scholarly journals Metabolic drug survey highlights cancer cell dependencies and vulnerabilities

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tea Pemovska ◽  
Johannes W. Bigenzahn ◽  
Ismet Srndic ◽  
Alexander Lercher ◽  
Andreas Bergthaler ◽  
...  
Keyword(s):  
Cell Lines ◽  
High Throughput Screening ◽  
Drug Response ◽  
Fatty Acid Synthase ◽  
Leukemia Cell ◽  
Cellular Metabolism ◽  
Acid Synthesis ◽  
Metabolic Drug ◽  
Response Profiles ◽  
Synthase Inhibitor

AbstractInterrogation 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.

Metabolic Drug Survey Highlights Cancer Cell Dependencies and Vulnerabilities

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 26-27
Author(s):  
Tea Pemovska ◽  
Johannes Bigenzahn ◽  
Ismet Srndic ◽  
Alexander Lercher ◽  
Andreas Bergthaler ◽  
...  
Keyword(s):  
Cell Lines ◽  
Drug Testing ◽  
Fatty Acid Synthase ◽  
Structural Information ◽  
Leukemia Cell ◽  
Area Under The Curve ◽  
Mtor Inhibitors ◽  
Nucleotide Metabolism ◽  
Response Curves ◽  
Metabolic Drug

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.

scholarly journals Fatty Acid Synthesis Is Essential for Survival of Cryptococcus neoformans and a Potential Fungicidal Target

2007 ◽  
Vol 51 (10) ◽  
pp. 3537-3545 ◽  
Author(s):  
Methee Chayakulkeeree ◽  
Thomas H. Rude ◽  
Dena L. Toffaletti ◽  
John R. Perfect
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Cryptococcus Neoformans ◽  
Fatty Acid Synthase ◽  
Acid Synthesis ◽  
Yeast Cells ◽  
Synthase Inhibitor ◽  
The Brain

ABSTRACT Fatty acid synthase in the yeast Cryptococcus neoformans is composed of two subunits encoded by FAS1 and FAS2 genes. We inserted a copper-regulated promoter (P CTR4-2 ) to regulate FAS1 and FAS2 expression in Cryptococcus neoformans (strains P CTR4-2 /FAS1 and P CTR4-2 /FAS2, respectively). Both mutants showed growth rates similar to those of the wild type in a low-copper medium in which FAS1 and FAS2 were expressed, but even in the presence of exogenous fatty acids, strains were suppressed in growth under high-copper conditions. The treatment of C. neoformans with fluconazole was shown to have an increased inhibitory activity and even became fungicidal when either FAS1 or FAS2 expression was suppressed. Furthermore, a subinhibitory dose of fluconazole showed anticryptococcal activity in vitro in the presence of cerulenin, a fatty acid synthase inhibitor. In a murine model of pulmonary cryptococcosis, a tissue census of yeast cells in P CTR4-2 /FAS2 strain at day 7 of infection was significantly lower than that in mice treated with tetrathiomolybdate, a copper chelator (P < 0.05), and a yeast census of P CTR4-2 /FAS1 strain at day 14 of infection in the brain was lower in the presence of more copper. In fact, no positive cultures from the brain were detected in mice (with or without tetrathiomolybdate treatment) infected with the P CTR4-2 /FAS2 strain, which implies that this mutant did not reach the brain in mice. We conclude that both FAS1 and FAS2 in C. neoformans are essential for in vitro and in vivo growth in conditions with and without exogenous fatty acids and that FAS1 and FAS2 can potentially be fungicidal targets for C. neoformans with a potential for synergistic behavior with azoles.

