Literature DB >> 31046221

Leukemia Cell Cycle Chemical Profiling Identifies the G2-Phase Leukemia Specific Inhibitor Leusin-1.

Xiaoyu Xia, Yu-Chen Lo, Ankur A Gholkar, Silvia Senese, Joseph Y Ong, Erick F Velasquez, Robert Damoiseaux, Jorge Z Torres.   

Abstract

Targeting the leukemia proliferation cycle has been a successful approach to developing antileukemic therapies. However, drug screening efforts to identify novel antileukemic agents have been hampered by the lack of a suitable high-throughput screening platform for suspension cells that does not rely on flow-cytometry analyses. We report the development of a novel leukemia cell-based high-throughput chemical screening platform for the discovery of cell cycle phase specific inhibitors that utilizes chemical cell cycle profiling. We have used this approach to analyze the cell cycle response of acute lymphoblastic leukemia CCRF-CEM cells to each of 181420 druglike compounds. This approach yielded cell cycle phase specific inhibitors of leukemia cell proliferation. Further analyses of the top G2-phase and M-phase inhibitors identified the leukemia specific inhibitor 1 (Leusin-1). Leusin-1 arrests cells in G2 phase and triggers an apoptotic cell death. Most importantly, Leusin-1 was more active in acute lymphoblastic leukemia cells than other types of leukemias, non-blood cancers, or normal cells and represents a lead molecule for developing antileukemic drugs.

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Year:  2019        PMID: 31046221      PMCID: PMC6884739          DOI: 10.1021/acschembio.9b00173

Source DB:  PubMed          Journal:  ACS Chem Biol        ISSN: 1554-8929            Impact factor:   5.100


  27 in total

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Review 4.  Principles and methods of integrative genomic analyses in cancer.

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Review 5.  Development of an effective therapy for chronic myelogenous leukemia.

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Review 9.  Cytogenetic and molecular predictors of outcome in acute lymphocytic leukemia: recent developments.

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10.  Computational Cell Cycle Profiling of Cancer Cells for Prioritizing FDA-Approved Drugs with Repurposing Potential.

Authors:  Yu-Chen Lo; Silvia Senese; Bryan France; Ankur A Gholkar; Robert Damoiseaux; Jorge Z Torres
Journal:  Sci Rep       Date:  2017-09-12       Impact factor: 4.379

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