Spatial proteomics profiling reveals oncogene-specific immune niches and prognostic markers in NSCLC

RATIONALE: Only subset of patients with Non-Small Cell Lung Cancer (NSCLC) benefit from immunotherapy and this is partly due to limited understanding of how oncogenic mutations shape the tumor microenvironment (TME). OBJECTIVES: To define how EGFR and KRAS mutations influence the spatial organization and immune composition of the NSCLC TME. METHODS: We conducted 38-marker high-plex immunofluorescence to 197 NSCLC tumors (>2 million cells) stratified by EGFR and KRAS genotypes. Quantitative phenotyping and spatial analyses, including cellular neighborhoods (CN), nearest neighbors (NNs = 5-20), and spatial proximity profiling (25-100 μm), were performed to assess immune architecture and clinical correlations. MEASUREMENTS AND MAIN RESULTS: EGFR- and KRAS-mutant tumors showed higher tumor cell density and reduced immune infiltration compared with wild-type tumors. Both mutation types were associated with depletion of cytotoxic T cells, dendritic cells, and granulocytes, while EGFR-mutant tumors showed enrichment of M2-like tumor-associated macrophages (TAMs). CN-analysis identified 14 spatial clusters, with reduced cytotoxic and helper T cell-rich neighborhoods in mutant tumors. NN-analysis revealed shorter distances between M2-like TAMs in EGFR-mutant tumors and greater immune exclusion in non-mutants. Spatial proximity revealed higher densities of T-regs, TAMs near tumor cells in KRAS-mutant tumors. All spatial metrics correlated significantly with prognosis in Cox proportional hazards models, highlighting immune cell positioning as an important predictor of outcome. CONCLUSIONS: EGFR- and KRAS-mutant tumors remodel the NSCLC immune landscape, creating distinct immunosuppressive and immune-excluded niches. Spatial proteomics reveals prognostic immune architectures that may guide mutation-directed immunotherapy strategies.