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.