Evidence map›Paper›PMID 28214928›Full record

ReviewCancer immunology, immunotherapy : CII2017

Dendritic cell rehab: new strategies to unleash therapeutic immunity in ovarian cancer.

Chang-Suk Chae, Eli Teran-Cabanillas, Juan R Cubillos-Ruiz

Open access · greenAbstract readReview
In one paragraph

Review in Cancer immunology, immunotherapy : CII, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 20% 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, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  12. IL-10 Signaling in the Tumor Microenvironment of Ovarian Cancer.Advances in experimental medicine and biology · 2021
    Review
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  14. Article
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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 2 countries.

Chang-Suk ChaeDepartment of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA.
Eli Teran-CabanillasDepartment of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA.
Juan R Cubillos-RuizDepartment of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA. jur2016@med.cornell.edu.ORCID http://orcid.org/0000-0002-4267-4893
Cornell University · USUniversidad Autónoma de Sinaloa · MX

Funding

NIMHD NIH HHS L60 MD001952
6 · The paper itself

Abstract

Immune-based therapies that induce remarkable and durable responses against melanoma and lung cancer have unfortunately demonstrated limited success in ovarian cancer patients. This is likely due to the exceptional immunoregulatory nature of ovarian tumors, which employ numerous strategies to effectively suppress anti-tumor immunity. Here, we summarize a decade of research indicating that ovarian cancers possess an exquisite capacity to subvert the activity of host dendritic cells (DCs) as a key mechanism to impede the development and maintenance of protective T cell-based immune responses. Identifying, understanding, and disabling the precise mechanisms promoting DC dysfunction in ovarian cancer are, therefore, fundamental requirements for devising the next generation of successful immunotherapies against this devastating malignancy.

Indexed as

ImmunotherapyAnimalsCancer VaccinesDendritic CellsFemaleHumansImmunityImmunomodulationMyeloid-Derived Suppressor CellsOvarian NeoplasmsTumor EscapeTumor MicroenvironmentCancer VaccinesDendritic cellsImmunosuppressionImmunotherapyOvarian cancerRegulatory myeloid suppressor cellsTumor microenvironment

Identifiers

PMID28214928
PMCPMC11028950
OpenAlexW2588318169

What OpenQuestion holds

Textmetadata
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.