Spatially resolved metabolomics to discover tumor-associated metabolic alterations

Chenglong Sun(Chinese Academy of Medical Sciences & Peking Union Medical College), Tiegang Li(Chinese Academy of Medical Sciences & Peking Union Medical College), Xiaowei Song(Chinese Academy of Medical Sciences & Peking Union Medical College), Luojiao Huang(Chinese Academy of Medical Sciences & Peking Union Medical College), Qingce Zang(Chinese Academy of Medical Sciences & Peking Union Medical College), Jing Xu(Chinese Academy of Medical Sciences & Peking Union Medical College), Nan Bi(Chinese Academy of Medical Sciences & Peking Union Medical College), Guanggen Jiao(Linzhou Cancer Hospital), Yanzeng Hao(Linzhou Cancer Hospital), Yanhua Chen(Chinese Academy of Medical Sciences & Peking Union Medical College), Ruiping Zhang(Chinese Academy of Medical Sciences & Peking Union Medical College), Zhigang Luo(Chinese Academy of Medical Sciences & Peking Union Medical College), Xin Li(Chinese Academy of Medical Sciences & Peking Union Medical College), Lühua Wang(Chinese Academy of Medical Sciences & Peking Union Medical College), Zhonghua Wang(Minzu University of China), Yongmei Song(Chinese Academy of Medical Sciences & Peking Union Medical College), Jiuming He(Chinese Academy of Medical Sciences & Peking Union Medical College), Zeper Abliz(Minzu University of China)
Proceedings of the National Academy of Sciences
December 17, 2018
Cited by 368Open Access
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Abstract

Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.


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