Evidence map›Paper›PMID 26217583›Full record

ReviewFrontiers in oncology2015

Immune Infiltration and Prostate Cancer.

Amy Strasner, Michael Karin

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 121 papers.

0numbers the graph read from it
0cells of the map it votes in
121citing papers in PubMed
14.3field-weighted citation impact, top 1% 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

121 citing papers in PubMed, 188 citations in OpenAlex.

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61 more citing papers are in PubMed but not listed here.

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.

Amy StrasnerLaboratory of Gene Regulation and Signal Transduction, Department of Pharmacology, University of California San Diego School of Medicine , La Jolla, CA , USA ; Laboratory of Gene Regulation and Signal Transduction, Department of Pathology, University of California San Diego School of Medicine , La Jolla, CA , USA.
Michael KarinLaboratory of Gene Regulation and Signal Transduction, Department of Pharmacology, University of California San Diego School of Medicine , La Jolla, CA , USA ; Laboratory of Gene Regulation and Signal Transduction, Department of Pathology, University of California San Diego School of Medicine , La Jolla, CA , USA.
University of California, San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is becoming increasingly clear that inflammation influences prostate cancer (PCa) development and that immune cells are among the primary drivers of this effect. This information has launched numerous clinical trials testing immunotherapy drugs in PCa patients. The results of these studies are promising but have yet to generate a complete response. Importantly, the precise immune profile that determines clinical outcome remains unresolved. Individual immune cell types are divided into various functional subsets whose effects on tumor development may differ depending on their particular phenotype and functional status, which is often shaped by the tumor microenvironment. Thus, this review aims to examine the current knowledge regarding the role of inflammation and specific immune cell types in mediating PCa progression to assist in directing and optimizing immunotherapy targets, regimens, and responses and to uncover areas in which further research is needed. Finally, a summary of ongoing immunotherapy clinical trials in PCa is provided.

Indexed as

B cellsimmune cellsimmunotherapyinflammationprostate cancer

Identifiers

PMID26217583
PMCPMC4495337
OpenAlexW1572810235

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.