Evidence map›Paper›PMID 39061136›Full record

ArticleCancers2024

Optimizing Ex Vivo CAR-T Cell-Mediated Cytotoxicity Assay through Multimodality Imaging.

John G Foulke, Luping Chen, Hyeyoun Chang, Catherine E McManus, Fang Tian, Zhizhan Gu

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Cationic mRNA Lipid Nanoparticles for Ex Vivo NanoCAR-T Cell Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Article
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

6 authors.

John G FoulkeAmerican Type Culture Collection (ATCC), Manassas, VA 20110, USA.
Luping ChenAmerican Type Culture Collection (ATCC), Manassas, VA 20110, USA.
Hyeyoun ChangAmerican Type Culture Collection (ATCC), Manassas, VA 20110, USA.ORCID 0000-0003-4969-8932
Catherine E McManusAmerican Type Culture Collection (ATCC), Manassas, VA 20110, USA.ORCID 0000-0001-9943-712X
Fang TianAmerican Type Culture Collection (ATCC), Manassas, VA 20110, USA.
Zhizhan GuAmerican Type Culture Collection (ATCC), Manassas, VA 20110, USA.ORCID 0000-0001-9934-5209

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CAR-T cell-based therapies have demonstrated remarkable efficacy in treating malignant cancers, especially liquid tumors, and are increasingly being evaluated in clinical trials for solid tumors. With the FDA's initiative to advance alternative methods for drug discovery and development, full human ex vivo assays are increasingly essential for precision CAR-T development. However, prevailing ex vivo CAR-T cell-mediated cytotoxicity assays are limited by their use of radioactive materials, lack of real-time measurement, low throughput, and inability to automate, among others. To address these limitations, we optimized the assay using multimodality imaging methods, including bioluminescence, impedance tracking, phase contrast, and fluorescence, to track CAR-T cells co-cultured with CD19, CD20, and HER2 luciferase reporter cancer cells in real-time. Additionally, we varied the ratio of CAR-T cells to cancer cells to determine optimal cytotoxicity readouts. Our findings demonstrated that the CAR-T cell group effectively attacked cancer cells, and the optimized assay provided superior temporal and spatial precision measurements of ex vivo CAR-T killing of cancer cells, confirming the reliability, consistency, and high throughput of the optimized assay.

Indexed as

CAR-TCD19CD20cytotoxicity assayHER2multimodality imaging

Identifiers

PMID39061136
PMCPMC11274748

What OpenQuestion holds

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LicenceCC BY
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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.