三阴性乳腺癌
癌症研究
三重阴性
生物
计算生物学
乳腺癌
癌症
医学
生物信息学
亚型
内科学
计算机科学
程序设计语言
作者
Yue Gong,Peng Ji,Yun‐Song Yang,Shaowei Xie,Tian‐Jian Yu,Yi Xiao,Ming‐Liang Jin,Ding Ma,Lin‐Wei Guo,Yu-Chen Pei,Wen-Jun Chai,Da‐Qiang Li,Fan Bai,François Bertucci,Xin Hu,Yi‐Zhou Jiang,Zhi-Ming Shao
出处
期刊:Cell Metabolism
[Cell Press]
日期:2020-11-11
卷期号:33 (1): 51-64.e9
被引量:319
标识
DOI:10.1016/j.cmet.2020.10.012
摘要
Summary
Triple-negative breast cancer (TNBC) remains an unmet medical challenge. We investigated metabolic dysregulation in TNBCs by using our multi-omics database (n = 465, the largest to date). TNBC samples were classified into three heterogeneous metabolic-pathway-based subtypes (MPSs) with distinct metabolic features: MPS1, the lipogenic subtype with upregulated lipid metabolism; MPS2, the glycolytic subtype with upregulated carbohydrate and nucleotide metabolism; and MPS3, the mixed subtype with partial pathway dysregulation. These subtypes were validated by metabolomic profiling of 72 samples. These three subtypes had distinct prognoses, molecular subtype distributions, and genomic alterations. Moreover, MPS1 TNBCs were more sensitive to metabolic inhibitors targeting fatty acid synthesis, whereas MPS2 TNBCs showed higher sensitivity to inhibitors targeting glycolysis. Importantly, inhibition of lactate dehydrogenase could enhance tumor response to anti-PD-1 immunotherapy in MPS2 TNBCs. Collectively, our analysis demonstrated the metabolic heterogeneity of TNBCs and enabled the development of personalized therapies targeting unique tumor metabolic profiles.
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