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 mum), 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.
- Nandigama, R.
- Cheikh, B. B.
- Wilhelm, J.
- Nikulina, N.
- Klotz, L. V.
- Nabhanizadeh, J.
- Kriegsmann, M.
- Bartkuhn, M.
- Looso, M.
- Jhaveri, N.
- Braubach, O.
- Stenzinger, A.
- Reck, M.
- Grimminger, F.
- Seeger, W.
- Pullamsetti, S. S.
- Weigert, A.
- Stiewe, T.
- Winter, H.
- Savai, R.
Keywords
- driver mutation
- lung cancer
- spatial profiling
- tumor microenvironment