Deep learning for drug response prediction in cancer

2020 ◽  
Author(s):  
Delora Baptista ◽  
Pedro G Ferreira ◽  
Miguel Rocha
Keyword(s):  
Deep Learning ◽  
Cell Lines ◽  
Cancer Cell ◽  
High Throughput Screening ◽  
Drug Response ◽  
Prediction Models ◽  
Response Prediction ◽  
Cancer Cell Lines ◽  
Cancer Treatments ◽  
Novel Drugs

Abstract Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of paramount importance for precision medicine. Machine learning(ML) algorithms can be trained on high-throughput screening data to develop models that are able to predict the response of cancer cell lines and patients to novel drugs or drug combinations. Deep learning (DL) refers to a distinct class of ML algorithms that have achieved top-level performance in a variety of fields, including drug discovery. These types of models have unique characteristics that may make them more suitable for the complex task of modeling drug response based on both biological and chemical data, but the application of DL to drug response prediction has been unexplored until very recently. The few studies that have been published have shown promising results, and the use of DL for drug response prediction is beginning to attract greater interest from researchers in the field. In this article, we critically review recently published studies that have employed DL methods to predict drug response in cancer cell lines. We also provide a brief description of DL and the main types of architectures that have been used in these studies. Additionally, we present a selection of publicly available drug screening data resources that can be used to develop drug response prediction models. Finally, we also address the limitations of these approaches and provide a discussion on possible paths for further improvement. Contact:[email protected]

Altered Lipid and Mitochondrial Metabolism Are Viable Targets in Acute Leukemia,

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3618-3618 ◽  
Author(s):  
Timothy Pardee ◽  
Laura M DeFord-Watts ◽  
Erica Peronto ◽  
Denise A Levitan ◽  
David Duane Hurd ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Acute Leukemia ◽  
Cell Lines ◽  
Leukemia Cell ◽  
K562 Cells ◽  
Acid Synthesis ◽  
Acute Leukemias ◽  
Transfusion Independence

Abstract Abstract 3618 Acute leukemias are aggressive malignancies of the bone marrow. In adults these diseases disproportionally affect the elderly with a median age of onset of 72 for acute myeloid leukemia (AML) and 60 for acute lymphoblastic leukemia (ALL). Patients over the age of 60 have less than 10% survival at 5 years. This is the result of a combination of increased primary resistant disease and comorbidities that lead to treatment related mortality. Despite decades of research for the majority of AML and ALL patients, therapies have remained unchanged. There is a desperate need for novel agents with acceptable toxicities. Altered metabolism is a hallmark of cancer including the acute leukemias. Nearly all tumor cells will preferentially utilize anaerobic glycolysis even under aerobic conditions, a phenomenon known as the Warburg effect. Additionally, cancer cells can also increase lipid anabolism and upregulate fatty acid synthase (FASN). These alterations in metabolism represent a possible therapeutic target. The novel lipoate derivative CPI-613 is a first in class agent that targets a key mitochondrial enzyme involved in aberrant metabolism, pyruvate dehydrogenase complex (PDH). PDH is required for the conversion of pyruvate to acetyl-CoA, which then enters into the tricarboxylic acid cycle (TCA). TCA intermediates are utilized as biosynthetic precursors for the production of a variety of molecules, including fatty acids. To determine if leukemic blasts upregulate FASN we performed western blots on leukemic cell lines and primary patient samples and compared levels to normal hematopoietic precursor cells. We found all cell lines and many primary AML samples had increased levels of FASN when compared to controls implying an upregulation of fatty acid synthesis. Consistent with this, inhibition of fatty acid synthesis with the FASN inhibitor orlistat or acetyl-CoA carboxylase inhibitor TOFA resulted in loss of viability of HL60, Jurkat and K562 cells. To determine if PDH inhibition by CPI-613 has activity in the acute leukemias, we tested it against several human and murine acute leukemia cell lines in vitro and in vivo. CPI-613 was active against HL60, Jurkat and K562 cells with an average IC50 value of 14 μM (range 12.2 – 16.4). CPI-613 was found to be synergistic with doxorubicin with Combinatorial Index (CI) values between 0.478 and 0.765. Sensitivity to CPI-613 in a genetically defined murine AML cell line was increased with shRNA mediated knockdown of p53 or expression of MN1 despite their increased resistance to standard therapy. Intriguingly, in preliminary studies, CPI-613 appeared to be highly synergistic with the tyrosine kinase inhibitor nilotinib in Baf-3 cells transduced to express the p210 BCR-ABL kinase with CI values of 0.073–0.059. In vivo, CPI-613 was found to synergize with doxorubicin when these cells were injected into syngeneic Balb/c mice with an extension of median survival from 12 days with doxorubicin alone to 16 days with the combination of CPI-613 and doxorubicin (p=0.0001). In addition to these studies, CPI-631 is also the subject of a phase I clinical trial for patients with relapsed and refractory hematologic malignancies at the Wake Forest University Comprehensive Cancer Center. To date, ten patients have been treated. CPI-613 appears to be well tolerated with no adverse events > grade 1 attributed as probably associated with drug. Four patients had a diagnosis of relapsed or refractory AML. CPI-613 at the initial dosing level concurrent with hydroxyurea resulted in a transient reduction in peripheral blood blasts in the first AML patient. Treatment at the next dosing level resulted in a hematologic improvement leading to transfusion independence and transient decrease in the 7q minus clone in the second AML patient. He maintains transfusion independence after 7 cycles and continues on therapy to date. The third patient with refractory AML had an increase in neutrophil count but no reduction in peripheral blood blasts. Taken together, these data suggest that altered lipid and mitochondrial metabolism are viable targets in the acute leukemias. The novel agent CPI-613 has activity against several acute leukemia cell lines in vitro and in vivo and may have activity in patients with relapsed disease. The therapeutic index appears quite high with only minor toxicities seen. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Cytokine response profiles of human myeloid factor-dependent leukemia cell lines

