Spatially resolved whole-transcriptomic and proteomic profiling of lung cancer and immune-microenvironment according to PD-L1 expression

The expression of PD-L1 on tumor cells (TCs) is used as an immunotherapy biomarker in lung cancer, but heterogeneous intratumoral expression is often observed. Using a Digital Spatial Profiler, we performed proteomic and whole-transcriptomic analyses of TCs and immune cells (ICs) in spatially matched areas according to tumor PD-L1 expression and the status of the immune microenvironment. Several findings were validated using immunohistochemistry, The Cancer Genome Atlas, and immunotherapy cohorts. ICs in areas with high PD-L1 expression showed more features indicative of immunosuppression and exhaustion than ICs in areas with low PD-L1 expression. TCs highly expressing PD-L1 within immune-inflamed (IF) areas show up-regulation of pro-inflammatory processes, whereas TCs highly expressing PD-L1 within immune-deficient (ID) areas show up-regulation of various metabolic processes. Using differentially expressed genes of TCs between the IF and ID areas, we identified a novel prognostic gene signature for lung cancer. In addition, the high ratio of CD8+ cells to M2 macrophages was found to predict favorable outcomes in patients with PD-L1-expressing lung cancer after immune checkpoint inhibitor therapy. This study demonstrates that TCs and ICs have distinct spatial features within the tumor microenvironment that are related to tumoral PD-L1 expression and IC infiltration. Overall design: Total 95 areas of interest from 8 Lung Adenocarcinomas were sequenced using Nanostring GeoMX Digital Spatial Profiling (DSP) with (v1.0) Human NGS Whole Transcriptome Atlas RNA Probeset.