Evidence map›Paper›PMID 34101736›Full record

ArticlePloS one2021

Comprehensive analysis of lncRNA biomarkers in kidney renal clear cell carcinoma by lncRNA-mediated ceRNA network.

Ke Gong, Ting Xie, Yong Luo, Hui Guo, Jinlan Chen, Zhiping Tan, Yifeng Yang, Li Xie

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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.

Ke GongDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.
Ting XieDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.
Yong LuoDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.
Hui GuoDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.
Jinlan ChenDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.
Zhiping TanThe Clinical Center for Gene Diagnosis and Therapy of The State Key Laboratory of Medical Genetics, The Second Xiangya Hospital of Central South University, Central South University, Changsha, Hunan, P.R. China.
Yifeng YangDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.
Li XieDepartment of Cardiovascular Surgery, The Second Xiangya Hospital of Central South University, Central South University, Changsha, P.R. China.ORCID 0000-0002-2634-6187

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionKidney renal clear cell carcinoma (KIRC) has a high incidence globally, and its pathogenesis remains unclear. Long non-coding RNA (lncRNA), as a molecular sponge, participates in the regulation of competitive endogenous RNA (ceRNA). We aimed to construct a ceRNA network and screened out possible lncRNAs to predict KIRC prognosis. MATERIAL AND

methodsAll KIRC data were downloaded from the TCGA database and screened to find the possible target lncRNA; a ceRNA network was designed. Next, GO functional enrichment and KEGG pathway of differentially expressed mRNA related to lncRNA were performed. We used Kaplan-Meier curve analysis to predict the survival of these RNAs. We used Cox regression analysis to construct a model to predict KIRC prognosis.

resultsIn the KIRC datasets, 1457 lncRNA, 54 miRNA and 2307 mRNA were screened out. The constructed ceRNA network contained 81 lncRNAs, nine miRNAs, and 17 mRNAs differentially expressed in KIRC. Survival analysis of all differentially expressed RNAs showed that 21 lncRNAs, four miRNAs, and two mRNAs were related to the overall survival rate. Cox regression analysis was performed again, and we found that eight lncRNAs were related to prognosis and used to construct predictive models. Three lnRNAs from independent samples were meaningful.

conclusionThe construction of ceRNA network was involved in the process and transfer of KIRC, and three lncRNAs may be potential targets for predicting KIRC prognosis.

Indexed as

AgedCarcinoma, Renal CellFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMaleMicroRNAsMiddle AgedPrognosisProportional Hazards ModelsRNA, Long NoncodingRNA, MessengerMicroRNAsRNA, Long NoncodingRNA, Messenger

Identifiers

PMID34101736
PMCPMC8186793

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