Title |
Translational and HIF-1α-Dependent Metabolic Reprogramming Underpin Metabolic Plasticity and Responses to Kinase Inhibitors and Biguanides
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Published in |
Cell Metabolism (Science Direct), September 2018
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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
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 32% |
Canada | 3 | 16% |
France | 1 | 5% |
Japan | 1 | 5% |
Germany | 1 | 5% |
Spain | 1 | 5% |
Unknown | 6 | 32% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 11 | 58% |
Members of the public | 7 | 37% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
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% |