Evidence map›Paper›PMID 31083589›Full record

ReviewCancers2019

Countering TRAIL Resistance in Melanoma.

Jürgen Eberle

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.8field-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

26 citing papers in PubMed, 44 citations in OpenAlex.

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  6. Pharmaceuticals (Basel, Switzerland) · 2023
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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

1 author at 1 institution in 1 country.

Jürgen EberleDepartment of Dermatology, Venerology and Allergology, Skin Cancer Center Charité, Charité-Universitätsmedizin Berlin (University Medical Center Charité), 10117 Berlin, Germany. juergen.eberle@charite.de.
Charité - Universitätsmedizin Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Melanoma of the skin has become a prime example for demonstrating the success of targeted cancer therapy. Nevertheless, high mortality has remained, mainly related to tumor heterogeneity and inducible therapy resistance. But the development of new therapeutic strategies and combinations has raised hope of finally defeating this deadly disease. TNF-related apoptosis-inducing ligand (TRAIL) represents a promising antitumor strategy. The principal sensitivity of melanoma cells for TRAIL was demonstrated in previous studies; however, inducible resistance appeared as a major problem. To address this issue, combination strategies were tested, and survival pathway inhibitors were shown to sensitize melanoma cells for TRAIL-induced apoptosis. Finally, cell cycle inhibition was identified as a common principle of TRAIL sensitization in melanoma cells. Mitochondrial apoptosis pathways, pro- and antiapoptotic Bcl-2 proteins as well as the rheostat consisted of Smac (Second mitochondria-derived activator of caspase) and XIAP (X-linked inhibitor of apoptosis protein) appeared to be of particular importance. Furthermore, the role of reactive oxygen species (ROS) was recognized in this setting. Inducible TRAIL resistance in melanoma can be explained by (i) high levels of antiapoptotic Bcl-2 proteins, (ii) high levels of XIAP, and (iii) suppressed Bax activity. These hurdles have to be overcome to enable the use of TRAIL in melanoma therapy. Several strategies appear as particularly promising, including new TRAIL receptor agonists, Smac and BH3 mimetics, as well as selective kinase inhibitors.

Indexed as

BaxBcl-2 proteinskinasesmelanomaSmacTRAILXIAP

Identifiers

PMID31083589
PMCPMC6562618
OpenAlexW2944386970

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.