Evidence map›Paper›PMID 28915650›Full record

ArticleOncotarget2017

MicroRNA-107-5p suppresses non-small cell lung cancer by directly targeting oncogene epidermal growth factor receptor.

Ping Wang, Xiaomin Liu, Yang Shao, Huimin Wang, Chen Liang, Baohui Han, Zhongliang Ma

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

22 citing papers in PubMed, 32 citations in OpenAlex.

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  13. Emerging insights into the biology of metastasis: A review article.Iranian journal of basic medical sciences · 2019
    Review
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  19. Review
  20. Effect of miR-483-5p on apoptosis of lung cancer cells through targeting of RBM5.International journal of clinical and experimental pathology · 2018
    Article
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

7 authors at 3 institutions in 1 country.

Ping Wang *Laboratory for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, Shanghai, China.
Xiaomin Liu *Laboratory for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, Shanghai, China.
Yang ShaoLaboratory for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, Shanghai, China.
Huimin WangLaboratory for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, Shanghai, China.
Chen LiangLaboratory for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, Shanghai, China.
Baohui HanDepartment of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Zhongliang MaLaboratory for Noncoding RNA & Cancer, School of Life Sciences, Shanghai University, Shanghai, China.
Shanghai University · CNFudan University Shanghai Cancer Center · CNShanghai Chest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are dysregulated in cancers, including human non-small cell lung cancer (NSCLC). The function of MicroRNA-107-5p (miR-107-5p) in NSCLC is not fully elucidated. Epidermal growth factor receptor (EGFR) is a cancer-driven gene in tumorigenesis. In this study, we found that miR-107-5p was significantly decreased in NSCLC tissues and NSCLC cell lines. Moreover, our results indicated that miR-107-5p could suppress cell proliferation, inhibit metastasis, impede cell cycle, and promote apoptosis via directly targeting EGFR. We also investigated roles of miR-107-5p

Indexed as

EGFRMicroRNA-107-5pNSCLCproliferationtumorigenesis

Identifiers

PMID28915650
PMCPMC5593621
OpenAlexW2624880388

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.