Evidence map›Paper›PMID 37429007›Full record

ArticleCancer immunology research2023

Synthesizing a Smarter CAR T Cell: Advanced Engineering of T-cell Immunotherapies.

Iowis Zhu, Dan I Piraner, Kole T Roybal

Abstract read
In one paragraph

Article in Cancer immunology research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Transforming bacterial pathogens into wonder tools in cancer immunotherapy.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  2. CAR-armored-cell therapy in solid tumor treatment.Journal of translational medicine · 2024
    Review
  3. Review
  4. Review
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

3 authors.

Iowis Zhu *Department of Microbiology and Immunology, University of California San Francisco, San Francisco, California.ORCID 0000-0001-7852-0987
Dan I Piraner *Department of Microbiology and Immunology, University of California San Francisco, San Francisco, California.ORCID 0000-0003-3857-9487
Kole T RoybalDepartment of Microbiology and Immunology, University of California San Francisco, San Francisco, California.ORCID 0000-0003-3030-7954

Funding

MOLECULAR AND CELLULAR IMMUNOLOGYT32AI007334 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CYSTER, JASON G · 1988 to 2023
$11.0M
Engineering the Next-generation of Custom Immune Cell TherapiesDP2CA239143 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROYBAL, KOLE T · 2018 to 2018
$2.4M
NCI NIH HHS DP2 CA239143NIAID NIH HHS T32 AI007334
6 · The paper itself

Abstract

The immune system includes an array of specialized cells that keep us healthy by responding to pathogenic cues. Investigations into the mechanisms behind immune cell behavior have led to the development of powerful immunotherapies, including chimeric-antigen receptor (CAR) T cells. Although CAR T cells have demonstrated efficacy in treating blood cancers, issues regarding their safety and potency have hindered the use of immunotherapies in a wider spectrum of diseases. Efforts to integrate developments in synthetic biology into immunotherapy have led to several advancements with the potential to expand the range of treatable diseases, fine-tune the desired immune response, and improve therapeutic cell potency. Here, we examine current synthetic biology advances that aim to improve on existing technologies and discuss the promise of the next generation of engineered immune cell therapies.

Indexed as

NeoplasmsT-LymphocytesHumansImmunotherapyImmunotherapy, AdoptiveReceptors, Antigen, T-CellReceptors, Antigen, T-Cell

Identifiers

PMID37429007
PMCPMC10527511

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.