Purpose: Only a minority of patients with advanced non–small cell lung cancer (NSCLC) truly benefits from single-agent PD-1 checkpoint blockade, and more robust predictive biomarkers are needed. Experimental Design: We assessed tumor samples from 67 immunotherapy-treated NSCLC cases represented in a tissue microarray, 53 of whom had pretreatment samples and received monotherapy. Using GeoMx Digital Spatial Profiling System (NanoString Technologies), we quantified 39 immune parameters simultaneously in four tissue compartments defined by fluorescence colocalization [tumor (panCK+), leucocytes (CD45+), macrophages (CD68+), and nonimmune stroma]. Results: A total of 156 protein variables were generated per case. In the univariate unadjusted analysis, we found 18 markers associated with outcome in spatial context, five of which remained significant after multiplicity adjustment. In the multivariate analysis, high levels of CD56 and CD4 measured in the CD45 compartment were the only markers that were predictive for all clinical outcomes, including progression-free survival (PFS, HR: 0.24, P = 0.006; and HR: 0.31, P = 0.011, respectively), and overall survival (OS, HR: 0.26, P = 0.014; and HR: 0.23, P = 0.007, respectively). Then, using an orthogonal method based on multiplex immunofluorescence and cell counting (inForm), we validated that high CD56+ immune cell counts in the stroma were associated with PFS and OS in the same cohort. Conclusions: This pilot scale discovery study shows the potential of the digital spatial profiling technology in the identification of spatially informed biomarkers of response to PD-1 checkpoint blockade in NSCLC. We identified a number of relevant candidate immune predictors in spatial context that deserve validation in larger independent cohorts. This article is featured in Highlights of This Issue, [p. 4169][1] [1]: /lookup/volpage/26/4169?iss=16

中文翻译：

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与非小细胞肺癌 (NSCLC) 中有益的 PD-1 检查点阻断相关的生物标志物使用 High-Plex 数字空间分析确定。

目的：只有少数晚期非小细胞肺癌 (NSCLC) 患者真正受益于单药 PD-1 检查点阻断，因此需要更可靠的预测性生物标志物。实验设计：我们评估了来自组织微阵列中代表的 67 例免疫疗法治疗的 NSCLC 病例的肿瘤样本，其中 53 例具有预处理样本并接受单一疗法。使用 GeoMx 数字空间分析系统（NanoString Technologies），我们同时量化了由荧光共定位定义的四个组织区室中的 39 个免疫参数[肿瘤 (panCK+)、白细胞 (CD45+)、巨噬细胞 (CD68+) 和非免疫基质]。结果：每个病例共产生 156 个蛋白质变量。在单变量未调整分析中，我们发现了 18 个与空间背景下的结果相关的标记，其中五个在多重性调整后仍然显着。在多变量分析中，CD45 区室中测量的高水平 CD56 和 CD4 是唯一可预测所有临床结果的标志物，包括无进展生存期（PFS，HR：0.24，P = 0.006；HR：0.31，P = 0.011，分别）和总生存期（OS，HR：0.26，P = 0.014；HR：0.23，P = 0.007，分别）。然后，使用基于多重免疫荧光和细胞计数 (inForm) 的正交方法，我们验证了基质中高 CD56+ 免疫细胞计数与同一队列中的 PFS 和 OS 相关。结论：这项试点规模的发现研究显示了数字空间分析技术在识别 NSCLC 中对 PD-1 检查点封锁反应的空间通知生物标志物方面的潜力。我们在空间环境中确定了许多相关的候选免疫预测因子，值得在更大的独立队列中进行验证。这篇文章在本期亮点 [p. 4169][1][1]：/lookup/volpage/26/4169?iss=16