Evidence map›Paper›PMID 36875550›Full record

ArticleOncoimmunology2023

Trial watch: Toll-like receptor ligands in cancer therapy.

Julie Le Naour, Guido Kroemer

Open access · goldAbstract read
In one paragraph

Article in Oncoimmunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

29 citing papers in PubMed, 41 citations in OpenAlex.

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  12. Prognostic significance ofTranslational cancer research · 2025
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  19. Recent trends in the delivery of RNA drugs: Beyond the liver, more than vaccine.European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V · 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

2 authors at 1 institution in 1 country.

Julie Le NaourCentre de Recherche Des Cordeliers, Equipe Labellisée Par la Ligue Contre le Cancer, Université de Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France.ORCID 0000-0002-3749-2171
Guido KroemerCentre de Recherche Des Cordeliers, Equipe Labellisée Par la Ligue Contre le Cancer, Université de Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France.
Inserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulating evidence indicates that Toll-like receptor (TLR) agonists proficiently (re)instore cancer immunosurveillance as immunological adjuvants. So far, three TLR agonists have been approved by regulatory agencies for use in oncological applications. Additionally, these immunotherapeutics have been extensively investigated over the past few years. Multiple clinical trials are currently evaluating the combination of TLR agonists with chemotherapy, radiotherapy, or different immunotherapies. Moreover, antibodies targeting tumor-enriched surface proteins that have been conjugated to TLR agonists are being developed to stimulate anticancer immune responses specifically within the tumor microenvironment. Solid preclinical and translational results support the favorable immune-activating effects of TLR agonists. Here, we summarize recent preclinical and clinical advances in the development of TLR agonists for anticancer immunotherapy.

Indexed as

ImmunotherapyNeoplasmsAdjuvants, ImmunologicLigandsMembrane ProteinsNeoplasm ProteinsToll-Like ReceptorsAdjuvants, ImmunologicLigandsMembrane ProteinsNeoplasm ProteinsToll-Like Receptorsampligenantibodyimmune checkpoint blockersImmunotherapyvidutolimod

Identifiers

PMID36875550
PMCPMC9980677
OpenAlexW4321219717

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.