Abstract 3962: Pan-cancer spatial characterization of tertiary lymphoid structures
Authors: Kyung Serk Cho, Yunhe Liu, Guangsheng Pei, Jianfeng Chen, Tieling Zhou, Khalida M. Wani, Alejandra G. Serrano, Sharia D. Hernandez, Akshaya S. Jadhav, Daiwei Zhang, Hannah C. Beird, Jiahui Jiang, Diana Shamsutdinova, Xinmiao Yan, Yibo Dai, Enyu Dai, Ashley L. Wilson, Anne Waldrep, Fuduan Peng, Wei Lu, Yang Liu, Jimin Min, Paola A. Guerrero, Idania C. Julio, Tong Yin, Shin Hsu Shi, Sabitha Prabhakaran, Scott E. Kopetz, Dipen M. Maru, Alexander Lazar, Amir A. Jazaeri, Michael Green, Mingyao Li, Catherine Sautes-Fridman, Wolf H. Fridman, Andrew Futreal, Luisa M. Soto, Humam Kadara, Anirban Maitra, Suet Yi Leung, Jianjun Gao, Linghua Wang
Journal: Cancer Research (2025)

Abstract Tertiary lymphoid structures (TLS) are frequently observed in various solid tumors, where they play a pivotal role in regulating anti-tumor immune responses. Despite their importance, our understanding of TLS and their interactions with cancer cells within complex tissue environments remains limited. Recent advances in spatial transcriptomics (ST) technology offer new possibilities for investigating the spatial and phenotypic heterogeneity of TLS. We developed TLSphenotyper, a computational framework for automatic TLS segmentation, labeling, extraction, and comprehensive profiling of TLS using spot-level ST data. It enables reproducible and efficient large-scale analysis of TLS. To accurately map TLS and characterize their cellular composition, we created a robust TLS-specific gene signature and enhanced the resolution of spot-level ST data to near-single-cell resolution. TLSphenotyper computes cell type-specific gene signature scores to generate a detailed cell type probability map across the tissue section. This map facilitates segmentation of key cellular components within TLS, enabling precise spatial mapping and colocalization analysis of major cell types and their transcriptomic states. Additionally, TLSphenotyper automatically analyzes and classifies TLSs based on their maturation stages, offering insights into their phenotypic and functional heterogeneity. Its accuracy and precision were validated using single-cell ST data generated from adjacent tissue sections. Further benchmarking against established deconvolution methods demonstrated superior accuracy and granularity in spatial cell type inference, cell organization and co-location analysis within TLS regions. To further investigate TLS and their interactions with cancer cells in a pan-cancer setting, we curated a comprehensive dataset of publicly available and in-house spot-level ST data, encompassing 340 tissue sections from 12 distinct cancer types. This represents the largest collection of ST data on human cancer assembled to date. Using TLSphenotyper, we identified and characterized 695 TLSs across 340 tissues. Our analysis revealed substantial variation in TLS presence, size, location, density, cellular composition, and maturation stage across cancer types. TLSs at different maturation stages exhibited distinct transcriptomic profiles. Notably, cancer cells in proximity to TLS demonstrated significantly different activity across key signaling pathways compared to those farther away, suggesting that TLS interaction can shape cancer cell expression profiles and cellular states. Additionally, patients classified based on the maturation stages of TLS demonstrated distinct survival outcomes. Together, this study provides novel insights into the spatial dynamics and phenotypic heterogeneity of TLS, identifies potential targets for modulating TLS, and establishes a valuable resource for the research community. Citation Format: Kyung Serk Cho, Yunhe Liu, Guangsheng Pei, Jianfeng Chen, Tieling Zhou, Khalida M. Wani, Alejandra G. Serrano, Sharia D. Hernandez, Akshaya S. Jadhav, Daiwei Zhang, Hannah C. Beird, Jiahui Jiang, Diana Shamsutdinova, Xinmiao Yan, Yibo Dai, Enyu Dai, Ashley L. Wilson, Anne Waldrep, Fuduan Peng, Wei Lu, Yang Liu, Jimin Min, Paola A. Guerrero, Idania C. Julio, Tong Yin, Shin Hsu Shi, Sabitha Prabhakaran, Scott E. Kopetz, Dipen M. Maru, Alexander Lazar, Amir A. Jazaeri, Michael Green, Mingyao Li, Catherine Sautes-Fridman, Wolf H. Fridman, Andrew Futreal, Luisa M. Soto, Humam Kadara, Anirban Maitra, Suet Yi Leung, Jianjun Gao, Linghua Wang. Pan-cancer spatial characterization of tertiary lymphoid structures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3962.