1. The landscape of cancer cell line metabolism
- Author
-
David E. Root, Clary B. Clish, Mahmoud Ghandi, William R. Sellers, Verena Apfel, Kerry A. Pierce, William C. Hahn, Shuba Gopal, Raymond Pagliarini, Dojna Shkoza, Shaoyang Ning, Francisca Vazquez, Aviad Tsherniak, Levi A. Garraway, Stuart L. Schreiber, Amanda Souza, Amy Deik, Yilong Zou, Marios Giannakis, Gregory V. Kryukov, Julie Ann, Paula Keskula, Giorgio G. Galli, Haoxin Li, Desiree Hernandez, and Jordi Barretina
- Subjects
0301 basic medicine ,Metabolite ,Druggability ,Mice, Nude ,Computational biology ,Biology ,Article ,General Biochemistry, Genetics and Molecular Biology ,Mice ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Metabolomics ,Stomach Neoplasms ,Cell Line, Tumor ,Neoplasms ,Metabolome ,medicine ,Animals ,Asparaginase ,Humans ,Epigenetics ,Kynurenine ,Liver Neoplasms ,Cancer ,General Medicine ,DNA Methylation ,medicine.disease ,030104 developmental biology ,chemistry ,Gene Knockdown Techniques ,030220 oncology & carcinogenesis ,DNA methylation ,Female ,Carbon-Nitrogen Ligases with Glutamine as Amide-N-Donor ,Asparagine - Abstract
Despite considerable efforts to identify cancer metabolic alterations that might unveil druggable vulnerabilities, systematic characterizations of metabolism as it relates to functional genomic features and associated dependencies remain uncommon. To further understand the metabolic diversity of cancer, we profiled 225 metabolites in 928 cell lines from more than 20 cancer types in the Cancer Cell Line Encyclopedia (CCLE) using liquid chromatography–mass spectrometry (LC-MS). This resource enables unbiased association analysis linking the cancer metabolome to genetic alterations, epigenetic features and gene dependencies. Additionally, by screening barcoded cell lines, we demonstrated that aberrant ASNS hypermethylation sensitizes subsets of gastric and hepatic cancers to asparaginase therapy. Finally, our analysis revealed distinct synthesis and secretion patterns of kynurenine, an immune-suppressive metabolite, in model cancer cell lines. Together, these findings and related methodology provide comprehensive resources that will help clarify the landscape of cancer metabolism. Systematic metabolite profiling across cancer cell lines uncovers patterns associated with genetic and epigenetic features and reveals dysregulated metabolic states that can be exploited for anticancer therapy
- Published
- 2019