彭布罗利珠单抗
医学
肺癌
流式细胞术
内科学
质量细胞仪
免疫疗法
癌症
细胞仪
癌症研究
肺
免疫学
病理
生物
遗传学
表型
基因
作者
Philippe Rochigneux,Aaron Lisberg,Alejandro J. Garcia,Samuel Granjeaud,Anne Madroszyk,Stéphane Fattori,Anthony Gonçalvès,Raynier Devillier,Pauline Maby,N. Salem,Laurent Gorvel,Brice Chanez,Jaklin Gukasyan,James Carroll,Jonathan W. Goldman,Anne-Sophie Chrétien,Daniel Olive,Edward B. Garon
标识
DOI:10.1158/1078-0432.ccr-22-1386
摘要
Abstract Purpose: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of non–small cell lung cancer (NSCLC), but predictive biomarkers of their efficacy are imperfect. The primary objective is to evaluate circulating immune predictors of pembrolizumab efficacy in patients with advanced NSCLC. Experimental Design: We used high-dimensional mass cytometry (CyTOF) in baseline blood samples of patients with advanced NSCLC treated with pembrolizumab. CyTOF data were analyzed by machine-learning algorithms (Citrus, tSNE) and confirmed by manual gating followed by principal component analysis (between-group analysis). Results: We analyzed 27 patients from the seminal KEYNOTE-001 study (median follow-up of 60.6 months). We demonstrate that blood baseline frequencies of classical monocytes, natural killer (NK) cells, and ICOS+ CD4+ T cells are significantly associated with improved objective response rates, progression-free survival, and overall survival (OS). In addition, we report that a baseline immune peripheral score combining these three populations strongly predicts pembrolizumab efficacy (OS: HR = 0.25; 95% confidence interval = 0.12–0.51; P < 0.0001). Conclusions: As this immune monitoring is easy in routine practice, we anticipate our findings may improve prediction of ICI benefit in patients with advanced NSCLC.
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