Leukemia ◽  
1997 ◽  
Vol 11 (5) ◽  
pp. 701-708 ◽  
Author(s):  
HG Drexler ◽  
M Zaborski ◽  
H Quentmeier
Keyword(s):  
Cell Lines ◽  
Leukemia Cell ◽  
Cytokine Response ◽  
Leukemia Cell Lines ◽  
Response Profiles

Antioxidant effects and in vitro cytotoxicity on human cancer cell lines of flavonoid-rich Flamboyant (Delonix regia (Bojer) Raf.) flower extract

2020 ◽  
Vol 21 ◽  
Author(s):  
Putthiporn Khongkaew ◽  
Phanphen Wattanaarsakit ◽  
Konstantinos I. Papadopoulos ◽  
Watcharaphong Chaemsawang
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Leukemia Cell ◽  
Leukemia Cell Line ◽  
Flower Extract ◽  
Dependent Inhibition ◽  
Dose Dependent Inhibition ◽  
Murine Leukemia Cell ◽  
Dose Dependent

Background: Cancer is a noncommunicable disease with increasing incidence and mortality rates both worldwide and in Thailand. Its apparent lack of effective treatments is posing challenging public health issues. Introduction: Encouraging research results indicating probable anti-cancer properties of the Delonix regia flower extract (DRE) have prompted us to evaluate the feasibility of developing a type of product for future cancer prevention or treatment. Methods and Results: In the present report, using High Performance Liquid Chromatography (HPLC), we demonstrate in the DRE, the presence of high concentrations of three identifiable flavonoids, namely rutin 4.15±0.30 % w/w, isoquercitrin 3.04±0.02 %w/w, and myricetin 2.61±0.01 % w/w respectively while the IC50 of DPPH and ABTS assay antioxidation activity was 66.88±6.30 µg/ml and 53.65±7.24 µg/ml respectively. Discussion: Our cancer cell line studies using the MTT assay demonstrated DREs potent and dose dependent inhibition of murine leukemia cell line (P-388: 35.28±4.07% of cell viability remaining), as well as of human breast adenocarcinoma (MCF-7), human cervical carcinoma (HeLa), human oral cavity carcinoma (KB), and human colon carcinoma (HT-29) cell lines in that order of magnitude. Conclusion: Three identifiable flavonoids (rutin, isoquercitrin and myricetin) with high antioxidation activity and potent and dose dependent inhibition of murine leukemia cell line and five other cancer cell lines were documented in the DRE. The extract’s lack of cytotoxicity in 3 normal cell lines is a rare advantage not usually seen in current antineoplastic agents. Yet another challenge of the DRE was its low dissolution rate and long-term storage stability, issues to be resolved before a future product can be formulated.

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