基于机器学习的慢性鼻炎与鼻息肉中有关基因分类模式和免疫透特征的识别
Ziqi Chen1, Lingmei Qu2, Qing Hao1
1Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Frontiers in molecular biosciences
|September 2, 2025
概括
这项研究确定了基于阿诺基斯相关基因的两种慢性鼻炎 (CRSwNP) 的分子亚型. 雄激素受体 (AR) 和PTHLH是个性化CRSwNP治疗的关键生物标志物.
科学领域:
- 免疫学
- 分子生物学
- 基因组学
背景情况:
- 长期鼻炎与鼻息肉 (CRSwNP) 涉及瘤和白沉积.
- 编程细胞死亡的一种形式Anoikis在CRSwNP的发病过程中起作用,但其机制尚不清楚.
研究的目的:
- 研究基因 (ARG) 在CRSwNP中的作用.
- 确定CRSwNP的分子亚型和潜在生物标志物.
主要方法:
- 对GEO数据集 (GSE136825,GSE179625) 和338个ARG进行分析.
- 共识聚类,用于关键ARG识别的机器学习和免疫细胞透分析.
- 在人类CRSwNP组织中使用qRT-PCR,IHC和IF进行验证.
主要成果:
- CRSwNP患者被分为两个不同的无毒相关集群.
- 确定了四个关键的ARG (CDH3,PTHLH,PDCD4,AR);AR和PTHLH是集群特定的生物标志物.
- 获得了高诊断准确度 (AUC>0. 90),并观察到群体之间的免疫微环境差异.
结论:
- 确定了两种与阿诺基斯相关的CRSwNP分子亚型.
- 受体 (AR) 和PTHLH作为CRSwNP的潜在集群特异性生物标志物.
- 这些发现支持个性化治疗,药物查和CRSwNP的免疫调节策略.
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