Spatially-resolved pharmaco-ecology of immunotherapy resistance in lung adenocarcinoma: Single-cell and spatial transcriptomics for mechanism-matched combination therapies

Immune checkpoint inhibitors have reshaped the treatment landscape of lung adenocarcinoma, but primary, adaptive and acquired resistance are still the main clinical obstacles. This review integrates LUAD-specific evidence with broader NSCLC single-cell and spatial-omics studies, emphasizing lung adenocarcinoma where subtype-specific data are available. We discuss how therapeutic stress can select or induce malignant epithelial states that manifest as impaired antigen presentation, altered interferon signaling, partial epithelial-mesenchymal transition, stress tolerance, and hypoxia-related metabolic adaptations. These programs interact with dendritic cells, exhausted and precursor T cells, regulatory T cells, B cells, tertiary lymphoid structures, myeloid cells, cancer-associated fibroblasts, extracellular matrix, and blood vessels to generate a unique resistance-associated spatial immune niche. Special emphasis is given to the niche with adaptive suppression, immunologically excluded interstitial boundaries, myeloid-rich hypoxic-metabolic suppressive niches, antigen-presentation-low residual niches, and tertiary lymphoid structure (TLS)-associated immuno-tissue niche. We further highlight the translational potential of integrating single-cell and spatial features for biomarker discovery, prognostic assessment, interpretation of residual disease, and mechanism-matched combination therapies. Finally, we outline key challenges for clinical implementation, including sampling bias, platform heterogeneity, distinguishing association from causation, and the need for FFPE-compatible testing and prospective validation. Spatially informed single-cell analysis may enable lung adenocarcinoma to shift from descriptive immunophenotyping to ecological diagnosis and precision immune regulation.