Elucidating cellular origins and TME dynamic evolution in NSCLC through multi-omics technologies.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer mortality. Despite progress in targeted therapies and immunotherapy, resistance driven by tumor heterogeneity and dynamic tumor microenvironment (TME) remodeling persists. Multi-omics (single-cell/spatial transcriptomics) reveals lung adenocarcinoma (LUAD) origins in alveolar type 2 (AT2) cells and lineage plasticity via SOX2/WNT/YAP pathways driving aggressive subtypes. The TME, a dynamic ecosystem of immune cells and fibroblasts, evolves through immune-editing phases and cancer-associated fibroblasts (CAF)/tumor-associated macrophage (TAM) crosstalk to foster immunosuppression. Multi-omics identifies key immune subsets (CXCL13CD8T cells, M1/M2 macrophages) and antigen-presenting cancer-associated fibroblasts (apCAFs) as therapeutic targets. Emerging strategies targeting lineage plasticity, TME reprogramming, and microbiome modulation may overcome immune checkpoint blockade (ICB)/tyrosine kinase inhibitor (TKI) resistance. Challenges in spatiotemporal heterogeneity resolution call for artificial intelligence (AI)-driven TME modeling to guide precision interventions. This review highlights multi-omics in bridging NSCLC evolution with clinical translation for personalized therapies.