI)后的恢复,但目前缺乏关于CIRI中血管生成相关生物标志物的生物信息学研究。在本研究中,我们利用来自GEO的GSE97537和GSE61616数据集,鉴定出181个血管生成相关基因(ARG),并分析了CIRI组与对照组之间的差异表达基因(DEG)。我们将ARG转化为169个大鼠同源基因,并与DEG进行交叉分析以找到差异表达的血管生成相关基因(DE-ARG)。采用随机森林(RF)和极端梯度提升(XGBoost)模型鉴定出5个生物标志物(Stat3、Hmox1、Egfr、Col18a1、Ptgs2),并对这些生物标志物进行基因集富集分析(GSEA),发现它们在细胞外基质-受体相互作用和造血细胞谱系等通路中富集。我们还分析了免疫微环境,发现CIRI组与对照组之间21种免疫细胞存在显著差异。此外,我们构建了lncRNA-miRNA-mRNA网络和药物-基因网络。最后,通过qRT-PCR比较了CIRI组与对照组在组织和血液样本中的生物标志物表达。总体而言,我们对CIRI中血管生成相关生物标志物的生物信息学探索为CIRI的诊断和治疗提供了新的见解。