Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Statistics, Rice University, Houston, TX 77005, USA.
Cell Rep. 2018 Apr 3;23(1):255-269.e4. doi: 10.1016/j.celrep.2018.03.077.
Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1-master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility.
代谢重编程为临床肿瘤学提供了关键信息。我们利用来自癌症基因组图谱的 9125 名患者样本的分子数据，根据七种主要代谢过程的 mRNA 表达模式，在 33 种癌症类型中鉴定出肿瘤亚型，并评估了它们的临床相关性。我们的代谢表达亚型与临床结果密切相关：碳水化合物、核苷酸和维生素/辅因子代谢上调的亚型与预后最差最一致相关，而脂质代谢上调的亚型则相反。代谢亚型与多种体细胞驱动因素相关，但对癌症特征途径的影响趋同，并受多种癌症类型中高度反复出现的主调控因子的调节。作为一个概念验证示例，我们证明了 SNAI1 或 RUNX1（碳水化合物代谢亚型的主调控因子）的敲低可调节代谢活性和药物敏感性。我们的研究提供了肿瘤内和肿瘤间代谢异质性的系统水平视图，并确定了途径交叉对话，提示具有相关的预后、治疗和预测效用。
