Neutrophil extracellular traps (NETs) have emerged as key modulators in the tumor microenvironment, yet their cellular heterogeneity, molecular mechanisms, and clinical relevance in lung adenocarcinoma (LUAD) remain elusive. Here, we performed an integrative single‑cell and multi‑omics dissection of NETs activity across LUAD tissues. Single‑cell transcriptomics revealed that NETs signatures were predominantly enriched in neutrophils but also detectable in dendritic cells and macrophages, where NETs‑high subpopulations exhibited intensified intercellular signaling. Genomic profiling indicated that NETs‑related genes were largely affected by missense mutations and single nucleotide polymorphisms (C > A and C > T), with frequent alterations in PTPRD, VCAN, and ZNF804A. Functional enrichment associated these genes with immune regulation and tumor‑promoting pathways. By integrating seven independent clinical cohorts, we constructed a machine‑learning–based NETs‑related prognostic signature (NETs‑Sig) that robustly predicted overall survival across datasets (AUC > 0.75). Patients with high NETs‑Sig scores exhibited immune‑cold phenotypes characterized by reduced immune infiltration and impaired antigen presentation, whereas low‑score cases displayed elevated MHC‑II expression, enhanced antigen processing, and putative sensitivity to immunotherapy. Experimental validation further identified AP2S1 as a central NETs‑Sig gene—overexpressed in multiple cancers and functionally promoting invasion and metastasis in LUAD cells. Together, our study delineates the cellular, genomic, and immunological frameworks of NETs in LUAD, establishes NETs‑Sig as a clinically actionable biomarker for risk stratification and immunotherapy guidance, and highlights AP2S1 as a promising therapeutic target for translational intervention.
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