Evidence map›Paper›PMID 32308421›Full record

ArticleOncoTargets and therapy2020

miR-34c Targets MET to Improve the Anti-Tumor Effect of Cisplatin on Ovarian Cancer.

Shiying Yang, Zhen Li, Rui Luo

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 37% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Review
  5. 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 3 institutions in 1 country.

Shiying YangDepartment of Gynecology and Obstetrics, Rizhao People's Hospital, Rizhao City 276800, Shandong Province, People's Republic of China.
Zhen LiReproductive Medicine Center, Qingdao Women and Children Hospital, Qingdao City 266011, Shandong Province, People's Republic of China.
Rui LuoDepartment of Gynecology, Linyi People's Hospital, Linyi City 276000, Shandong Province, People's Republic of China.
Linyi People's Hospital · CNPeople’s Hospital of Rizhao · CNQingdao Women and Children's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCisplatin is a commonly used drug for the treatment of various types of malignant cancers, including ovarian cancer. However, resistance to cisplatin is still a considerable obstacle to achieve a satisfactory therapeutic effect. The purpose of this study is to develop a strategy to sensitize ovarian cancer cells to cisplatin-induced cytotoxicity.

methodsmiR-34c levels in ovarian cancer tissues and cell lines were tested by qRT-PCR analysis. In vitro assays, the effect of miR-34c on cisplatin was evaluated by using MTT. Expression of MET and phosphorylation of PI3K and AKT were tested by Western blot assays. Conjugation with Bad and Bcl-xl was evaluated through immunoprecipitation. Flow cytometry analysis was performed to measure the apoptotic rate of ovarian cancer cells.

resultsDownregulation of miR-34c was observed in ovarian cancer tissues and cell lines. However, miR-34c overexpression was found to sensitize ovarian cancer cells to cisplatin treatment in vitro and in vivo. Mechanically, we found that miR-34c targeted the MET gene, thereby inhibiting the phosphorylation of PI3K and AKT to activate Bad. As a result, miR-34c reduced resistance of ovarian cancer cells to cisplatin-induced apoptosis.

conclusionmiR-34c/MET axis promotes cisplatin-induced cytotoxicity against ovarian cancer by targeting the MET/PI3K/AKT/Bad pathway.

Indexed as

BadcisplatinMETmiR-34covarian cancer

Identifiers

PMID32308421
PMCPMC7148417
OpenAlexW3014900382

What OpenQuestion holds

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Registered trials

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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.