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Abstract The expression of PD-L1 on tumor cells (TC) is used as an immunotherapy biomarker in lung cancer, but heterogeneous intratumoral expression is often observed. To better understand heterogeneity in the lung cancer tumor microenvironment, we performed proteomic and whole-transcriptomic digital spatial profiling analyses of TCs and immune cells (IC) in spatially matched areas based on tumor PD-L1 expression and the status of the immune microenvironment. We validated our findings using IHC, data from The Cancer Genome Atlas, and immunotherapy cohorts. ICs in areas with high PD-L1 expression on TCs showed more features, indicative of immunosuppression and exhaustion, than ICs in areas with low PD-L1 expression on TCs. TCs highly expressing PD-L1 within immune-inflamed areas showed upregulation of proinflammatory processes, whereas TCs highly expressing PD-L1 within immune-deficient areas showed upregulation of various metabolic processes. Using differentially expressed genes of TCs between the immune-inflamed and immune-deficient areas, we identified a prognostic gene signature for lung cancer. In addition, we found that a high ratio of CD8+ cells to M2 macrophages predicted favorable outcomes in patients with PD-L1–expressing lung cancer after immune checkpoint inhibitor therapy. Overall, this study demonstrates that TCs and ICs have distinct spatial features within the lung tumor microenvironment that are related to tumor PD-L1 expression and IC infiltration.
Koh et al. (Thu,) studied this question.