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Open AccessArticle

Functional Dependency Analysis Identifies Potential Druggable Targets in Acute Myeloid Leukemia

1
Division of Hematology and Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL 32610-0278, USA
2
Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610-0278, USA
3
Department of Physiological Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL 32610-0278, USA
*
Author to whom correspondence should be addressed.
Authors contributed equally.
Cancers 2020, 12(12), 3710; https://doi.org/10.3390/cancers12123710
Received: 3 November 2020 / Revised: 30 November 2020 / Accepted: 7 December 2020 / Published: 10 December 2020
(This article belongs to the Special Issue Novel Biomarkers and Molecular Targets in Cancer)
New drugs are needed for treating acute myeloid leukemia (AML). We analyzed data from genome-edited leukemia cells to identify druggable targets. These targets were necessary for AML cell survival and had favorable binding sites for drug development. Two lists of genes are provided for target validation, drug discovery, and drug development. The deKO list contains gene-targets with existing compounds in development. The disKO list contains gene-targets without existing compounds yet and represent novel targets for drug discovery.
Refractory disease is a major challenge in treating patients with acute myeloid leukemia (AML). Whereas the armamentarium has expanded in the past few years for treating AML, long-term survival outcomes have yet to be proven. To further expand the arsenal for treating AML, we searched for druggable gene targets in AML by analyzing screening data from a lentiviral-based genome-wide pooled CRISPR-Cas9 library and gene knockout (KO) dependency scores in 15 AML cell lines (HEL, MV411, OCIAML2, THP1, NOMO1, EOL1, KASUMI1, NB4, OCIAML3, MOLM13, TF1, U937, F36P, AML193, P31FUJ). Ninety-four gene KOs met the criteria of (A) specifically essential to AML cell survival, (B) non-essential in non-AML cells, and (C) druggable according to three-dimensional (3D) modeling or ligand-based druggability scoring. Forty-four of 94 gene-KOs (47%) had an already-approved drug match and comprised a drug development list termed “deKO.” Fifty of 94 gene-KOs (53%) had no drug in development and comprised a drug discovery list termed “disKO.” STRING analysis and gene ontology categorization of the disKO targets preferentially cluster in the metabolic processes of UMP biosynthesis, IMP biosynthesis, dihydrofolate metabolism, pyrimidine nucleobase biosynthesis, vitellogenesis, and regulation of T cell differentiation and hematopoiesis. Results from this study serve as a testable compendium of AML drug targets that, after validation, may be translated into new therapeutics. View Full-Text
Keywords: acute myeloid leukemia; CRISPR; screening; target identification acute myeloid leukemia; CRISPR; screening; target identification
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MDPI and ACS Style

Zhou, Y.; Takacs, G.P.; Lamba, J.K.; Vulpe, C.; Cogle, C.R. Functional Dependency Analysis Identifies Potential Druggable Targets in Acute Myeloid Leukemia. Cancers 2020, 12, 3710. https://doi.org/10.3390/cancers12123710

AMA Style

Zhou Y, Takacs GP, Lamba JK, Vulpe C, Cogle CR. Functional Dependency Analysis Identifies Potential Druggable Targets in Acute Myeloid Leukemia. Cancers. 2020; 12(12):3710. https://doi.org/10.3390/cancers12123710

Chicago/Turabian Style

Zhou, Yujia; Takacs, Gregory P.; Lamba, Jatinder K.; Vulpe, Christopher; Cogle, Christopher R. 2020. "Functional Dependency Analysis Identifies Potential Druggable Targets in Acute Myeloid Leukemia" Cancers 12, no. 12: 3710. https://doi.org/10.3390/cancers12123710

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