摘要
      主动脉夹层（AD）是心血管系统最危险的疾病之一，其特点是发病急、预后差，而AD的发病机制尚不清楚，可能影响甚至延迟AD的诊断。锚定依赖性细胞死亡（Anoikis）是一种特殊的细胞死亡模式，其是由正常细胞从细胞外基质（ECM）分离后引起的程序性细胞死亡，近年来在肿瘤学领域得到了广泛研究。在本研究中，我们应用生物信息学分析，根据研究分析结果和基因本体论（GO）以及京都基因和基因组百科全书（KEGG），最终发现了3个基于机器学习的失巢相关基因（ARGs）。然后通过受试者操作特征（ROC）、基因集富集分析（GSEA）、基因集中富集分析（GSMA）等方法进一步验证。我们假设ARGs可能通过氧化应激、炎症反应和ECM等途径参与AD的发病机制。因此，我们得出结论，ARGs可能是决定AD诊断的重要因素。
Abstract
Aortic dissection (AD) is one of the most dangerous diseases of the cardiovascular system, which is characterized by acute onset and poor prognosis, while the pathogenesis of AD is still unclear and may affect or even delay the diagnosis of AD. Anchorage-dependent cell death (Anoikis) is a special mode of cell death, which is programmed cell death caused by normal cells after detachment from extracellular matrix (ECM)and has been widely studied in the field of oncology in recent years. In this study, we applied bioinformatics analysis, according to the results of research analysis and Gene Ontology (GO), as well as Kyoto Encyclopedia of Genes and Genomes (KEGG), finally found 3 anoikis-related genes (ARGs) based on machine learning. Then we further verified by receiver operating characteristic (ROC), gene set enrichment analysis (GSEA), gene set enrichment analysis (GSVA)and other methods. We hypothesize ARGs may be involved in the pathogenesis of AD through pathways such as oxidative stress, inflammatory response, and ECM. Therefore, we conclude that the ARGs can be an important factor in determining the diagnosis of AD.

https://assets.researchsquare.com/files/rs-2461419/v1/c856e395-129e-45ba-9ea2-1f915d3f2e0e.pdf?c=1676267081