泛肿瘤基因组生物标志物用于基于 PD-1 检查点阻断的免疫治疗。
Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy.
机构信息
Merck & Co., Kenilworth, NJ 07033, USA.
Fox Chase Cancer Center, Philadelphia, PA 19111, USA.
出版信息
Science. 2018 Oct 12;362(6411). doi: 10.1126/science.aar3593.
Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.
程序性死亡蛋白-1（PD-1）和程序性死亡配体-1（PD-L1）检查点阻断免疫疗法在多种癌症中引发了持久的抗肿瘤作用，但并非所有患者都有反应。我们报告了来自四项 KEYNOTE 临床试验的 22 种肿瘤类型的 300 多个患者样本的评估。肿瘤突变负担（TMB）和 T 细胞浸润基因表达谱（GEP）联合具有识别 PD-1 抗体 pembrolizumab 应答者和无应答者的预测作用。TMB 和 GEP 独立地预测了反应，并且表现出低度相关性，表明它们捕获了新抗原性和 T 细胞激活的不同特征。对癌症基因组图谱数据库的分析表明 TMB 和 GEP 相关性较低，联合分层分析揭示了具有靶向耐药生物学的生物标志物定义模式。这些生物标志物可能通过指导合理选择抗 PD-1 单药治疗和联合免疫治疗方案，在临床试验设计中具有实用性。
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