Evidence map›Paper›PMID 29956728›Full record

ArticleMolecular medicine reports2018

Detection of dysregulated competing endogenous RNA modules associated with clear cell kidney carcinoma.

Hong Wang, Dahua Xu, Huiying Huang, Ying Cui, Chunhua Li, Chunrui Zhang, Shengnan Guo, Lining Zhang, Xiaomu Xu, Jiankai Xu and 3 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

8 citing papers in PubMed, 15 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

13 authors at 2 institutions in 1 country.

Hong WangNetwork Information Center, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Dahua XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Huiying HuangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Ying CuiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Chunhua LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Chunrui ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Shengnan GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Lining ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Xiaomu XuInstitute of Petrochemistry Heilongjiang Academy of Sciences, Harbin, Heilongjiang 150040, P.R. China.
Jiankai XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Jianping LuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Liqiang WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Kongning LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China.
Harbin Medical University · CNHeilongjiang Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent evidence has suggested that competitive endogenous RNAs (ceRNAs) are important regulatory molecules in clear cell kidney carcinoma (KIRC) and their dysregulation may contribute to cancer pathogenesis. However, the critical roles of dysregulated ceRNAs in KIRC remain unknown. In the present study, a KIRC dysregulated ceRNA‑ceRNA network (KDCCNet) was constructed based on the 'ceRNA hypothesis' by integrating microRNA regulation and expression profiles in cancerous and normal tissues. Two dysregulated patterns of ceRNAs interaction (gain and loss) exist in KDCCNet. The two modules, which are 95% loss interactions and 97% gain interactions, were demonstrated to be able to distinguish normal samples from cancer samples. Two long non‑coding (lnc)‑RNAs (glucuronidase β pseudogene 11 and LIFR antisense RNA 1) demonstrated significant associations with KIRC prognosis. The present study of the KDCCNet revealed a novel biological mechanism for KIRC and provides novel lncRNAs as candidate prognostic biomarkers.

Indexed as

Carcinoma, Renal CellGene Expression Regulation, NeoplasticKidney NeoplasmsRNA, Long NoncodingRNA, NeoplasmHumansRNA, Long NoncodingRNA, Neoplasm

Identifiers

PMID29956728
PMCPMC6072225
OpenAlexW2808829302

What Socratic 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 Socratic graph.