Evidence map›Paper›PMID 28536623›Full record

ArticleCellular & molecular biology letters2016

A computationally constructed ceRNA interaction network based on a comparison of the SHEE and SHEEC cell lines.

Jiachun Sun, Junqiang Yan, Xiaozhi Yuan, Ruina Yang, Tanyou Dan, Xinshuai Wang, Guoqiang Kong, Shegan Gao

Open access · goldAbstract read
In one paragraph

Article in Cellular & molecular biology letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.5field-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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

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  15. Editorial focus: entering into the non-coding RNA era.Cellular & molecular biology letters · 2018
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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

8 authors at 1 institution in 1 country.

Jiachun Sun *Department of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Junqiang Yan *Department of Neurology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Xiaozhi YuanDepartment of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Ruina YangDepartment of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Tanyou DanDepartment of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Xinshuai WangDepartment of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Guoqiang KongDepartment of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
Shegan GaoDepartment of Oncology, Cancer Institute, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, People's Republic of China.
First Affiliated Hospital of Henan University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) play critical and complicated roles in the regulation of various biological processes, including chromatin modification, transcription and post-transcriptional processing. Interestingly, some lncRNAs serve as miRNA "sponges" that inhibit interaction with miRNA targets in post-transcriptional regulation. We constructed a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression based on high-throughput RNA sequencing and microarray data to enable a comparison of the SHEE and SHEEC cell lines. Using Targetscan and miRanda bioinformatics algorithms and miRTarbase microRNA-target interactions database, we established that 51 miRNAs sharing 13,623 MREs with 2260 genes and 82 lncRNAs were involved in this ceRNA network. Through a biological function analysis, the ceRNA network appeared to be primarily involved in cell proliferation, apoptosis, the cell cycle, invasion and metastasis. Functional pathway analyses demonstrated that the ceRNA network potentially modulated multiple signaling pathways, such as the MAPK, Ras, HIF-1, Rap1, and PI3K/Akt signaling pathways. These results might provide new clues to better understand the regulation of the ceRNA network in cancer.

Indexed as

Gene Regulatory NetworksCarcinoma, Squamous CellCell LineComputational BiologyEpithelial CellsEsophageal NeoplasmsEsophagusGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansMicroRNAsOligonucleotide Array Sequence AnalysisRNA, Long NoncodingSequence Analysis, RNAMicroRNAsRNA, Long NoncodingceRNAlncRNAmiRNASHEESHEEC

Identifiers

PMID28536623
PMCPMC5415789
OpenAlexW2528381588

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.