糖酵解
氧化磷酸化
生物
厌氧糖酵解
癌症研究
胶质母细胞瘤
转录组
细胞生物学
线粒体
新陈代谢
生物化学
基因
基因表达
作者
Luciano Garofano,Simona Migliozzi,Young Taek Oh,Fulvio D’Angelo,Ryan D. Najac,Aram Ko,Brulinda Frangaj,Francesca Pia Caruso,Kai Yu,Jinzhou Yuan,Wenting Zhao,Anna Luisa Di Stefano,Franck Bielle,Tao Jiang,Peter A. Sims,Mario L. Suvà,Fuchou Tang,Xiao-Dong Su,Michele Ceccarelli,Marc Sanson,Anna Lasorella,Antonio Iavarone
出处
期刊:Nature cancer
[Springer Nature]
日期:2021-01-11
卷期号:2 (2): 141-156
被引量:236
标识
DOI:10.1038/s43018-020-00159-4
摘要
The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter
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