Noninvasive Imaging Assessment of Tertiary Lymphoid Structures and Immunotherapy Response in Gastric Cancer: A Multicenter Study

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Authors: Zepang Sun, Zhenhui Li, M. Usman Ahmad, Yun Zhu, Zixia Zhou, Kangneng Zhou, Lin Wu, Chuanli Chen, Qingyu Yuan, T. Zhang, Yan Chen, Jingjing Xie
+6 more Wanying Feng, Yikai Xu, Wenjun Xiong, Wei Wang, G. Li, Yuming Jiang
Cited by: 0
References: 35

Abstract

PURPOSE: Tertiary lymphoid structures (TLS) are associated with improved survival and enhanced response to anticancer immunotherapy. This study aimed to develop a CT imaging-based approach for noninvasive assessment of TLSs and immunotherapy response. EXPERIMENTAL DESIGN: This study involved 3,155 patients with gastric cancer. TLSs were classified into four stages (absence, Agg, FL-I, and FL-II) according to their maturation based on IHC staining. A CT imaging-based TLS scoring model (ctTLS) was developed to assess TLS status, subsequently classified into four classes (ctTLS-0/1/2/3). We next evaluated the model's associations with prognosis and immunotherapy response. To enhance the model's interpretability, we analyzed multiomics data and employed the Shapley value strategy. RESULTS: The ctTLS model achieved high accuracies in predicting TLS status in the internal validation (AUC range, 0.727-0.809) and external validation (0.704-0.807) cohorts. In retrospective and prospective validation cohorts, ctTLSs exhibited significant associations with both disease-free and overall survival (HR range, 0.206-0.634; all P < 0.01). Shapley value analysis highlighted ctTLSs as the strongest predictor of TLS status. Upon analyzing multiomics data, we found that higher ctTLS levels positively correlated with tumor immune activation and apoptosis signaling, while displaying a negative correlation with tumor proliferation and metabolism signaling. Intriguingly, patients with high ctTLSs (but not low ctTLSs) exhibited substantial benefits from immunotherapy (P < 0.0001). The objective response rate of four ctTLS classes was 16.7% in ctTLS-0, 35.5% in ctTLS-1, 45.8% in ctTLS-2, and 53.8% in ctTLS-3. CONCLUSIONS: The ctTLS model could noninvasively assess TLS status, enabling improved prognosis evaluation and informed decisions about immunotherapy.

Fields of Study & Subjects

Cancer Immunotherapy and Biomarkers Gastric Cancer Management and Outcomes Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Clinical Cancer Research
Volume
32
Issue
8
Pages
1486–1498
Publication date
5 February 2026
Language
EN