Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
NanoString Technologies, Seattle, Washington.
Clin Cancer Res. 2020 Aug 15;26(16):4360-4368. doi: 10.1158/1078-0432.CCR-20-0175. Epub 2020 Apr 6.
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.
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].
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, = 0.006; and HR: 0.31, = 0.011, respectively), and overall survival (OS, HR: 0.26, = 0.014; and HR: 0.23, = 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.
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.
只有少数晚期非小细胞肺癌(NSCLC)患者真正从单药 PD-1 检查点阻断中受益,因此需要更强大的预测性生物标志物。
我们评估了 67 例免疫治疗 NSCLC 病例的组织微阵列肿瘤样本,其中 53 例有预处理样本并接受了单药治疗。使用 GeoMx 数字空间分析系统(NanoString Technologies),我们同时在四个通过荧光共定位定义的组织区室中定量了 39 个免疫参数[肿瘤(panCK)、白细胞(CD45)、巨噬细胞(CD68)和非免疫基质]。
每个病例共生成了 156 个蛋白质变量。在单变量未调整分析中,我们发现了 18 个与空间背景下结果相关的标志物,其中 5 个在多重性调整后仍然具有统计学意义。在多变量分析中,CD45 区室中高表达的 CD56 和 CD4 是唯一对所有临床结局(包括无进展生存期[PFS]、总生存期[OS])有预测作用的标志物,其中 PFS(HR:0.24, = 0.006;HR:0.31, = 0.011)和 OS(HR:0.26, = 0.014;HR:0.23, = 0.007)。然后,我们使用基于多重免疫荧光和细胞计数的正交方法(inForm)验证了同一队列中基质中高 CD56 免疫细胞计数与 PFS 和 OS 相关。
这项初步探索性研究表明,数字空间分析技术在鉴定 NSCLC 中 PD-1 检查点阻断反应的空间信息生物标志物方面具有潜力。我们在空间背景下确定了一些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。