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系统性免疫特征预测了晚期乳腺癌患者对免疫检查点抑制剂的毒性

Yalong Qi¹, Hewei Ge¹, Xiaoying Sun²

¹Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Journal of autoimmunity

|April 23, 2025

概括

预测免疫治疗引起的免疫相关不良事件 (irAEs) 是至关重要的. 这项研究确定了血液中的特定免疫细胞种群,可以预测发展irrAEs的风险,有助于患者管理.

科学领域:

免疫学免疫学免疫学
在瘤学瘤学.
计算生物学计算生物学

背景情况:

免疫检查点抑制剂 (ICI) 提供有前途的癌症治疗,但可能导致严重的免疫相关不良事件 (irAEs).
缺乏对IREs的预测模型,这阻碍了ICI治疗的个性化风险效益评估.
这项研究旨在确定与irAEs相关的全身免疫特征,并开发一个预测模型.

研究的目的:

在接受ICI治疗的患者中分析免疫细胞亚群.
建立基于基线免疫细胞概况的irAEs风险预测模型.
在独立的队列中验证预测模型.

主要方法:

通过量细胞计飞行时间 (CyTOF) 分析了外周血液单核细胞 (PBMC).
在ICI治疗之前和之后量化了免疫细胞亚群.
使用GEO数据库队列 (GSE189125,GSE186143) 开发并验证了后勤回归模型.

主要成果:

基线高比例的CXCR3+CCR6+CD4+T细胞和CD38+CD86+CXCR3+CCR6+CD8+T细胞,以及低比例的CXCR3低CD56dimNK细胞与irAE发生率有显著的相关性.
这些相关性在与免疫相关的肺炎和甲状腺炎的子组中是一致的.
一个预测模型在培训队列中实现了0.79的AUROC,在验证队列中达到0.75.

结论:

特定的免疫细胞群作为预测irAE风险的潜在生物标志物.
鉴定这些免疫细胞的特征可以帮助管理irrAEs,并可能减少它们的发生率.
开发的模型在预测irAEs方面显示出临床应用的前景.

关键词:

生物标志物生物标志物与免疫相关的不良事件.质量细胞测量飞行时间.预测模型是一个预测模型.系统性免疫力系统性免疫力

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