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Integrated analysis of miRNA, gene, and pathway regulatory networks in hepatic cancer stem cells

Overview of attention for article published in Journal of Translational Medicine, August 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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7 X users

Citations

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21 Dimensions

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39 Mendeley
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Title
Integrated analysis of miRNA, gene, and pathway regulatory networks in hepatic cancer stem cells
Published in
Journal of Translational Medicine, August 2015
DOI 10.1186/s12967-015-0609-7
Pubmed ID
Authors

Min Ding, Jiang Li, Yong Yu, Hui Liu, Zi Yan, Jinghan Wang, Qijun Qian

Abstract

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. HCC has a poor prognosis associated with tumor recurrence and drug resistance, which has been attributed to the existence of hepatic cancer stem cells (HCSCs). However, the characteristics and regulatory mechanisms of HCSCs remain unclear. We therefore established a novel system to enrich HCSCs and we demonstrate that these HCSCs exhibit cancer stem cell properties. We used miRNA and mRNA high-throughput sequencing data sets to determine molecular signatures and regulatory mechanisms in HCSCs. Paired miRNA and gene deep sequencing data in HCSCs versus HCC cells were used to identify candidate biomarkers of HCSCs. Using network analysis, we studied the relationship between miRNA and gene biomarkers, and KEGG pathway enrichment analysis was performed to study the function of candidate biomarkers. We identified 9 up- and 9 down-regulated miRNAs and 115 up- and 402 down-regulated genes in HCSCs compared with HCC cells. A miRNA-gene network was constructed using 651 miRNA-gene interactions (between 7 up-regulated miRNAs and 274 down-regulated genes), and 103 miRNA-gene interactions (between 9 down-regulated miRNAs and 62 up-regulated genes). Pathway enrichment analysis identified five tumor invasion- and metastasis-related pathways and MAPK signaling associated with HCSCs. We further discovered two novel pathways that likely play a role in the regulation of HCSCs. We identified a molecular expression signature and pathway regulatory mechanisms in HCSCs with potential diagnostic and therapeutic value.

X Demographics

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The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 15%
Student > Master 5 13%
Student > Doctoral Student 4 10%
Professor 4 10%
Researcher 4 10%
Other 8 21%
Unknown 8 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 21%
Medicine and Dentistry 6 15%
Biochemistry, Genetics and Molecular Biology 5 13%
Engineering 3 8%
Computer Science 2 5%
Other 6 15%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 March 2016.
All research outputs
#12,738,978
of 22,821,814 outputs
Outputs from Journal of Translational Medicine
#1,428
of 3,993 outputs
Outputs of similar age
#113,960
of 264,425 outputs
Outputs of similar age from Journal of Translational Medicine
#41
of 112 outputs
Altmetric has tracked 22,821,814 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,993 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 63% of its peers.
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 264,425 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.