Abstract 2436: Gastric cancer-derived tertiary lymphoid structure score from single-cell spatial transcriptomics with pan-cancer validation for immunotherapy response

Abstract Background: Gastric cancer (GC) is a leading cause of cancer-related death, with poor 5-year survival rates for advanced stages, emphasizing the need for biomarkers to guide immunotherapy. Tertiary lymphoid structures (TLSs) in the tumor microenvironment have been linked to favorable prognosis and immune checkpoint blockade response, but the specificity of GC-derived TLS transcriptional signatures and their utility across tumor types remain unclear. We used single-cell-resolution spatial transcriptomics to construct a GC-derived TLS score and evaluated its prognostic and immunotherapy-predictive value in GC and pan-cancer cohorts. Methods: In a cohort of 100 GC patients, TLS presence and maturation were assessed on surgical specimens by H&E, immunohistochemistry, and multiplex immunohistochemistry. A subset of 20 fresh GC tumors underwent high-resolution CosMx single-cell spatial transcriptomics to map immune and stromal cell distribution in TLS-positive versus TLS-negative regions. These spatial data were used to identify TLS regions, define major cell populations, and derive a 78-gene TLS signature, from which we constructed the GC-derived TLS score. The score was applied to pan-cancer bulk transcriptomic datasets and anti-PD-1 melanoma cohorts to assess its prognostic and immunotherapy-predictive performance. Patient-derived xenograft (PDOX) GC tumors were established in huCD34+ HSC-NCG mice and treated with anti-PD-1/CTLA-4 antibodies to test functional associations with TLS score. Results: Patients were stratified into TLS-negative, immature TLS, and mature TLS groups. CosMx spatial transcriptomics resolved 10 major cell populations and mapped their distribution in TLS versus non-TLS regions. From mature TLS regions, we derived a 78-gene signature and constructed a GC-derived TLS score. Higher scores were associated with improved survival and better response to immune checkpoint blockade across multiple tumor types, including low-grade glioma, melanoma, NSCLC, metastatic melanoma, and metastatic GC (AUCs up to 0.857); in melanoma immunotherapy cohorts, high-score patients consistently had superior overall survival. In the humanized GC PDOX model, high TLS score tumors showed enhanced response to anti-PD-1/CTLA-4, with increased tumor cell apoptosis and higher T- and B-cell infiltration, potentially enhancing anti-tumor immunity. Conclusions: We developed the first GC-derived TLS score using single-cell-resolution spatial transcriptomic data and validated its performance across multiple tumor types and in a humanized GC model. This high-resolution score was consistently associated with improved response and survival after immune checkpoint blockade, supporting its use as a precise biomarker for patient stratification and immunotherapy guidance across cancers. Citation Format: Wenbo Zhu, Hongru Shen, Huijun Wang, Ben Liu, Xiangchun Li, Kexin Chen. Gastric cancer-derived tertiary lymphoid structure score from single-cell spatial transcriptomics with pan-cancer validation for immunotherapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2436.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-2436
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 2436: Gastric cancer-derived tertiary lymphoid structure score from single-cell spatial transcriptomics with pan-cancer validation for immunotherapy response

Hongru Shen, Hao Wang, Kexin Chen, Wenbo Zhu et al.
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 2436: Gastric cancer-derived tertiary lymphoid structure score from single-cell spatial transcriptomics with pan-cancer validation for immunotherapy response

Hongru Shen, Hao Wang, Kexin Chen, Wenbo Zhu, Xiangchun Li, Ben Liu
article en

Abstract

Abstract Background: Gastric cancer (GC) is a leading cause of cancer-related death, with poor 5-year survival rates for advanced stages, emphasizing the need for biomarkers to guide immunotherapy. Tertiary lymphoid structures (TLSs) in the tumor microenvironment have been linked to favorable prognosis and immune checkpoint blockade response, but the specificity of GC-derived TLS transcriptional signatures and their utility across tumor types remain unclear. We used single-cell-resolution spatial transcriptomics to construct a GC-derived TLS score and evaluated its prognostic and immunotherapy-predictive value in GC and pan-cancer cohorts. Methods: In a cohort of 100 GC patients, TLS presence and maturation were assessed on surgical specimens by H&E, immunohistochemistry, and multiplex immunohistochemistry. A subset of 20 fresh GC tumors underwent high-resolution CosMx single-cell spatial transcriptomics to map immune and stromal cell distribution in TLS-positive versus TLS-negative regions. These spatial data were used to identify TLS regions, define major cell populations, and derive a 78-gene TLS signature, from which we constructed the GC-derived TLS score. The score was applied to pan-cancer bulk transcriptomic datasets and anti-PD-1 melanoma cohorts to assess its prognostic and immunotherapy-predictive performance. Patient-derived xenograft (PDOX) GC tumors were established in huCD34+ HSC-NCG mice and treated with anti-PD-1/CTLA-4 antibodies to test functional associations with TLS score. Results: Patients were stratified into TLS-negative, immature TLS, and mature TLS groups. CosMx spatial transcriptomics resolved 10 major cell populations and mapped their distribution in TLS versus non-TLS regions. From mature TLS regions, we derived a 78-gene signature and constructed a GC-derived TLS score. Higher scores were associated with improved survival and better response to immune checkpoint blockade across multiple tumor types, including low-grade glioma, melanoma, NSCLC, metastatic melanoma, and metastatic GC (AUCs up to 0.857); in melanoma immunotherapy cohorts, high-score patients consistently had superior overall survival. In the humanized GC PDOX model, high TLS score tumors showed enhanced response to anti-PD-1/CTLA-4, with increased tumor cell apoptosis and higher T- and B-cell infiltration, potentially enhancing anti-tumor immunity. Conclusions: We developed the first GC-derived TLS score using single-cell-resolution spatial transcriptomic data and validated its performance across multiple tumor types and in a humanized GC model. This high-resolution score was consistently associated with improved response and survival after immune checkpoint blockade, supporting its use as a precise biomarker for patient stratification and immunotherapy guidance across cancers. Citation Format: Wenbo Zhu, Hongru Shen, Huijun Wang, Ben Liu, Xiangchun Li, Kexin Chen. Gastric cancer-derived tertiary lymphoid structure score from single-cell spatial transcriptomics with pan-cancer validation for immunotherapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2436.

Cancer ResearchVol. 86(7_Supplement)
Tianjin Medical University Cancer Institute and Hospital (CN)
Good health and well-being
Openalex Percentile: Top 8%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.