Evidence map›Paper›PMID 40944717›Full record

ArticleCancer immunology, immunotherapy : CII2025

Tertiary lymphoid structures gene signature predicts response to immunotherapy plus chemotherapy in advanced non-small cell lung cancer.

Wei Du, Bijing Xiao, Xuan Yang, Jianhua Zhan, Haishuang Sun, Yunpeng Yang, Wenfeng Fang, Yan Huang, Dongchen Sun, Shaodong Hong and 1 more

Erratum issuedAbstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
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  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Wei DuState 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.
Bijing XiaoState 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.
Xuan YangState 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.
Jianhua ZhanState 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.
Haishuang SunState 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.
Yunpeng YangState 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.
Wenfeng FangState 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.
Yan HuangState 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.
Dongchen SunState 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. sundc@sysucc.org.cn.
Shaodong HongState 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. hongshd@sysucc.org.cn.
Li ZhangState 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. zhangli@sysucc.org.cn.

Funding

Guangzhou Municipal Science and Technology Project 2024A04J6485National Natural Science Foundation of China 82172713, 82241232, and 82272789National Science and Technology Major Project 2024ZD0520200, 2024ZD0520205Natural Science Foundation of Guangdong Province 2023B1515020008
6 · The paper itself

Abstract

backgroundNon-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.

methodsData 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.

resultsTLS 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.

conclusionsTLS 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.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorCarcinoma, Non-Small-Cell LungImmunotherapyLung NeoplasmsTertiary Lymphoid StructuresAgedB7-H1 AntigenFemaleHumansMaleMiddle AgedPrognosisB7-H1 AntigenBiomarkers, TumorFirst-lineNon-small cell lung cancerPlatinum-based chemotherapy combined with immunotherapyTertiary lymphoid structures

Identifiers

PMID40944717
PMCPMC12433388

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.