Evidence map›Paper›PMID 34943864›Full record

ReviewCells2021

Chimeric Antigen Receptors Expand the Repertoire of Antigenic Macromolecules for Cellular Immunity.

John T Keane, Avery D Posey

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 28% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Colorectal Cancer; Novel Approaches in Chimeric Antigen Receptors (CAR) -T cell.International journal of molecular and cellular medicine · 2025
    Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. 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 2 institutions in 1 country.

John T KeaneDepartment of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Avery D PoseyDepartment of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Philadelphia VA Medical Center · USTranslational Therapeutics (United States) · US

Funding

SPORE in Ovarian CancerP50CA228991 · NCI · JOHNS HOPKINS UNIVERSITY · PI Ronny I DRAPKIN, IE-MING SHIH · 2018 to 2026
$20.5M
6 · The paper itself

Abstract

T-cell therapies have made significant improvements in cancer treatment over the last decade. One cellular therapy utilizing T-cells involves the use of a chimeric MHC-independent antigen-recognition receptor, typically referred to as a chimeric antigen receptor (CAR). CAR molecules, while mostly limited to the recognition of antigens on the surface of tumor cells, can also be utilized to exploit the diverse repertoire of macromolecules targetable by antibodies, which are incorporated into the CAR design. Leaning into this expansion of target macromolecules will enhance the diversity of antigens T-cells can target and may improve the tumor-specificity of CAR T-cell therapy. This review explores the types of macromolecules targetable by T-cells through endogenous and synthetic antigen-specific receptors.

Indexed as

Immunity, CellularAnimalsAntigensHumansMacromolecular SubstancesPolysaccharidesReceptors, Chimeric AntigenRNAAntigensMacromolecular SubstancesPolysaccharidesReceptors, Chimeric AntigenRNAcancerCAR T-cellsimmunity

Identifiers

PMID34943864
PMCPMC8699116
OpenAlexW3214753975

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.