Evidence map›Paper›PMID 42099654›Full record

ReviewFrontiers in immunology2026

Adapter-based allogeneic CAR T cells to overcome antigen escape in solid tumors.

Phuc Q Pham, Quaovi H Sodji

Abstract readReview
In one paragraph

Review 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

2 authors.

Phuc Q PhamDepartment of Human Oncology, University of Wisconsin-Madison, Madison, WI, United States.
Quaovi H SodjiDepartment of Human Oncology, University of Wisconsin-Madison, Madison, WI, United States.

Funding

Targeted Radionuclide Therapy to Enhance the Efficacy of CAR T Cells Against NeuroblastomaK08CA285941 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Quaovi H Sodji · 2024 to 2026
$479k
NCI NIH HHS K08 CA285941
6 · The paper itself

Abstract

Monospecific Chimeric Antigen Receptor (CAR) T cell therapy against hematological malignancies targeting specific tumor-associated antigen (TAA) has gained clinical success in recent years. Despite their clinical outcomes, challenges including antigen escape, time and labor-intensive manufacturing process, and diminished efficacy especially against solid tumors persist. While allogeneic monospecific "off-the-shelf" CAR T cell therapy from healthy donors with knockout of alloreactive genes using gene editing tools such as CRISPR/Cas9 or TALEN has been evaluated to overcome manufacturing challenges, these allogeneic CAR T cells still face antigen escape. As such, adapter-based CAR T cells that can be redirected by small-molecule adapters to target multiple TAAs have emerged as an alternative therapeutic platform to overcome antigen escape. However, autologous adapter-based CAR T cell manufacturing remains time and labor intensive and scales poorly. Furthermore, chemotherapy-induced T cell dysfunction may compromise both manufacturing and efficacy of autologous CAR T cells. In this comprehensive review, we highlight advantages and limitations of the adapter-based CAR T platform and discuss how allogeneic manufacturing can be applied to adapter-based CAR T as a potential "off-the-shelf" therapeutic for treating multiple cancer types and overcome antigen escape.

Indexed as

Antigens, NeoplasmImmunotherapy, AdoptiveNeoplasmsReceptors, Chimeric AntigenT-LymphocytesTumor EscapeAnimalsHumansAntigens, NeoplasmReceptors, Chimeric Antigenallogeneic cell therapyantigen escapeCAR T cell therapyCRISPR/Cas9T cell receptortumor-associated antigen

Identifiers

PMID42099654
PMCPMC13144075

What OpenQuestion holds

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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.