Recapitulating lung cancer metastasis : Advances in organoid models and challenges in clinical translation (Review).

Lung cancer remains a significant global health challenge, with metastatic progression being the leading driver of mortality. Organoid technology provides a tractable, physiologically relevant platform to model key aspects of lung cancer metastasis . The present review summarized methodologies for constructing and interrogating these models, covering tissue sources, culture modalities, gene editing and transplantation; applications in studying metastatic mechanisms, drug screening and capturing intra‑ and intertumoral heterogeneity are also highlighted. Persistent challenges include standardizing derivation and culture conditions, improving preservation of tumor‑microenvironmental interactions, expanding immune‑competent and vascularized models, and addressing scalability, cost, and regulatory and ethical considerations for clinical translation. Future directions include integrating multi‑omics approaches and spatial profiling, leveraging artificial intelligence for image and response analytics, advancing immune‑organoid models and establishing shared standards, reference materials and reporting guidelines to enhance reproducibility and clinical impact.