TLS as Predictors and Targets in Neoadjuvant Chemoimmunotherapy for NSCLC

Tertiary lymphoid structures (TLS) have emerged as critical modulators of antitumor immunity in non-small cell lung cancer (NSCLC), with growing evidence supporting their role as both prognostic biomarkers and functional targets in neoadjuvant chemoimmunotherapy. TLS are organized ectopic lymphoid aggregates that facilitate local antigen presentation, T and B cell activation, and memory immune responses within the tumor microenvironment. Their presence and maturation status correlate with favorable clinical outcomes and enhanced responsiveness to immune checkpoint inhibitors. Despite these insights, several obstacles hinder clinical translation. Current approaches remain limited in dynamically monitoring TLS evolution during treatment, and the underlying immunoregulatory mechanisms-particularly interactions among immune subsets, stromal components, and tumor cells-are not fully elucidated. Additionally, translation faces challenges including inter-institutional variability, lack of standardized assessment criteria, and the need for multi-center prospective validation. Integrating multimodal technologies-high-plex imaging, spatial transcriptomics, and digital pathology-with AI-based platforms holds promise for refined TLS characterization and real-time monitoring. Near-term priorities include optimizing dynamic monitoring techniques and establishing standardized scoring systems. Medium-to-long-term priorities encompass multi-center trials to validate TLS utility across diverse populations, identify novel drivers of TLS formation, and develop optimized combinatorial immunotherapy regimens that leverage TLS as both predictive biomarkers and therapeutic targets. By bridging basic immunology and clinical oncology, TLS are poised to emerge as key regulatory nodes in precision cancer immunotherapy, which may catalyze a paradigm shift in the neoadjuvant NSCLC landscape, enabling a closed-loop management framework encompassing prediction, intervention, and dynamic efficacy optimization across the entire continuum of patient care.