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Aging

Matcha green tea (MGT) inhibits the propagation of cancer stem cells (CSCs), by targeting mitochondrial metabolism, glycolysis and multiple cell signalling pathways

Overview of attention for article published in Aging, August 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
15 news outlets
blogs
2 blogs
twitter
14 X users
facebook
5 Facebook pages
video
2 YouTube creators

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
85 Mendeley
Title
Matcha green tea (MGT) inhibits the propagation of cancer stem cells (CSCs), by targeting mitochondrial metabolism, glycolysis and multiple cell signalling pathways
Published in
Aging, August 2018
DOI 10.18632/aging.101483
Pubmed ID
Authors

Gloria Bonuccelli, Federica Sotgia, Michael P. Lisanti

Abstract

Matcha green tea (MGT) is a natural product that is currently used as a dietary supplement and may have significant anti-cancer properties. However, the molecular mechanism(s) underpinning its potential health benefits remain largely unknown. Here, we used MCF7 cells (an ER(+) human breast cancer cell line) as a model system, to systematically dissect the effects of MGT at the cellular level, via i) metabolic phenotyping and ii) unbiased proteomics analysis. Our results indicate that MGT is indeed sufficient to inhibit the propagation of breast cancer stem cells (CSCs), with an IC-50 of ~0.2 mg/ml, in tissue culture. Interestingly, metabolic phenotyping revealed that treatment with MGT is sufficient to suppress both oxidative mitochondrial metabolism (OXPHOS) and glycolytic flux, shifting cancer cells towards a more quiescent metabolic state. Unbiased label-free proteomics analysis identified the specific mitochondrial proteins and glycolytic enzymes that were down-regulated by MGT treatment. Moreover, to discover the underlying signalling pathways involved in this metabolic shift, we subjected our proteomics data sets to bio-informatics interrogation via Ingenuity Pathway Analysis (IPA) software. Our results indicate that MGT strongly affected mTOR signalling, specifically down-regulating many components of the 40S ribosome. This raises the intriguing possibility that MGT can be used as inhibitor of mTOR, instead of chemical compounds, such as rapamycin. In addition, other key pathways were affected, including the anti-oxidant response, cell cycle regulation, as well as interleukin signalling. Our results are consistent with the idea that MGT may have significant therapeutic potential, by mediating the metabolic reprogramming of cancer cells.

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X Demographics

The data shown below were collected from the profiles of 14 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 85 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 18%
Student > Ph. D. Student 14 16%
Researcher 9 11%
Student > Master 7 8%
Other 6 7%
Other 6 7%
Unknown 28 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 16%
Medicine and Dentistry 8 9%
Nursing and Health Professions 7 8%
Agricultural and Biological Sciences 6 7%
Unspecified 3 4%
Other 12 14%
Unknown 35 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 134. 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 12 March 2024.
All research outputs
#313,964
of 25,698,912 outputs
Outputs from Aging
#62
of 4,166 outputs
Outputs of similar age
#6,569
of 343,930 outputs
Outputs of similar age from Aging
#3
of 60 outputs
Altmetric has tracked 25,698,912 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,166 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has done particularly well, scoring higher than 98% 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 343,930 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.