Evidence map›Paper›PMID 37753197›Full record

ReviewSynthetic and systems biotechnology2023

Intelligent tunable CAR-T cell therapy leads the new trend.

Jiayi Cheng, Mingyao Liu, Jiqin Zhang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Synthetic and systems biotechnology, 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. CAR-engineered neutrophils derived from induced pluripotent stem cells: a new frontier in cellular immunotherapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  2. 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.

Jiayi ChengShanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
Mingyao LiuShanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
Jiqin ZhangShanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adoptive transfer of T cells engineered with chimeric antigen receptor (CAR) has been proved to have robust anti-tumor effects against hematological malignancies. However, problems about safety and efficacy, such as cytokine release syndrome (CRS), T cell exhaustion and antigen escape are still raised when patients are treated with CAR-T cells. Moreover, CAR-T therapy has limited applications in treating solid tumors, owing to inefficient infiltration and poor functional persistence of CAR-T cells and diverse immunosuppression in tumor microenvironment. In order to overcome these limitations and broad its applications, multiple controllable CAR-T technologies were exploited. In this article, we review the designs of intelligent controlled CAR-T technologies and the innovations that they bring about in recent years.

Indexed as

Autologous universal systemChimeric antigen receptor TOn and off systemsSafety and efficacySynthetic notch systemTumor

Identifiers

PMID37753197
PMCPMC10518343

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.