在非小细胞肺癌中预测免疫疗法的反应 - 从长椅到床边
Chris Montoya1, Benjamin Spieler1, Scott M Welford1
1Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, Miami, FL, United States.
Frontiers in oncology
|November 30, 2023
概括
放射学和实验室数据可以预测晚期非小细胞肺癌 (aNSCLC) 中的免疫检查点抑制剂 (ICI) 反应. 这些发现表明一种非侵入性的方法来分类患者,以便更好地选择治疗.
科学领域:
- 在瘤学瘤学.
- 放射学 放射学是一门学科.
- 免疫治疗是一种免疫疗法.
背景情况:
- 免疫检查点抑制剂 (ICI) 治疗是高级非小细胞肺癌 (aNSCLC) 的标准治疗方法.
- 预测患者对ICI治疗的反应对于优化治疗策略和选择替代方案至关重要.
- 这项研究研究了放射学和实验室变量的潜力,以预测ICI反应.
研究的目的:
- 在小鼠模型中识别预处理放射学和实验室变量,以预测ICI反应.
- 为了验证这些预测因素在人类aNSCLC患者治疗nivolumab和pembrolizumab.
- 根据预测的ICI反应开发一种非侵入性方法来对aNSCLC患者进行分类.
主要方法:
- 肺癌的小鼠模型接受了ICI,预治疗实验室和CT数据分析了反应相关性.
- 从117名接受尼沃卢马布治疗的aNSCLC患者的基线临床和CT数据与整体存活率 (OS) 相相关.
- 该预测模型在接受pembrolizumab的42名aNSCLC患者身上进行了内部交叉验证和外部测试.
主要成果:
- 结合基线NLR和特定放射性特征 (表面与质量比,平均灰色,二维曲解) 的模型预测了小鼠的ICI反应 (AUC=0.91) 和人类的OS反应 (AUC=0.75).
- 人类模型准确地将pembrolizumab患者分为分层,分为具有显著不同的预测OS (35个月与6个月) 的组.
结论:
- 预处理放射学和NLR是有希望的非侵入性生物标志物,用于预测aNSCLC中的ICI反应.
- 这些已识别的特征表明,它们可以从临床前模型转化为人类患者,进步精确瘤学.
- 未来的研究将专注于放射基因组方法,以进一步完善ICI反应预测.
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