Evidence map›Paper›PMID 37468610›Full record

ReviewJournal of cancer research and clinical oncology2023

Chimeric antigen receptor T cells march into T cell malignancies.

Jie Tang, Xudong Zhao

Open access · greenAbstract readReview
In one paragraph

Review in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 27% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Jie TangDepartment of Targeting Therapy & Immunology and Laboratory of Animal Tumor Models, Cancer Center and National Clinical Research Center for Geriatrics and Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xudong ZhaoDepartment of Targeting Therapy & Immunology and Laboratory of Animal Tumor Models, Cancer Center and National Clinical Research Center for Geriatrics and Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China. zhaoxudong@wchscu.cn.
Sichuan University · CN

Funding

National Natural Science Foundation of China No. 82172701
6 · The paper itself

Abstract

T cell malignancies represent a diverse collection of leukemia/lymphoma conditions in humans arising from aberrant T cells. Such malignancies are often associated with poor clinical prognoses, cancer relapse, as well as progressive resistance to anti-cancer treatments. While chimeric antigen receptor (CAR) T cell immunotherapy has emerged as a revolutionary treatment strategy that is highly effective for treating B cell malignancies, its application as a treatment for T cell malignancies remains to be better explored. Furthermore, the effectiveness of CAR-T treatment in T cell malignancies is significantly influenced by the quality of contamination-free CAR-T cells during the manufacturing process, as well as by multiple characteristics of such malignancies, including the sharing of antigens across normal and malignant T cells, fratricide, and T cell aplasia. In this review, we provide a detailed account of the current developments in the clinical application of CAR-T therapy to treat T cell malignancies, offer strategies for addressing current challenges, and outline a roadmap toward its effective implementation as a broad treatment option for this condition.

Indexed as

CAR-TCAR-T product contaminationFratricideT cell aplasiaT cell malignancies

Identifiers

PMID37468610
PMCPMC11797312
OpenAlexW4384819520

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.