Metabolic feature profiling and metabolic vulnerability in acute lymphoblastic leukemia
Xiaojie Liang, Zihong Cai, Bingqing Tang, Zicong Huang, Baiwei Luo, Bingyu Lin, Yunong Yang, Zhihao Jin, Xiaoqing Li, Xiuli Xu, Yeling Deng, Chaoran Lin, Liang Wang, Hongsheng ZhouAbstract
Metabolic reprogramming is a hallmark of cancer and serves as a potential therapeutic target, whereas the metabolic feature of acute lymphoblastic leukemia (ALL) was marginally addressed. Based on RNA‐sequencing data in an in‐house and external cohort, we aimed to dissect metabolic feature subtypes (MFS) of ALL, which were further cross‐validated through a transcriptomics‐metabolomics‐functional systematic framework. ALL were stratified into three subtypes, of which MFS1 was polysaccharide‐metabolic, MFS2 was cold‐metabolic, and MFS3 was glycolysis hot‐metabolic subtype. Notably, metabolic stratification was significantly associated with patient survival, as 70%–81% overall‐survival in MFS1, compared with 25%–56% in MFS2 and MFS3 (MFS1 vs. MFS2, MFS3, p < 0.001). Additional analysis revealed the association between MFSs and clinical features, molecular mutation, and copy number aberration. Metabolic heterogeneity indicated susceptibility to antimetabolite drugs for ALL in vitro. MFS1 was sensitive to antimetabolite drugs for ALL, such as L‐asparaginase and 6‐mercaptopurine, while MFS2 and MFS3 were resistant. Furthermore, a glycolysis inhibitor reversed the resistance to L‐asparaginase and promoted survival in MFS3‐patient‐derived xenografts. We developed a novel metabolic‐stratification, which dissects metabolic profiling, clinical outcome, and therapeutic vulnerability for precision metabolic intervention in ALL.