Common biochemical and topological properties of metabolic genes recurrently dysregulated in tumors

Although tumors exhibit numerous metabolic alterations, it’s unclear if common objectives and constraints underlie diverse metabolic changes. Here we interpret cancer gene expression, copy number variation, and survival data using a computational model, MetOncoFit. MetOncoFit evaluates142 metabolic features that can impact tumor fitness, including enzyme catalytic activity, pathway association, network topological attributes, and reaction flux. Meta-analysis of tumor databases using MetOncoFit revealed that metabolic enzymes with high catalytic activity were frequently up-regulated in many tumors and associated with poor survival. MetOncoFit also identified metabolites that were hot-spots of dysregulation. MetOncoFit illuminates how enzyme activity and metabolic network architecture influences tumorigenesis.尽管肿瘤存在诸多代谢改变，但目前尚不清楚是否存在共同的目标与约束机制，支撑各类不同的代谢变化。本研究采用计算模型MetOncoFit对癌症基因表达、拷贝数变异及生存数据进行解析。该模型可评估142项可影响肿瘤适应性的代谢特征，涵盖酶催化活性、通路关联、网络拓扑属性以及反应通量。借助MetOncoFit对肿瘤数据库开展荟萃分析后发现，催化活性较高的代谢酶在多种肿瘤中常呈上调表达，且与不良预后密切相关。此外，MetOncoFit还鉴定出了代谢失调的热点代谢物。该模型阐明了酶活性与代谢网络架构如何影响肿瘤发生发展过程。