-Author name in bold denotes the presenting author
-Asterisk * with author name denotes a Non-ASH member
Clinically Relevant Abstract denotes an abstract that is clinically relevant.

PhD Trainee denotes that this is a recommended PHD Trainee Session.

Ticketed Session denotes that this is a ticketed session.

3374 Metabolic Drug Survey Highlights Cancer Cell Dependencies and Vulnerabilities

Program: Oral and Poster Abstracts
Session: 802. Chemical Biology and Experimental Therapeutics: Poster III
Hematology Disease Topics & Pathways:
AML, Diseases, CML, Non-Biological, Therapies, Biological Processes, Myeloid Malignancies, Clinically relevant, integrative -omics, metabolomics, pathways
Monday, December 7, 2020, 7:00 AM-3:30 PM

Tea Pemovska, PhD1,2*, Johannes Bigenzahn, MD, PhD1,3*, Ismet Srndic, MSc1*, Alexander Lercher, MSc1*, Andreas Bergthaler, PhD1*, Adrian Cesar Razquin, PhD1*, Felix Kartnig, MD1*, Philipp B. Staber, MD, PhD2 and Giulio Superti Furga, PhD1,4*

1CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
2Department of Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
3Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
4Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria

Here we assembled a novel metabolic drug library covering 243 compounds allowing to systematically identify metabolic dependencies in high-throughput phenotypic screens. The CeMM Library of Metabolic Drugs (CLIMET) was compiled in a stepwise fashion, starting from 8000 candidate compounds, after a survey of public drug-target databases, and ending with 243 highly-curated compounds including extensive crosschecking for approval status, structural information, compound’s potency and selectivity for the intended target, pathway/target redundancy, and commercial availability. To assess the potency of the compounds in CLIMET, we screened the full collection against a panel of 15 diverse myeloid leukemia cell lines. Each compound was tested for its effect on cell growth and survival in a 10,000-fold concentration range (1nM to 10uM) enabling the generation of dose response curves and calculation of area under the curve values (AUC) for each drug. We, further, functionally grouped the cell lines and drugs based on metabolic drug efficacy patterns and associated them with distinct genomic and metabolic attributes.

Analysis of the metabolic drug response profiles revealed that 77 compounds (32%) affected cell viability with the top effective compounds targeting nucleotide metabolism, oxidative stress, and the PI3K/mTOR pathway. Unsupervised hierarchical clustering of the drug sensitivity profiles stratified the cell lines in 5 functional taxonomic groups, with the activity of 19 compounds significantly contributing to the cell line grouping (e.g. PF-02545920, GW 4064, mTOR inhibitors, daporinad). Comparison of the oxygen consumption rate and extracellular acidification rate showed that the examined cell lines have analogous baseline metabolic phenotypes, suggesting that the mitochondrial function of the cells as assessed by Seahorse analysis did not significantly influence the clustering. Genotype to phenotype associations were identified between FLT3mutations and sensitivity to 5-FU, lestaurtinib, and PF-02545920. Moreover, RAS mutations negatively correlated to mTOR and mitochondrial respiration inhibitor sensitivity, whereas TP53 mutations conferred a resistance phenotype to PI3K pathway inhibitors and antineoplastic agents. Selective sensitivities were detected to the lactate transporter (SLC16A1) inhibitor AZD3965, the PI3K inhibitor pictilisib, and the fatty acid synthase inhibitor GSK2194069, which could be explained by varied gene expression in sensitive cell lines and target/process dependency.

CLIMET allows for identification of metabolic susceptibilities, grouping of cancer cells based on metabolic dependencies, as well as understanding of context-dependent mechanism of action of drugs. Functional drug testing may provide a rapid and robust approach to identify metabolic vulnerabilities, responding patients, and prioritize compounds for clinical evaluation as illustrated with our study.

Disclosures: Staber: Janssen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Research Funding; Celgene/ BMS: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; msd: Consultancy, Honoraria.

Previous Abstract | Next Abstract >>
*signifies non-member of ASH