关键词: hub genes immune microenvironment intracranial aneurysm machine learning single-cell sequencing

Mesh : Humans Intracranial Aneurysm / genetics immunology Single-Cell Analysis / methods Monocytes / immunology metabolism Machine Learning Macrophages / immunology metabolism Gene Expression Profiling Transcriptome Cellular Microenvironment / immunology genetics Male Female Gene Regulatory Networks Computational Biology / methods

来  源:   DOI:10.3389/fimmu.2024.1397475   PDF(Pubmed)

Abstract:
Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrophage (Mo/MΦ)-associated gene signatures to elucidate their correlation with the pathogenesis and immune microenvironment of IAs, thereby offering potential avenues for targeted therapy against IAs. Single-cell RNA-sequencing (scRNA-seq) data of IAs were acquired from the Gene Expression Synthesis (GEO) database. The significant infiltration of monocyte subsets in the parietal tissue of IAs was identified using single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis (hdWGCNA). The integration of six machine learning algorithms identified four crucial genes linked to these Mo/MΦ. Subsequently, we developed a multilayer perceptron (MLP) neural model for the diagnosis of IAs (independent external test AUC=1.0, sensitivity =100%, specificity =100%). Furthermore, we employed the CIBERSORT method and MCP counter to establish the correlation between monocyte characteristics and immune cell infiltration as well as patient heterogeneity. Our findings offer valuable insights into the molecular characterization of monocyte infiltration in IAs, which plays a pivotal role in shaping the immune microenvironment of IAs. Recognizing this characterization is crucial for comprehending the limitations associated with targeted therapies for IAs. Ultimately, the results were verified by real-time fluorescence quantitative PCR and Immunohistochemistry.
摘要:
单核细胞是引发特异性免疫反应的关键免疫细胞,可以对进展产生重大影响。预后,颅内动脉瘤(IAs)的免疫治疗。这项研究的目的是鉴定单核细胞/巨噬细胞(Mo/MΦ)相关的基因特征,以阐明它们与IAs的发病机理和免疫微环境的相关性。从而为针对IAs的靶向治疗提供了潜在的途径。IA的单细胞RNA测序(scRNA-seq)数据从基因表达合成(GEO)数据库获得。使用单细胞RNA测序和高维加权基因共表达网络分析(hdWGCNA)鉴定了IA的壁组织中单核细胞亚群的显着浸润。六个机器学习算法的整合确定了与这些Mo/MΦ相关的四个关键基因。随后,我们开发了用于诊断IAs的多层感知器(MLP)神经模型(独立外部测试AUC=1.0,灵敏度=100%,特异性=100%)。此外,我们使用CIBERSORT方法和MCP计数器来建立单核细胞特征与免疫细胞浸润以及患者异质性之间的相关性。我们的发现为IAs中单核细胞浸润的分子表征提供了有价值的见解,在塑造IAs的免疫微环境中起着关键作用。认识到这种表征对于理解与IA的靶向治疗相关的局限性至关重要。最终,结果经实时荧光定量PCR和免疫组化验证。
公众号