Tertiary lymphoid structures predict the neoadjuvant chemoimmunotherapy response of stage III non-small cell lung cancer

Background: Neoadjuvant chemoimmunotherapy is standard for resectable stage III non-small cell lung cancer (NSCLC), yet reliable predictive biomarkers are lacking. Tertiary lymphoid structures (TLS) correlate with survival in NSCLC, but their role in predicting chemoimmunotherapy response remains unclear. This study aimed to characterize TLS comprehensively and develop a composite TLS score to predict pathological response and survival in stage III NSCLC.

Methods: We retrospectively analyzed tumor tissues from patients with stage III (IIIA–IIIC) NSCLC who underwent neoadjuvant chemoimmunotherapy. TLS were characterized using hematoxylin and eosin (H&E) staining and multiplex immunohistochemistry (mIHC) for maturity, density, area, location, and spatial distribution. A composite TLS status score integrating these metrics was developed. Associations with pathological response, survival outcomes, and features of the tumor microenvironment (TME), including programmed death-ligand 1 (PD-L1) expression and immune cell composition were analyzed.

Results: Greater TLS maturity was associated with earlier T-stage and clinical stages. Superior TLS characteristics—including advanced maturity, high density, large area, and stromal location—were significantly correlated with improved progression-free survival (PFS). Furthermore, patients who achieved a major pathological response (MPR) exhibited tumors characterized by more mature and denser TLS, and concomitant increase in tumor-infiltrating lymphocytes. A favorable TLS status, defined as a composite score =4, was a robust predictor of superior PFS [area under the curve (AUC) =0.82, P<0.001]. Furthermore, TLS maturity was inversely correlated with PD-L1 expression in the TME.

Conclusions: TLS status, through its role in actively modulating the immune TME, serves as a predictive biomarker for neoadjuvant chemoimmunotherapy in resectable stage III NSCLC. This may offer a qualified advance for optimizing clinical therapeutics.