Evidence map›Paper›PMID 32010197›Full record

ArticleFrontiers in genetics2019

Long Noncoding RNA RAET1K Enhances CCNE1 Expression and Cell Cycle Arrest of Lung Adenocarcinoma Cell by Sponging miRNA-135a-5p.

Chang Zheng, Xuelian Li, Yangwu Ren, Zhihua Yin, Baosen Zhou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

12 citing papers in PubMed, 18 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

5 authors at 1 institution in 1 country.

Chang ZhengDepartment of Clinical Epidemiology, First Affiliated Hospital of China Medical University, Shenyang, China.
Xuelian LiDepartment of Epidemiology, School of Public Health, China Medical University, Shenyang, China.
Yangwu RenDepartment of Epidemiology, School of Public Health, China Medical University, Shenyang, China.
Zhihua YinDepartment of Epidemiology, School of Public Health, China Medical University, Shenyang, China.
Baosen ZhouDepartment of Clinical Epidemiology, First Affiliated Hospital of China Medical University, Shenyang, China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular dysregulation is believed to participate in the onset and progression of lung adenocarcinoma (LUAD). This study aimed to identify and evaluate the potential key long noncoding RNAs (lncRNAs) involved in the significant dysfunctional process of LUAD. We found that lncRNA retinoic acid early transcript 1K (RAET1K) was upregulated in tumor tissues and were correlated with a poor prognosis of patients with LUAD; further, for the first time, we detected the biological roles of RAET1K. Weighted gene correlation network and gene set enrichment analysis revealed that high RAET1K expression is related to cell cycle dysfunction through upregulated cyclin E1 (CCNE1) by targeting miR-135. The dual-luciferase reporter gene assay was performed to clarify the binding relationship between RAET1K and miR-135a-5p in transgenic A549 and H1299 cells. Real-time PCR and Western blot analyses showed that RAET1K overexpression and miR-135a-5p inhibition exerted a strong synergistic effect on CCNE1 expression, and cell cycle flow cytometry analysis was used to confirm the arrest of A549 and H1299 cells at the G1/S phase. The lncRNA RAET1K/miR-135a-5p axis might participate in the regulation of LUAD progression by influencing CCNE1 expression and the accumulation of cells arrested at the G1/S phase boundary.

Indexed as

cell cyclegene regulatory networkslong noncoding RNAlung adenocarcinomaRAET1K

Identifiers

PMID32010197
PMCPMC6979007
OpenAlexW2999150320

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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.