Evidence map›Paper›PMID 32742489›Full record

ReviewJournal of Cancer2020

A brief review concerning Chimeric Antigen Receptors T cell therapy.

Ling-Lin Li, Hong-Ling Yuan, Yu-Qiong Yang, Lin Wang, Ren-Chao Zou

Abstract readReview
In one paragraph

Review in Journal of Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

5 authors.

Ling-Lin LiDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650101, Yunnan, China.
Hong-Ling YuanDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan, China.
Yu-Qiong YangDepartment of Nephrology, The Third People's Hospital of Yunnan Province, Kunming, Yunnan, P.R. China.
Lin WangDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650101, Yunnan, China.
Ren-Chao ZouDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650101, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The understanding concerning the function of immune system in cancer has achieved considerable advance with time passes by. Manipulating genetically engineered immune cells were investigated as a novel strategy for treating cancer. Chimeric antigen receptors (CARs) are recombinant protein molecules by merging the exquisite targeting the potent cytotoxicity of T cells and specificity of monoclonal antibodies and, which could trigger serial cascades of signal transduction and thereby activate T cells to directly destroy the tumor cells. Manufacturing CAR-modified T lymphocytes were successfully implemented in treating cancer derived from they could specifically retarget tumor-associated antigens, causing effective elimination of tumor cells, which spurred the optimization and development of new CAR-T cell technology. The advancement of synthetic biology methodologies of cell therapy in CAR-T would ultimately provide us with a much safer, reliable and efficient modality to against cancer. This review primarily described the emergence, development and application of cell therapy in CAR-T, then discuss the side effects and the potential factors of tumor reccurrence caused by CAR-T cell therapy, in addition to the corresponding countermeasure concerning complications.

Indexed as

CancerChimeric antigen receptorsComplicationRelapse

Identifiers

PMID32742489
PMCPMC7391193

What OpenQuestion holds

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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.