PhD Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, Texas, United States of America.
Center for Theoretical Biological Physics and Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.
PLoS Comput Biol. 2022 Feb 11;18(2):e1009841. doi: 10.1371/journal.pcbi.1009841. eCollection 2022 Feb.
While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive heterogeneity with respect to the presentation of the Warburg effect. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. Next, we report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer.
虽然有氧糖酵解，或沃伯格效应，长期以来一直被认为是肿瘤代谢的标志，但最近的研究揭示了一个更为复杂的图景。肿瘤细胞表现出广泛的代谢异质性，不仅表现在沃伯格效应的表现上，还表现在它们所依赖的营养物质和代谢途径上。此外，肿瘤细胞可以根据环境线索和治疗干预来在不同的代谢表型之间切换。然而，目前缺乏分析观察到的代谢异质性和可塑性的框架。我们使用一种包括肿瘤细胞中活跃的关键代谢途径的机制模型，表明细胞质中过量 ATP 对磷酸果糖激酶的抑制可以驱动快速增殖的肿瘤细胞对有氧糖酵解的偏好。因此，肿瘤细胞中 ATP 利用的不同速率可以驱动沃伯格效应表现的异质性。在此基础上，我们将肿瘤细胞的代谢表型与它们的迁移表型联系起来，并表明我们的模型预测与以前的实验结果一致。接下来，我们报告说，增殖细胞对不同氨酰源途径的依赖取决于葡萄糖和谷氨酰胺的相对可用性，并且可以进一步驱动代谢异质性。最后，我们以黑色素瘤细胞用 BRAF 抑制剂治疗为例，表明我们的模型可以用于预测癌症细胞对药物治疗的代谢和基因表达变化。与以前的肿瘤代谢建模方法相比，我们的框架做出的预测更加具有通用性和可解释性，它确定了控制肿瘤细胞代谢以及所报道的异质性和可塑性的关键原则。这些原则可能是针对癌症代谢脆弱性的关键。
