亚型
肝细胞癌
免疫系统
代谢物
肿瘤微环境
计算生物学
代谢组学
癌症研究
生物信息学
生物
免疫学
生物化学
计算机科学
程序设计语言
作者
Di Chen,Yiran Zhang,Wen Wang,Huan Chen,Ting Ling,Renyu Yang,Yawei Wang,Chao Duan,Yu Liu,Xin Guo,Lei Fang,Wuguang Liu,Xiumei Liu,Jing Liu,Wuxiyar Otkur,Huan Qi,Xiaolong Liu,Tian Xia,Hong‐xu Liu,Hulin Piao
标识
DOI:10.1002/advs.202100311
摘要
Metabolite-protein interactions (MPIs) play key roles in cancer metabolism. However, our current knowledge about MPIs in cancers remains limited due to the complexity of cancer cells. Herein, the authors construct an integrative MPI network and propose a MPI network based hepatocellular carcinoma (HCC) subtyping and mechanism exploration workflow. Based on the expressions of hub proteins on the MPI network, two prognosis-distinctive HCC subtypes are identified. Meanwhile, multiple interdependent features of the poor prognostic subtype are observed, including hypoxia, DNA hypermethylation of metabolic pathways, fatty acid accumulation, immune pathway up-regulation, and exhausted T-cell infiltration. Notably, the immune pathway up-regulation is probably induced by accumulated unsaturated fatty acids which are predicted to interact with multiple immune regulators like SRC and TGFB1. Moreover, based on tumor microenvironment compositions, the poor prognostic subtype is further divided into two sub-populations showing remarkable differences in metabolism. The subtyping shows a strong consistency across multiple HCC cohorts including early-stage HCC. Overall, the authors redefine robust HCC prognosis subtypes and identify potential MPIs linking metabolism to immune regulations, thus promoting understanding and clinical applications about HCC metabolism heterogeneity.
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