Evidence map›Paper›PMID 39748921›Full record

ReviewFrontiers in medicine2024

Gamma delta T cells in cancer therapy: from tumor recognition to novel treatments.

Xinyu Luo, Yufan Lv, Jinsai Yang, Rou Long, Jieya Qiu, Yuqi Deng, Guiyang Tang, Chaohui Zhang, Jiale Li, Jianhong Zuo

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

10 authors.

Xinyu Luo *The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Yufan Lv *The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Jinsai YangComputer Institute, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Rou LongTransformation Research Lab, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Jieya QiuTransformation Research Lab, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Yuqi DengTransformation Research Lab, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Guiyang TangTransformation Research Lab, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Chaohui ZhangThe Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Jiale LiComputer Institute, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Jianhong ZuoThe Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional immunotherapies mainly focus on αβ T cell-based strategies, which depend on MHC-mediated antigen recognition. However, this approach poses significant challenges in treating recurrent tumors, as immune escape mechanisms are widespread. γδ T cells, with their ability for MHC-independent antigen presentation, offer a promising alternative that could potentially overcome limitations observed in traditional immunotherapies. These cells play a role in tumor immune surveillance through a unique mechanism of antigen recognition and synergistic interactions with other immune effector cells. In this review, we will discuss the biological properties of the Vδ1 and Vδ2 T subsets of γδ T cells, their immunomodulatory role within the tumor microenvironment, and the most recent clinical advances in γδ T cell-based related immunotherapies, including cell engaging strategies and adoptive cell therapy.

Indexed as

adoptive cell therapyCAR-γδ T cellgamma delta T cellimmunotherapytumor microenvironment

Identifiers

PMID39748921
PMCPMC11693687

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.