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微卫星的不稳定性,不匹配的修复,和瘤突变负担在肺癌

Oana C Rosca¹, Oana E Vele²

¹Molecular Pathologist/Cytopathologist, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell; Department of Pathology and Laboratory Medicine, 2200 Northern Boulevard, Suite 104, Greenvale, NY 11548, USA.

Surgical pathology clinics

|May 1, 2024

概括

编程死亡连接体1 (PD-L1),微卫星不稳定性/不匹配修复缺陷 (MSI/MMR) 和瘤突变负担 (TMB) 是预测癌症免疫治疗反应的关键生物标志物. 未来的算法可能将这些和新型标记器结合起来,可能使用人工智能,以优化治疗选择.

科学领域:

在瘤学瘤学.
免疫治疗是一种免疫疗法.
生物标志物发现发现

背景情况:

美国FDA批准了编程死亡配体1 (PD-L1) 作为非小细胞肺癌中免疫检查点抑制剂 (ICI) 的伴侣诊断,改善了患者的生存率.
对ICI反应的患者的选择仍然是一个挑战,这促使对额外的预测生物标志物的调查.

研究的目的:

审查PD-L1,微卫星不稳定性/不匹配修复缺陷 (MSI/MMR) 和瘤突变负担 (TMB) 作为免疫疗法的预测生物标志物的作用.
讨论对这些生物标志物的测试方法和检测设计进行协调的持续努力.
探索未来的方向,包括新的生物标志物和人工智能 (AI),以优化免疫疗法资格确定.

主要方法:

对癌症免疫治疗中PD-L1,MSI/MMR和TMB的临床数据和现有文献的审查.
讨论生物标志物标准化和实施的当前挑战和正在进行的研究.
探索潜在的未来算法,整合多个生物标志物和人工智能.

主要成果:

确立了PD-L1,MSI/MMR和TMB作为免疫治疗反应的独立预测生物标志物.
临床数据支持这些生物标志物在患者选择ICI治疗中的有用性.
测试和测试优化的协调对于可靠的生物标志物评估至关重要.

结论:

PD-L1,MSI/MMR和TMB对于预测免疫疗法的疗效至关重要.
未来的免疫疗法选择算法可能会将这些已知生物标志物与新生物标志物相结合.
人工智能有望开发复杂的算法,以指导基于复杂的遗传数据的ICI选择.

关键词:

生物标志物生物标志物免疫检查点抑制剂免疫检查点抑制剂免疫治疗是一种免疫疗法.肺癌是一种肺癌.微卫星的不稳定性/不匹配修复缺陷瘤突变负担是瘤突变负担.

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