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评估个性化的分子肖像,在肺动脉高血压中为内皮细胞到介质细胞过渡提供基础

Ruhao Wu¹, Ge Zhang^2,3,4, Mingzhou Guo¹

¹Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.

Molecular medicine (Cambridge, Mass.)

|October 27, 2024

概括

研究人员在肺动脉高血压 (PAH) 中确定了不同的细胞群,专注于内皮细胞 (EC) 和它们的过渡. 为潜在的PAH诊断和治疗,开发了一种机器学习工具,即PAH内皮细胞到介质细胞过渡信号 (PETS).

科学领域:

肺高血压研究肺高血压研究
细胞生物学细胞生物学
生物标志物发现发现

背景情况:

肺动脉高血压 (PAH) 是一种严重的,进展性疾病,原因复杂.
通过微妙的生物过程探索,早期发现PAH病变对于及时干预至关重要.
了解PAH中的细胞异质性是开发有效治疗方法的关键.

研究的目的:

在肺动脉高血压 (PAH) 中识别不同的细胞群及其特征.
研究内皮细胞 (ECs) 和内皮细胞转化为介质细胞 (EndMT) 在PAH中的作用.
开发一种基于已识别的细胞特征的PAH新型诊断和治疗工具.

主要方法:

基因表达造型,以识别PAH中的九种不同的细胞群.
细胞组成,功能,分布和通信模式的比较分析.
使用9名学习者开发了一种机器学习程序 (PAH 内皮细胞到介质细胞过渡签名 - PETS).

主要成果:

在PAH中观察到细胞群体,功能和通信的显著异质性.
内皮细胞 (ECs) 呈现出显著的变异,包括内皮细胞转变为介质细胞 (EndMT) 的证据.
确定了一个具有对比表型的ECs的特定子组.

结论:

该研究在PAH的背景下确定了参与EndMT的关键细胞群.
开发的PETS工具显示出有助于PAH诊断和指导精确治疗策略的潜力.
对这些细胞机制的进一步研究可能会为PAH治疗开辟新的途径.

关键词:

生物标志物生物标志物内皮细胞到介质细胞的过渡.机器学习是机器学习.分子签名分子签名肺动脉高血压是肺动脉高血压.

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