↓ Skip to main content

Roles of microRNA on cancer cell metabolism

Overview of attention for article published in Journal of Translational Medicine, November 2012
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
162 Dimensions

Readers on

mendeley
174 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Roles of microRNA on cancer cell metabolism
Published in
Journal of Translational Medicine, November 2012
DOI 10.1186/1479-5876-10-228
Pubmed ID
Authors

Bing Chen, Hongbin Li, Xiao Zeng, Pengbo Yang, Xinyu Liu, Xia Zhao, Shufang Liang

Abstract

Advanced studies of microRNAs (miRNAs) have revealed their manifold biological functions, including control of cell proliferation, cell cycle and cell death. However, it seems that their roles as key regulators of metabolism have drawn more and more attention in the recent years. Cancer cells display increased metabolic autonomy in comparison to non-transformed cells, taking up nutrients and metabolizing them in pathways that support growth and proliferation. MiRNAs regulate cell metabolic processes through complicated mechanisms, including directly targeting key enzymes or transporters of metabolic processes and regulating transcription factors, oncogenes / tumor suppressors as well as multiple oncogenic signaling pathways. MiRNAs like miR-375, miR-143, miR-14 and miR-29b participate in controlling cancer cell metabolism by regulating the expression of genes whose protein products either directly regulate metabolic machinery or indirectly modulate the expression of metabolic enzymes, serving as master regulators, which will hopefully lead to a new therapeutic strategy for malignant cancer. This review focuses on miRNA regulations of cancer cell metabolism,including glucose uptake, glycolysis, tricarboxylic acid cycle and insulin production, lipid metabolism and amino acid biogenesis, as well as several oncogenic signaling pathways. Furthermore, the challenges of miRNA-based strategies for cancer diagnosis, prognosis and therapeutics have been discussed.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 1%
Chile 2 1%
Netherlands 1 <1%
India 1 <1%
United Kingdom 1 <1%
Egypt 1 <1%
Denmark 1 <1%
United States 1 <1%
Unknown 164 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 25%
Researcher 32 18%
Student > Bachelor 19 11%
Student > Master 18 10%
Student > Doctoral Student 13 7%
Other 23 13%
Unknown 25 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 30%
Biochemistry, Genetics and Molecular Biology 43 25%
Medicine and Dentistry 28 16%
Engineering 7 4%
Immunology and Microbiology 6 3%
Other 7 4%
Unknown 31 18%
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 27 December 2012.
All research outputs
#18,325,190
of 22,691,736 outputs
Outputs from Journal of Translational Medicine
#2,936
of 3,965 outputs
Outputs of similar age
#214,055
of 275,842 outputs
Outputs of similar age from Journal of Translational Medicine
#60
of 91 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,965 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 16th percentile – i.e., 16% 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 275,842 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.