Evidence map›Paper›PMID 31071196›Full record

ArticlePloS one2019

Derivation of mimetic γδ T cells endowed with cancer recognition receptors from reprogrammed γδ T cell.

Jieming Zeng, Shin Yi Tang, Shu Wang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

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  4. Practical immunomodulatory landscape of glioblastoma multiforme (GBM) therapy.Journal of the Egyptian National Cancer Institute · 2024
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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

3 authors at 2 institutions in 1 country.

Jieming ZengInstitute of Bioengineering and Nanotechnology, Singapore.ORCID 0000-0003-3504-8226
Shin Yi TangInstitute of Bioengineering and Nanotechnology, Singapore.
Shu WangInstitute of Bioengineering and Nanotechnology, Singapore.
National University of Singapore · SGInstitute of Bioengineering and Nanotechnology · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using induced pluripotent stem cells (iPSCs) to derive chimeric antigen receptor-modified T (CAR-T) cells has great industrial potential. A previous study used αβ T cell-derived CAR-modified iPSCs to produce CAR-T cells. However, these αβ T cells are restricted to autologous use and only recognize single cancer antigen. To make CAR-T alternative for allogeneic use, we reprogrammed γδ T cell into iPSCs (γδ T-iPSCs) to circumvent the risk of graft-versus-host disease. To target multiple cancer-associated antigens, we used an "NK cell-promoting" protocol to differentiate γδ T-iPSCs and to induce expression of natural killer receptors (NKRs). Through such two-step strategy, mimetic γδ T cells endowed with an array of NKRs and thus designated as "γδ natural killer T (γδ NKT) cells" were derived. With no/low-level expression of inhibitory killer cell immunoglobulin-like receptors (KIRs) and immune checkpoint receptors, γδ NKT cells may provide a potent "off-the-shelf" cytotoxic cell source to recognize multiple ubiquitous antigens in a broad spectrum of cancers.

Indexed as

Antigens, NeoplasmHCT116 CellsHep G2 CellsHumansInduced Pluripotent Stem CellsK562 CellsMCF-7 CellsNatural Killer T-CellsNeoplasmsReceptors, Antigen, T-Cell, alpha-betaReceptors, Antigen, T-Cell, gamma-deltaReceptors, Chimeric AntigenTHP-1 CellsAntigens, NeoplasmReceptors, Antigen, T-Cell, alpha-betaReceptors, Antigen, T-Cell, gamma-deltaReceptors, Chimeric Antigen

Identifiers

PMID31071196
PMCPMC6508724
OpenAlexW2944128808

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.