Hadi Mahdieh, Marashi Sayed-Amir
Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran.
Mol Biosyst. 2014 Nov;10(11):3014-21. doi: 10.1039/c4mb00300d.
A promising strategy for finding new cancer drugs is to use metabolic network models to investigate the essential reactions or genes in cancer cells. In this study, we present a generic constraint-based model of cancer metabolism, which is able to successfully predict the metabolic phenotypes of cancer cells. This model is reconstructed by collecting the available data on tumor suppressor genes. Notably, we show that the activation of oncogene related reactions can be explained by the inactivation of tumor suppressor genes. We show that in a simulated growth medium similar to the body fluids, our model outperforms the previously proposed model of cancer metabolism in predicting expressed genes.
寻找新型抗癌药物的一个有前景的策略是使用代谢网络模型来研究癌细胞中的关键反应或基因。在本研究中，我们提出了一种基于约束的通用癌症代谢模型，该模型能够成功预测癌细胞的代谢表型。通过收集关于肿瘤抑制基因的现有数据来重建此模型。值得注意的是，我们表明癌基因相关反应的激活可以通过肿瘤抑制基因的失活来解释。我们还表明，在类似于体液的模拟生长培养基中，我们的模型在预测表达基因方面优于先前提出的癌症代谢模型。
