期刊
FEBS JOURNAL
卷 288, 期 19, 页码 5629-5649出版社
WILEY
DOI: 10.1111/febs.15858
关键词
branched‐ chain amino acids; cancer metabolism; cell growth; cell proliferation; KRAS
资金
- NIH [1R01DK075850-01, 1R01CA160458-01A1]
- David H. Koch Graduate Fellowship Fund
- Ludwig Fund for Cancer Research
- MIT Center for Precision Cancer Medicine
- Ludwig Center at MIT
- HHMI
- SU2C
The study found that the metabolic changes induced by the oncogenic gene KRAS expression in human mammary epithelial cells are similar to those corresponding to proliferation driven by epidermal growth factor (EGF), but in media without added EGF, KRAS-expressing cells showed lower glucose and glutamine consumption, which correlated with reduced sensitivity to specific drug treatments.
Many metabolic phenotypes in cancer cells are also characteristic of proliferating nontransformed mammalian cells, and attempts to distinguish between phenotypes resulting from oncogenic perturbation from those associated with increased proliferation are limited. Here, we examined the extent to which metabolic changes corresponding to oncogenic KRAS expression differed from those corresponding to epidermal growth factor (EGF)-driven proliferation in human mammary epithelial cells (HMECs). Removal of EGF from culture medium reduced growth rates and glucose/glutamine consumption in control HMECs despite limited changes in respiration and fatty acid synthesis, while the relative contribution of branched-chain amino acids to the TCA cycle and lipogenesis increased in the near-quiescent conditions. Most metabolic phenotypes measured in HMECs expressing mutant KRAS were similar to those observed in EGF-stimulated control HMECs that were growing at comparable rates. However, glucose and glutamine consumption as well as lactate and glutamate production were lower in KRAS-expressing cells cultured in media without added EGF, and these changes correlated with reduced sensitivity to GLUT1 inhibitor and phenformin treatment. Our results demonstrate the strong dependence of metabolic behavior on growth rate and provide a model to distinguish the metabolic influences of oncogenic mutations and nononcogenic growth.
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