Evidence map›Paper›PMID 28123641›Full record

ArticleAmerican journal of translational research2017

Suppressing role of miR-520a-3p in breast cancer through CCND1 and CD44.

Jun Li, Juan Wei, Zhu Mei, Yongmei Yin, Yongfei Li, Mingjie Lu, Shidai Jin

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

30 citing papers in PubMed, 44 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Jun LiDepartment of Medical Oncology, The First Affiliated Hospital with Nanjing Medical University Nanjing, P. R. China.
Juan WeiDepartment of Medical Oncology, The Second Affiliated Hospital with Southeast University Nanjing, P. R. China.
Zhu MeiDepartment of Medical Oncology, Mingde Hospital of Nanjing Medical University Nanjing, P. R. China.
Yongmei YinDepartment of Medical Oncology, The First Affiliated Hospital with Nanjing Medical University Nanjing, P. R. China.
Yongfei LiDepartment of Medical Oncology, The First Affiliated Hospital with Nanjing Medical University Nanjing, P. R. China.
Mingjie LuDepartment of Medical Oncology, The First Affiliated Hospital with Nanjing Medical University Nanjing, P. R. China.
Shidai JinDepartment of Medical Oncology, The First Affiliated Hospital with Nanjing Medical University Nanjing, P. R. China.
Nanjing Medical University · CNSecond Affiliated Hospital of Nanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies show that many microRNAs (miRNAs) are found to play important roles in breast cancer, however, most of miRNAs are not investigated completely. In the present study, significant down-regulation of miR-520a-3p was found in the breast cancer tissues and cell lines. The restoration of miR-520a-3p expression in breast cancer cells could inhibit cell proliferation, migration and invasion. In addition, miR-520a-3p was able to induce breast cancer cell apoptosis. Luciferase assay was used to confirm that CCND1 and CD44 were the direct target genes of miR-520a-3p. The ectopic expression of miR-520a-3p repressed CCND1 and CD44 expression on post-transcriptional levels in breast cancer cells. This study suggests that miR-520a-3p may act as an optional method for breast cancer therapy.

Indexed as

breast cancerCCND1CD44metastasismiR-520a-3pproliferation

Identifiers

PMID28123641
PMCPMC5250711
OpenAlexW2585152980

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.