Evidence map›Paper›PMID 42311665›Full record

ArticleFrontiers in immunology2026

Systematic optimization of PD-L1 and CLDN18.2 CAR-T designs identifies a bicistronic dual-target, double-CD3ζ architecture with enhanced antitumor activity in gastric cancer.

Xiang Zhang, Yao-Jie Kong, Jing-Yao Li, Heng-Hui Li, Liang Chen

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xiang Zhang *School of Medicine, Shanghai University, Shanghai, China.
Yao-Jie Kong *School of Medicine, Shanghai University, Shanghai, China.
Jing-Yao LiSchool of Medicine, Shanghai University, Shanghai, China.
Heng-Hui LiSchool of Medicine, Shanghai University, Shanghai, China.
Liang ChenSchool of Medicine, Shanghai University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gastric cancer is a leading cause of cancer-related mortality, with limited efficacy of immunotherapies due to intratumoral heterogeneity, an immunosuppressive microenvironment, and antigen-loss escape. The optimization of chimeric antigen receptor (CAR) T-cell therapy targeting PD-L1 and Claudin18.2 (CLDN18.2) is crucial for improving the antitumor response. Methods: We performed a stepwise optimization of CAR designs targeting PD-L1 and CLDN18.2, focusing on the costimulatory domains and intracellular signaling architecture. We engineered monospecific PD-L1 and CLDN18.2 CAR-T cells using CD28 or 4-1BB costimulatory domains and assessed their CAR expression, activation phenotype, subset composition, and cytotoxicity. We then engineered three bicistronic dual-target CARs with distinct CD3ζ configurations and evaluated their functionality through Results: The single-target CLDN18.2-CD28 CAR-T cells exhibited the strongest cytotoxicity Conclusions: The study identifies a bicistronic dual-target, double-CD3ζ CAR-T design that enhances T-cell functional fitness and antitumor efficacy in gastric cancer models. This approach offers a promising strategy for addressing antigen heterogeneity and improving the durability of CAR-T therapies in solid tumors.

Indexed as

B7-H1 AntigenCD3 ComplexClaudinsImmunotherapy, AdoptiveReceptors, Chimeric AntigenStomach NeoplasmsT-LymphocytesAnimalsCell Line, TumorFemaleHumansMiceXenograft Model Antitumor AssaysB7-H1 AntigenCD274 protein, humanCD3 antigen, zeta chainCD3 ComplexClaudinsCLDN18 protein, humanReceptors, Chimeric Antigenbicistronic CARCAR T-cell therapyCD3ζCLDN18.2dual-target CAR-Tgastric cancerimmunotherapyPD-L1

Identifiers

PMID42311665
PMCPMC13270025

What Socratic holds

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LicenceCC BY
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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 Socratic graph.