Tertiary lymphoid structure patterns predicted anti-PD1 therapeutic responses in gastric cancer.

Objective: Recent studies have highlighted the distinct value of tertiary lymphoid structure (TLS) for immunotherapeutic response prediction. However, it remains unclear whether TLS could play such roles in gastric cancer (GC).

Methods: In this study, tumor tissue slices from 292 GC patients from Zhongshan Hospital were firstly reviewed to explore the correlation between TLS and clinical characteristics. Subsequently, we curated 38 reported genes that may function as triggers of TLS and performed consensus molecular subtyping in public RNA-seq datasets to determine TLS patterns in GC. Based on the differentially expressed genes acquired from two TLS patterns, we quantified TLS-related genes on the principal component analysis (PCA) algorithm to develop TLS score. A Zhongshan immunotherapy cohort including 13 patients who received programmed cell death 1 (PD1) blockade therapy was established to conduct RNA sequencing analysis and multiplex immunohistochemistry (mIHC) tests using formalin-fixed and paraffin-embedded (FFPE) tissues. The corresponding TLS score and immune cell counts were further compared based on therapeutic response variations.

Results: Mature TLS was revealed as an independent prognostic factor in 292 GC patients. Patients with higher TLS score was characterized by prolonged survival time and superior response to immunotherapy. TLS score was correlated with immunotherapy-related characters, such as microsatellite instability (MSI) and tumor mutation burden (TMB). In addition, RNA-seq data analysis in the Zhongshan immunotherapy cohort indicated that a higher TLS score was correlated with a superior response to PD1 blockade therapy. mIHC tests also revealed that PD1⁺CD8⁺ T cell counts were significantly increased in the high-TLS score group.

Conclusions: This study highlighted that TLS was significantly associated with immune landscape diversity and complexity. Quantitatively evaluating TLS patterns of individual tumor will strengthen our understanding of TME characteristics and promote more effective immunotherapy strategies.