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Translational and HIF-1α-Dependent Metabolic Reprogramming Underpin Metabolic Plasticity and Responses to Kinase Inhibitors and Biguanides

Overview of attention for article published in Cell Metabolism (Science Direct), September 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)

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Title
Translational and HIF-1α-Dependent Metabolic Reprogramming Underpin Metabolic Plasticity and Responses to Kinase Inhibitors and Biguanides
Published in
Cell Metabolism (Science Direct), September 2018
DOI 10.1016/j.cmet.2018.09.001
Pubmed ID
Authors

Laura Hulea, Simon-Pierre Gravel, Masahiro Morita, Marie Cargnello, Oro Uchenunu, Young Kyuen Im, Camille Lehuédé, Eric H., Matthew Leibovitch, Shannon McLaughlan, Marie-José Blouin, Maxime Parisotto, Vasilios Papavasiliou, Cynthia Lavoie, Ola Larsson, Michael Ohh, Tiago Ferreira, Celia Greenwood, Gaëlle Bridon, Daina Avizonis, Gerardo Ferbeyre, Peter Siegel, Russell G. Jones, William Muller, Josie Ursini-Siegel, Julie St-Pierre, Michael Pollak, Ivan Topisirovic

Abstract

There is increasing interest in therapeutically exploiting metabolic differences between normal and cancer cells. We show that kinase inhibitors (KIs) and biguanides synergistically and selectively target a variety of cancer cells. Synthesis of non-essential amino acids (NEAAs) aspartate, asparagine, and serine, as well as glutamine metabolism, are major determinants of the efficacy of KI/biguanide combinations. The mTORC1/4E-BP axis regulates aspartate, asparagine, and serine synthesis by modulating mRNA translation, while ablation of 4E-BP1/2 substantially decreases sensitivity of breast cancer and melanoma cells to KI/biguanide combinations. Efficacy of the KI/biguanide combinations is also determined by HIF-1α-dependent perturbations in glutamine metabolism, which were observed in VHL-deficient renal cancer cells. This suggests that cancer cells display metabolic plasticity by engaging non-redundant adaptive mechanisms, which allows them to survive therapeutic insults that target cancer metabolism.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 20%
Researcher 14 17%
Student > Master 9 11%
Student > Bachelor 7 9%
Student > Doctoral Student 4 5%
Other 9 11%
Unknown 23 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 29%
Agricultural and Biological Sciences 13 16%
Medicine and Dentistry 6 7%
Chemistry 3 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 8 10%
Unknown 26 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 03 September 2021.
All research outputs
#4,308,798
of 25,728,855 outputs
Outputs from Cell Metabolism (Science Direct)
#2,067
of 3,203 outputs
Outputs of similar age
#77,936
of 352,807 outputs
Outputs of similar age from Cell Metabolism (Science Direct)
#54
of 61 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,203 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 74.3. This one is in the 35th percentile – i.e., 35% 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 352,807 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.