Unraveling the alterations and biomarkers in the tumor microenvironment in lung adenocarcinoma metastases and their indications for therapeutic response and prognosis.

Lymph nodes, brain, bone, and liver are recognized as the four most common metastatic sites for lung adenocarcinoma (LUAD). Metastasis to these locations exhibits some common features, such as immune suppression, and distinct tumor microenvironment (TME) heterogeneity involving differentiation of immune cells, impacting treatment efficacy and prognosis. Lymph node metastases are characterized by immune suppression with exhausted CD8+ T cells, expanded regulated T cell (Tregs), M2-polarized macrophages, and high programmed death ligand-1 (PD-L1) expression. Brain metastases display an "immune desert" phenotype due to blood-brain barrier constraints, reduced T-cell infiltration, and microglia-mediated immunosuppression. Bone metastases involve osteoclast activation, RANKL/OPG pathway dysregulation, and metabolic reprogramming, while liver metastases show Kupffer cell-driven PD-L1/ programmed death 1(PD-1) axis suppression and elevated Treg infiltration. Key biomarkers across all types of metastases include PD-L1, cytokine profiles, immune cell ratios, and metabolic markers. Therapeutic strategies focus on combination therapies such as immune checkpoint inhibitors (ICIs) with metabolic modulators, localized drug delivery, and biomarker-guided approaches. Challenges in this field encompass spatial heterogeneity, dynamic TME evolution, and clinical translation barriers. Future research directions highlight spatial transcriptomics, microbiome interactions, and organoid models to optimize personalized immunotherapy. This article aims to provide a comprehensive review of regarding TME alterations across these four main metastatic locations of LUAD. It will also discuss relevant TME biomarkers and their clinical significance on therapeutic response and prognosis. We expect this article to serve as a source of evidence and inspiration for the future development of treatment strategies based on LUAD TME.