Evidence map›Paper›PMID 25992367›Full record

ReviewAnnals of translational medicine2015

MicroRNA and MET in lung cancer.

Matteo Brighenti

Open access · greenAbstract readReview
In one paragraph

Review in Annals of translational medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

19 citing papers in PubMed, 31 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Intercalating the Role of MicroRNAs in Cancer: As Enemy or Protector.Asian Pacific journal of cancer prevention : APJCP · 2020
    Review
  10. Article
  11. Review
  12. Article
  13. Exploring conserved mRNA-miRNA interactions in colon and lung cancers.Gastroenterology and hepatology from bed to bench · 2017
    Article
  14. Article
  15. Overexpression of MicroRNA-221 is associated with poor prognosis in non-small cell lung cancer patients.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    Article
  16. Article
  17. Article
  18. Article
  19. 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

1 author at 1 institution in 1 country.

Matteo BrighentiOncology Unit, Istituti Ospitalieri di Cremona, Cremona, Italy.
Istituti Ospitalieri di Cremona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are a class of small non-protein coding RNAs that modulate important cellular functions via their post-transcriptional regulation of messenger RNAs (mRNAs). Recent evidences from multiple tumor types and model systems implicate miRNA dysregulation as a common mechanism of tumorigenesis, cancer progression and resistance to therapy. Several miRNAs are dysregulated in cancers and a single miRNA can have multiple targets involved in different oncogenic pathways. MET, the tyrosine kinase receptor for hepatocyte growth factor (HGF), has a central role in lung cancer development and in acquired resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors; it has been predicted and shown to be the target gene of multiple miRNAs, which play a crucial role in controlling its activity in a stimulatory or inhibitory sense. In this review we will focus on the most important and recent studies about the role of miRNAs in the control of MET expression, reporting also the progress made using miRNAs for therapy of lung cancer.

Indexed as

lung cancerMETmicroRNA

Identifiers

PMID25992367
PMCPMC4402600
OpenAlexW245884118

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.