Evidence map›Paper›PMID 40289115›Full record

ReviewMolecular cancer2025

Strategies to overcome tumour relapse caused by antigen escape after CAR T therapy.

Yufei Lu, Fu Zhao

Abstract readReview
In one paragraph

Review in Molecular cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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  15. Therapeutic application of IL-12 for cancer therapy.Translational cancer research · 2026
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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

2 authors.

Yufei LuFuxing Hospital, Capital Medical University, Beijing, China.
Fu ZhaoDepartment of Pediatric Neurosurgery, Beijing Key Laboratory of Drug Innovation for Neuro-Oncology, Beijing Neurosurgical Institute, Capital Medical University, 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China. zhaofu@ccmu.edu.cn.

Funding

Beijing Natural Science Foundation 7252005
6 · The paper itself

Abstract

Chimeric antigen receptor (CAR) T cell therapy has revolutionized the treatment of B cell and plasma cell malignancies, and numerous promising targets against solid tumours are being explored. Despite their initial therapeutic success in hematological cancers, relapse occurs in a significant fraction of patients, highlighting the need for further innovations in advancing CAR T cell therapy. Tumour antigen heterogeneity and acquired tumour resistance leading to antigen escape (antigen loss/downregulation) have emerged as a crucial factor contributing to immune escape and CAR T cell resistance, particularly in the case of solid tumours with only limited success achieved to date. In this review, we discuss mechanisms of tumour relapse in CAR T cell therapy and the promising strategies that are under development to overcome multiple resistance mechanisms, thereby reducing outgrowth of antigen escape variants. Specifically, we emphasize the importance of designing clinical translational strategies to enhance CAR T cell crosstalk with host immune cells, eliciting endogenous antitumour immune responses through antigen/epitope spreading, which offers a genuine solution to the limitations of targeting tumour antigen heterogeneity in solid tumours with monospecific T cell therapies.

Indexed as

Antigens, NeoplasmImmunotherapy, AdoptiveNeoplasm Recurrence, LocalNeoplasmsReceptors, Chimeric AntigenTumor EscapeAnimalsHumansReceptors, Antigen, T-CellT-LymphocytesAntigens, NeoplasmReceptors, Antigen, T-CellReceptors, Chimeric AntigenAntigen/epitope spreadingAntigen loss/downregulationChimeric antigen receptorTumour heterogeneity

Identifiers

PMID40289115
PMCPMC12036236

What OpenQuestion holds

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Registered trials

None linked

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.