Evidence map›Paper›PMID 37928777›Full record

ReviewGEN biotechnology2023

Engineering T Cell Development for the Next Generation of Stem Cell-Derived Immunotherapies.

Yale S Michaels, Lauren J Durland, Peter W Zandstra

Open access · hybridAbstract readReview
In one paragraph

Review in GEN biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. [Biomaterials of different sizes for enhanced adoptive cell transfer therapy in solid tumors].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2025
    Review
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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 1 institution in 1 country.

Yale S MichaelsSchool of Biomedical Engineering, University of British Columbia, Vancouver, Canada; University of British Columbia, Vancouver, Canada.
Lauren J DurlandSchool of Biomedical Engineering, University of British Columbia, Vancouver, Canada; University of British Columbia, Vancouver, Canada.ORCID https://orcid.org/0000-0001-5740-8670
Peter W ZandstraSchool of Biomedical Engineering, University of British Columbia, Vancouver, Canada; University of British Columbia, Vancouver, Canada.
University of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Engineered T cells are at the leading edge of clinical cell therapy. T cell therapies have had a remarkable impact on patient care for a subset of hematological malignancies. This foundation has motivated the development of off-the-shelf engineered cell therapies for a broad range of devastating indications. Achieving this vision will require cost-effective manufacturing of precision cell products capable of addressing multiple process and clinical-design challenges. Pluripotent stem cell (PSC)-derived engineered T cells are emerging as a solution of choice. To unleash the full potential of PSC-derived T cell therapies, the field will require technologies capable of robustly orchestrating the complex series of time- and dose-dependent signaling events needed to recreate functional T cell development in the laboratory. In this article, we review the current state of allogenic T cell therapies, focusing on strategies to generate engineered lymphoid cells from PSCs. We highlight exciting recent progress in this field and outline timely opportunities for advancement with an emphasis on niche engineering and synthetic biology.

Identifiers

PMID37928777
PMCPMC10624212
OpenAlexW4366405937

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.