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Identification of important genes related to anoikis in acute myocardial infarction
Journal of Cellular and Molecular Medicine ( IF 5.3 ) Pub Date : 2024-03-25 , DOI: 10.1111/jcmm.18264
Puwei Song 1 , Yasen Yakufujiang 1 , Jianghui Zhou 1 , Shaorui Gu 1 , Wenli Wang 1 , Zhengyuan Huo 1
Affiliation  

Acute myocardial infarction (AMI) increasingly precipitates severe heart failure, with diagnoses now extending to progressively younger demographics. The focus of this study was to pinpoint critical genes linked to both AMI and anoikis, thereby unveiling potential novel biomarkers for AMI detection and intervention. Differential analysis was performed to identify significant differences in expression, and gene functionality was explored. Weighted gene coexpression network analysis (WGCNA) was used to construct gene coexpression networks. Immunoinfiltration analysis quantified immune cell abundance. Protein–protein interaction (PPI) analysis identified the proteins that interact with theanoikis. MCODE identified key functional modules. Drug enrichment analysis identified relevant compounds explored in the DsigDB. Through WGCNA, 13 key genes associated with anoikis and differentially expressed genes were identified. GO and KEGG pathway enrichment revealed the regulation of apoptotic signalling pathways and negative regulation of anoikis. PPI network analysis was also conducted, and 10 hub genes, such as IL1B, ZAP70, LCK, FASLG, CD4, LRP1, CDH2, MERTK, APOE and VTN were identified. IL1B were correlated with macrophages, mast cells, neutrophils and Tcells in MI, and the most common predicted medications were roxithromycin, NSC267099 and alsterpaullone. This study identified key genes associated with AMI and anoikis, highlighting their role in immune infiltration, diagnosis and medication prediction. These findings provide valuable insights into potential biomarkers and therapeutic targets for AMI.

中文翻译:

急性心肌梗死失巢凋亡相关重要基因的鉴定

急性心肌梗死 (AMI) 越来越多地引发严重心力衰竭,目前诊断范围已扩大到越来越年轻的人群。本研究的重点是查明与 AMI 和失巢凋亡相关的关键基因,从而揭示用于 AMI 检测和干预的潜在新型生物标志物。进行差异分析以确定表达的显着差异,并探索基因功能。加权基因共表达网络分析(WGCNA)用于构建基因共表达网络。免疫渗透分析量化了免疫细胞丰度。蛋白质-蛋白质相互作用 (PPI) 分析确定了与 theanoikis 相互作用的蛋白质。 MCODE确定了关键功能模块。药物富集分析确定了 DsigDB 中探索的相关化合物。通过WGCNA,鉴定出13个与失巢凋亡相关的关键基因和差异表达基因。 GO和KEGG通路富集揭示了细胞凋亡信号通路的调节和失巢凋亡的负调节。还进行了PPI网络分析,确定了10个枢纽基因,如IL1B、ZAP70、LCK、FASLG、CD4、LRP1、CDH2、MERTK、APOE和VTN。 IL1B 与 MI 中的巨噬细胞、肥大细胞、中性粒细胞和 T 细胞相关,最常见的预测药物是罗红霉素、NSC267099 和 alsterpaulone。这项研究确定了与 AMI 和失巢凋亡相关的关键基因,强调了它们在免疫浸润、诊断和药物预测中的作用。这些发现为 AMI 的潜在生物标志物和治疗靶点提供了宝贵的见解。
更新日期:2024-03-25
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