Abstract
OBJECTIVE: Tertiary Lymphoid Structures (TLSs) are ectopic lymphoid aggregates that form within the tumor microenvironment (TME) and are increasingly recognized as potential prognostic biomarkers in various cancers. However, the spatial heterogeneity and prognostic value of TLSs in esophageal squamous cell carcinoma (ESCC) remain poorly defined. This study aimed to characterize the spatial distribution patterns of TLSs and tumor-infiltrating lymphocytes (TILs), and to establish a refined prognostic model for ESCC patients in both surgery-only and neoadjuvant therapy cohorts. METHODS: The TLSs were quantified through microscopic evaluation and digital slide analysis and correlated with prognosis by Cox regression and Kaplan-Meier analyses. The heterogeneity and clinical prognostic value of TLSs were explored by analyzing their distribution, density, and maximum diameter in different regions of ESCC patients. RESULTS: TLSs showed spatial distribution heterogeneity in the tumor area, adjacent area, and marginal area, with consistent differences observed across different paraffin blocks. The distribution of iTIL and sTIL also exhibited certain spatial heterogeneity. In the surgical cohort (n = 117), the median Overall Survival (OS) and Disease-Free Survival (DFS) were 33 months and 15 months, respectively. Univariate analyses showed that TLS presence in tumor (TG), TLS-rich regions (TR), TLS ratio in normal regions (NR), tumor-stroma ratio (TSR), and both iTIL and sTIL levels were significantly associated with OS (p < 0.05). Multivariate analysis confirmed N stage, TG, TR, TLS abundance in adjacent regions (NA), and TLS density in tumor (NT), along with TSR, iTIL, and sTIL, as independent predictors of prognosis (p < 0.05). High TLS presence in tumor regions (TG-high) was associated with significantly improved OS (log-rank p = 0.026). CONCLUSION: This study demonstrates that TLSs and TILs in ESCC are not only prognostically relevant but also spatially heterogeneous. The refined spatial immune profiling across multiple tumor regions improves prognostic stratification and may inform personalized treatment planning in ESCC.