NDC80 as a Prognostic Biomarker: Insights From Single‐Cell RNA Sequencing and Machine Learning in Lung Adenocarcinoma

Natural killer T (NKT) cells play a fundamental role in tumor architecture and dynamically interact with diverse immune populations within the tumor microenvironment, critically influencing the progression and therapeutic response of lung adenocarcinoma (LUAD). In this study, we integrated single‐cell RNA sequencing with machine learning to systematically identify NKT cell–related genes and evaluate their prognostic and immunotherapeutic relevance in LUAD. By analyzing multiple datasets and employing a range of machine learning algorithms, we constructed and validated a robust prognostic signature for LUAD. Among the NKT cell‐associated genes analyzed, the random survival forest algorithm identified NDC80 as a top‐ranking gene with paramount prognostic importance. Further investigation revealed a significant association between NDC80 expression and immune cell infiltration patterns. Subsequent in vitro functional experiments confirmed that NDC80 regulates cellular proliferation and metastatic capacity in LUAD. In summary, our findings establish NDC80 as a promising prognostic biomarker and a potential target for immunotherapy in patients with LUAD.