Metabolic drug survey highlights cancer cell dependencies and vulnerabilities

Tea Pemovska, Johannes W. Bigenzahn, Ismet Srndic, Alexander Lercher, Andreas Bergthaler, Adrián César-Razquin, Felix Kartnig, Christoph Kornauth, Peter Valent, Philipp B. Staber and Giulio Superti-Furga ()
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Tea Pemovska: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Johannes W. Bigenzahn: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Ismet Srndic: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Alexander Lercher: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Andreas Bergthaler: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Adrián César-Razquin: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Felix Kartnig: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences
Christoph Kornauth: Medical University of Vienna
Peter Valent: Medical University of Vienna
Philipp B. Staber: Medical University of Vienna
Giulio Superti-Furga: CeMM—Research Center for Molecular Medicine of the Austrian Academy of Sciences

Nature Communications, 2021, vol. 12, issue 1, 1-19

Abstract: Abstract Interrogation of cellular metabolism with high-throughput screening approaches can unravel contextual biology and identify cancer-specific metabolic vulnerabilities. To systematically study the consequences of distinct metabolic perturbations, we assemble a comprehensive metabolic drug library (CeMM Library of Metabolic Drugs; CLIMET) covering 243 compounds. We, next, characterize it phenotypically in a diverse panel of myeloid leukemia cell lines and primary patient cells. Analysis of the drug response profiles reveals that 77 drugs affect cell viability, with the top effective compounds targeting nucleic acid synthesis, oxidative stress, and the PI3K/mTOR pathway. Clustering of individual drug response profiles stratifies the cell lines into five functional groups, which link to specific molecular and metabolic features. Mechanistic characterization of selective responses to the PI3K inhibitor pictilisib, the fatty acid synthase inhibitor GSK2194069, and the SLC16A1 inhibitor AZD3965, bring forth biomarkers of drug response. Phenotypic screening using CLIMET represents a valuable tool to probe cellular metabolism and identify metabolic dependencies at large.

Date: 2021
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DOI: 10.1038/s41467-021-27329-x

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