Non-coding RNA networks remodeling metastatic signaling in the lung cancer microenvironment: a focus on TGF-β signaling and its crosstalk with Wnt/β-catenin, HIF, Notch, integrin, and CXCL12/CXCR4 pathways.

Lung cancer mortality is driven largely by metastasis, which arises from tumor-intrinsic alterations and interactions within the tumor microenvironment (TME). Non-coding RNAs (ncRNAs), including miRNAs, lncRNAs, circRNAs, and extracellular vesicle-associated RNAs, regulate these interactions by modulating gene expression and intercellular signaling. This review examines ncRNA-mediated regulation of metastatic signaling in lung cancer, with particular emphasis on TGF-β signaling and its crosstalk with five additional pathways relevant to tumor dissemination: Wnt/β-catenin, hypoxia-inducible factor signaling, Notch, integrin/focal-adhesion signaling, and the CXCL12/CXCR4 axis. Particular attention is given to epithelial-mesenchymal transition, cancer stemness, extracellular matrix remodeling, angiogenesis, immune escape, and metastatic niche formation. The available evidence indicates that ncRNAs often act through interconnected regulatory circuits rather than isolated targets, and that their effects depend strongly on histological context, including LUAD, LUSC, other NSCLC subtypes, and SCLC, as well as on molecular background, cellular compartment, and experimental model. Findings derived from one histological or molecular setting should therefore not be assumed to apply uniformly across lung cancer. Hypoxia, cancer-associated fibroblasts, tumor-associated macrophages, and extracellular vesicles can alter ncRNA programs, while ncRNAs can reciprocally reshape these components. We also examine the potential translational relevance of ncRNA-based biomarkers and therapeutic strategies; however, most remain at the preclinical or exploratory stage and require further mechanistic, analytical, prospective, and clinical validation. Major barriers include delivery, target specificity, extracellular-vesicle standardization, reproducibility, and patient selection. A network-based interpretation may therefore provide a more realistic framework for understanding ncRNA contributions to lung cancer metastasis.