在肺状细胞癌中预测化学免疫治疗反应的病理学模型:一项多中心研究
Dongying Wang1, Shuai Mu2, Minghui Zhang3
1Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Shanghai Key Laboratory of Thoracic Tumor Biotherapy, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
Lung cancer (Amsterdam, Netherlands)
|December 20, 2025
概括
一个新的病理学模型准确地预测T细胞炎症基因表达特征 (GEP) 在肺状细胞癌 (LUSC) 的状态. 该模型识别了从化疗-免疫疗法 (CIT) 中受益的患者,改善了生存结果.
科学领域:
- 在瘤学瘤学.
- 计算病理学计算病理学
- 基因组学就是基因组学.
背景情况:
- 鉴定受益于一线化疗免疫疗法 (CIT) 的肺状细胞癌 (LUSC) 患者是具有挑战性的.
- 预测治疗反应需要强大的生物标志物.
研究的目的:
- 开发一种病理学模型来预测LUSC中的T细胞炎症基因表达特征 (GEP) 状态.
- 验证模型在识别受益于CIT的患者中的实用性.
主要方法:
- 来自TCGA LUSC队列 (n=334) 的全幻灯片图像和RNA测序数据被用于开发病理学模型和病理学得分 (PS).
- 模型的预测值在一个前性的多中心试验 (AK105-302,n=267) 和两个独立的队列 (n=82,n=50) 中得到验证.
- 评估了PS和治疗 (CIT与化疗) 之间的相互作用,以评估无进展生存期 (PFS) 和总生存期 (OS).
主要成果:
- 病理学模型实现了GEP状态预测的AUC为0.80 (训练) 和0.71 (验证).
- 在PFS (p=0.011) 和OS (p<0.001) 中发现了PS和治疗之间的显著相互作用.
- 接受CIT的高PS患者与接受化疗的高PS患者相比,PFS (HR:0.31) 和OS (HR:0.30) 显著延长;低PS患者没有显示这种益处.
- 高PS与免疫热瘤微环境有关.
结论:
- 开发了一个基于GEP的病理学模型.
- 该模型提供了一种实用的,具有成本效益的策略,用于识别LUSC患者,他们可能从一线CIT获得更高的生存益处,而不是仅仅使用化疗.
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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