Shen Fangzhou, Li Jian, Zhu Ying, Wang Zhuo
1 School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, P. R. China.
J Bioinform Comput Biol. 2016 Oct;14(5):1644001. doi: 10.1142/S0219720016440017. Epub 2016 Aug 29.
Cancer cells have different metabolism in contrast to normal cells. The advancement in omics measurement technology enables the genome-wide characterization of altered cellular processes in cancers, but the metabolic flux landscape of cancer is still far from understood. In this study, we compared the well-reconstructed tissue-specific models of five cancers, including breast, liver, lung, renal, and urothelial cancer, and their corresponding normal cells. There are similar patterns in majority of significantly regulated pathways and enriched pathways in correlated reaction sets. But the differences among cancers are also explicit. The renal cancer demonstrates more dramatic difference with other cancer models, including the smallest number of reactions, flux distribution patterns, and specifically correlated pathways. We also validated the predicted essential genes and revealed the Warburg effect by in silico simulation in renal cancer, which are consistent with the measurements for renal cancer. In conclusion, the tissue-specific metabolic model is more suitable to investigate the cancer metabolism. The similarity and heterogenicity of metabolic reprogramming in different cancers are crucial for understanding the aberrant mechanisms of cancer proliferation, which is fundamental for identifying drug targets and biomarkers.
与正常细胞相比，癌细胞具有不同的代谢方式。组学测量技术的进步使得能够在全基因组范围内表征癌症中细胞过程的改变，但癌症的代谢通量格局仍远未被理解。在本研究中，我们比较了五种癌症（包括乳腺癌、肝癌、肺癌、肾癌和尿路上皮癌）及其相应正常细胞的组织特异性模型，这些模型重建良好。在大多数显著调节的途径和相关反应集中富集的途径中存在相似模式。但癌症之间的差异也很明显。肾癌与其他癌症模型表现出更显著的差异，包括反应数量最少、通量分布模式以及特定的相关途径。我们还通过肾癌的计算机模拟验证了预测的必需基因并揭示了瓦伯格效应，这与肾癌的测量结果一致。总之，组织特异性代谢模型更适合研究癌症代谢。不同癌症中代谢重编程的相似性和异质性对于理解癌症增殖的异常机制至关重要，这对于识别药物靶点和生物标志物至关重要。
