Evidence map›Paper›PMID 27601996›Full record

ReviewFrontiers in pharmacology2016

miR-200c Regulation of Metastases in Ovarian Cancer: Potential Role in Epithelial and Mesenchymal Transition.

Siti A Sulaiman, Nurul-Syakima Ab Mutalib, Rahman Jamal

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
3.3field-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

41 citing papers in PubMed, 62 citations in OpenAlex.

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  17. βIII-Tubulin Gene Regulation in Health and Disease.Frontiers in cell and developmental biology · 2022
    Review
  18. Article
  19. Frontiers in genetics · 2022
    Article
  20. 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

3 authors at 1 institution in 1 country.

Siti A SulaimanUKM Medical Molecular Biology Institute, UKM Medical Centre, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia.
Nurul-Syakima Ab MutalibUKM Medical Molecular Biology Institute, UKM Medical Centre, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia.
Rahman JamalUKM Medical Molecular Biology Institute, UKM Medical Centre, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia.
University Kebangsaan Malaysia Medical Centre · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among the gynecological malignancies, ovarian cancer is the most fatal due to its high mortality rate. Most of the identified cases are epithelial ovarian cancer (EOC) with five distinct subtypes: high-grade serous carcinoma, low-grade serous carcinoma, mucinous carcinoma, endometrioid carcinoma, and clear-cell carcinoma. Lack of an early diagnostic approach, high incidence of tumor relapse and the heterogenous characteristics between each EOC subtypes contribute to the difficulties in developing precise intervention and therapy for the patients. MicroRNAs (miRNAs) are single-stranded RNAs that have been shown to function as tumor suppressors or oncomiRs. The miR-200 family, especially miR-200c, has been shown to be implicated in the metastasis and invasion of ovarian carcinoma due to its functional regulation of epithelial-to-mesenchymal transition (EMT). This mini review is aimed to summarize the recent findings of the miR-200c functional role as well as its validated targets in the metastasis cascade of ovarian cancer, with a focus on EMT regulation. The potential of this miRNA in early diagnosis and its dual expression status are also discussed.

Indexed as

EMTmetastasismiR-200covarian cancerregulation

Identifiers

PMID27601996
PMCPMC4993756
OpenAlexW2516517104

What OpenQuestion holds

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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.