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Oncology Reports
Article
License: CC BY
Data sources: UnpayWall
Oncology Reports
Article . 2019 . Peer-reviewed
Data sources: Crossref
Oncology Reports
Article . 2020
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Identification of a long non‑coding RNA‑mediated competitive endogenous RNA network in hepatocellular carcinoma

Authors: Hui, He; Di, Chen; Shimeng, Cui; Hailong, Piao; Haibo, Tang; Xun, Wang; Peng, Ye; +1 Authors

Identification of a long non‑coding RNA‑mediated competitive endogenous RNA network in hepatocellular carcinoma

Abstract

The present study was designed to identify the endogenous RNA regulatory networks involved in hepatocellular carcinoma (HCC) by bioinformatic analysis. Both miRNA interaction network‑based correlation analysis and expression‑based Spearman correlation coefficients were utilized to identify potential mRNA‑lncRNA interactions. Then, a competitive endogenous (ce)RNA network was constructed from these interactions, and network topology and Gene Ontology enrichment analyses were conducted to mine potential functions of ceRNAs. In HCC samples, a ceRNA network was constructed. It was composed of 35,657 edges connecting 113 lncRNAs and 6,136 mRNAs which were differentially expressed in HCC and normal liver tissues. Meanwhile, a number of significantly positively correlated mRNA and lncRNA pairs in this ceRNA network were found to be consistently positively correlated in another independent dataset. To be noted, further analyses on the potential roles of ceRNAs demonstrated than various lncRNAs such as LINC00657, TUG1 and SNHG1 may play key roles in HCC by regulating protein phosphorylation or cell cycle pathways or influencing miRNAs. From the perspective that lncRNAs can function as ceRNAs, this study revealed that the interaction between lncRNAs, miRNAs and mRNAs may provide new insight for the diagnosis and treatment in the tumorigenesis of hepatocellular carcinoma.

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Keywords

Carcinoma, Hepatocellular, Gene Expression Profiling, Liver Neoplasms, Computational Biology, High-Throughput Nucleotide Sequencing, Prognosis, Gene Expression Regulation, Neoplastic, MicroRNAs, Case-Control Studies, Biomarkers, Tumor, Humans, Gene Regulatory Networks, RNA, Long Noncoding, RNA, Messenger

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
hybrid