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Comprehensive analysis of the whole coding and non-coding RNA transcriptome expression profiles and construction of the circRNA–lncRNA co-regulated ceRNA network in laryngeal squamous cell carcinoma

Overview of attention for article published in Functional & Integrative Genomics, August 2018
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Title
Comprehensive analysis of the whole coding and non-coding RNA transcriptome expression profiles and construction of the circRNA–lncRNA co-regulated ceRNA network in laryngeal squamous cell carcinoma
Published in
Functional & Integrative Genomics, August 2018
DOI 10.1007/s10142-018-0631-y
Pubmed ID
Authors

Rui Zhao, Feng-Qing Li, Lin-Li Tian, De-Si Shang, Yan Guo, Jia-Rui Zhang, Ming Liu

Abstract

Recently, accumulating evidence has demonstrated that non-coding RNAs (ncRNAs) play a vital role in oncogenicity. Nevertheless, the regulatory mechanisms and functions remain poorly understood, especially for lncRNAs and circRNAs. In this study, we simultaneously detected, for the first time, the expression profiles of the whole transcriptome, including miRNA, circRNA and lncRNA + mRNA, in five pairs of laryngeal squamous cell carcinoma (LSCC) and matched non-carcinoma tissues by microarrays. Five miRNAs, four circRNAs, three lncRNAs and five mRNAs that were dysregulated were selected to confirm the verification of the microarray data by quantitative real-time PCR (qRT-PCR) in 20 pairs of LSCC samples. We constructed LSCC-related competing endogenous RNA (ceRNA) networks of lncRNAs and circRNAs (circRNA or lncRNA-miRNA-mRNA) respectively. Functional annotation revealed the lncRNA-mediated ceRNA network were enriched for genes involved in the tumor-associated pathways. Hsa_circ_0033988 with the highest degree in the circRNA-mediated ceRNA network was associated with fatty acid degradation, which was responsible for the depletion of fat in tumor-associated cachexia. Finally, to clarify the ncRNA co-regulation mechanism, we constructed a circRNA-lncRNA co-regulated network by integrating the above two networks and identified 9 modules for further study. A subnetwork of module 2 with the most dysregulated microRNAs was extracted to establish the ncRNA-involved TGF-β-associated pathway. In conclusion, our findings provide a high-throughput microarray data of the coding and non-coding RNAs and establish the foundation for further functional research on the ceRNA regulatory mechanism of non-coding RNAs in LSCC.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 4 14%
Student > Master 4 14%
Researcher 4 14%
Student > Bachelor 3 11%
Student > Ph. D. Student 2 7%
Other 3 11%
Unknown 8 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 32%
Medicine and Dentistry 8 29%
Agricultural and Biological Sciences 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Unknown 9 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 August 2018.
All research outputs
#17,987,988
of 23,100,534 outputs
Outputs from Functional & Integrative Genomics
#261
of 523 outputs
Outputs of similar age
#239,623
of 333,760 outputs
Outputs of similar age from Functional & Integrative Genomics
#5
of 11 outputs
Altmetric has tracked 23,100,534 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 523 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,760 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.