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Updated: Jan 6, 2026

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Tertiary lymphoid structures gene signature predicts response to immunotherapy plus chemotherapy in advanced
Wei Du1,2, Bijing Xiao1,2, Xuan Yang1,2
1State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Background:
Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality, with chemoimmunotherapy (CIT) as the first-line standard for advanced NSCLC without driver mutations. However, predictive biomarkers for CIT response are limited. Tertiary lymphoid structures (TLS) play a critical role in antitumor immunity and may serve as potential biomarkers. This study aimed to screen and validate a TLS-derived gene signature to predict responses to first-line CIT in advanced NSCLC.
Methods:
Data from three randomized trials (ORIENT-11, OAK, POPLAR) and The Cancer Genome Atlas-NSCLC were analyzed. TLS scores were computed via ssGSEA based on 17 TLS-related gene signatures. Patients were stratified into TLS-high and TLS-low groups. The predictive value was assessed by survival analysis, nomograms, and receiver operating characteristic curve. Correlations with programmed cell death 1 ligand (PD-L1) and ImmuneScore were evaluated.
Results:
TLS signature 3 was identified as a predictive biomarker. In ORIENT-11, high signature 3 scores correlated with longer progression-free survival (PFS) (9.92 vs 6.77 months, p = 0.001) and overall survival (OS) (not reached vs 17.60 months, p < 0.001). Multivariate analysis confirmed signature 3 as an independent predictor for both outcomes (PFS HR = 2.14, p = 0.006; OS HR = 2.24, p = 0.002). A nomogram integrating signature 3 and clinicopathologic factors showed strong discriminative power. Signature 3 also correlated with PD-L1 expression and 'hot' immune phenotypes, enhancing prediction in PD-L1-negative subsets.
Conclusions:
TLS signature 3 predicts CIT response independently of PD-L1, improving outcomes in PD-L1-negative patients and complementing PD-L1 testing. Integration into clinical practice may refine treatment decisions, warranting further mechanistic and clinical validation.

