Evidence map›Paper›PMID 31638248›Full record

ArticleOncology reports2019

Construction of a competing endogenous RNA network using differentially expressed lncRNAs, miRNAs and mRNAs in non‑small cell lung cancer.

Xi-Wen Wang, Qi-Qiang Guo, Yang Wei, Kai-Ming Ren, Fu-Shuang Zheng, Jun Tang, Hong-Yan Zhang, Jun-Gang Zhao

Open access · hybridAbstract read
In one paragraph

Article in Oncology reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

14 citing papers in PubMed, 29 citations in OpenAlex.

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  12. Prediction of Specific Subtypes and Common Markers of Non-Small Cell Lung Cancer Based on Competing Endogenous RNA Network.Medical science monitor : international medical journal of experimental and clinical research · 2020
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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.

Xi-Wen WangDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
Qi-Qiang GuoKey Laboratory of Medical Cell Biology, Ministry of Education, Institute of Translational Medicine, China Medical University, Liaoning Province Collaborative Innovation Center of Aging Related Disease Diagnosis and Treatment and Prevention, Shenyang, Liaoning 110122, P.R. China.
Yang WeiDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
Kai-Ming RenDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
Fu-Shuang ZhengDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
Jun TangDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
Hong-Yan ZhangDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
Jun-Gang ZhaoDepartment of The First Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The competing endogenous RNA (ceRNA) network is crucial for the development and progression of tumors, including non‑small cell lung cancer (NSCLC). However, what type of ceRNA network regulates NSCLC has not been clarified. The present study aimed to elucidate the long non‑coding RNA (lncRNA)/microRNA (miRNA)/mRNA ceRNA network in NSCLC, particularly for the significance of lncRNAs in NSCLC. NSCLC‑specific differentially expressed lncRNAs, miRNAs and mRNAs in the Cancer Genome Atlas (TCGA) were analyzed and their relationship was analyzed by a ceRNA network. Their potential functions of differentially expressed mRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the expression levels of four selected lncRNAs in TCGA were determined and their associated survival of patients was examined. In addition, the expression profiles of these four lncRNAs in 48 NSCLC specimens and cell lines, their cellular distribution and associated clinical parameters were examined. We successfully constructed a ceRNA network, including 113 lncRNAs, 12 miRNAs and 36 mRNAs differentially expressed between NSCLC and non‑tumor tissues. LINC00525, MED4‑AS1, STEAP2‑AS1 and SYNPR‑AS1 lncRNAs were selected and validated for their association with the survival of NSCLC patients. The expression of these lncRNAs was upregulated in 48 NSCLC tissues and was varying in NSCLC cells. While LINC00525 was mainly expressed in the cytoplasm, MED4‑AS1 was in both the nucleus and cytoplasm of A549 cells. In addition, the expression of LINC00525 was significantly associated with smoking history (P<0.05); MED4‑AS1 was significantly associated with women, poor differentiation and lymph node metastasis (P<0.05); STEAP2‑AS1 was significantly associated with women (P<0.01); and SYNPR‑AS1 was significantly associated with women and adenocarcinoma (P<0.05). These lncRNAs may be valuable biomarkers for prognosis of NSCLC and the ceRNA network may provide new insights in the pathogenesis of NSCLC.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksAdenocarcinoma of LungAgedAged, 80 and overBiomarkers, TumorCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellFemaleFollow-Up StudiesGene OntologyHumansLung NeoplasmsLymphatic MetastasisMaleMicroRNAsBiomarkers, TumorMicroRNAsRNA, Long NoncodingRNA, Messenger

Identifiers

PMID31638248
PMCPMC6859443
OpenAlexW2981213019

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.