Literature DB >> 31625692

Identification of chlorprothixene as a potential drug that induces apoptosis and autophagic cell death in acute myeloid leukemia cells.

Yuxin Du1,2, Kening Li1,2, Xiangeng Wang1, Aman Chandra Kaushik1, Muhammad Junaid1, Dongqing Wei1.   

Abstract

Although acute myeloid leukemia (AML) is a highly heterogeneous malignance, the common molecular mechanisms shared by different AML subtypes play critical roles in AML development. It is possible to identify new drugs that are effective for various AML subtypes based on the common molecular mechanisms. Therefore, we developed a hypothesis-driven bioinformatic drug screening framework by integrating multiple omics data. In this study, we identified that chlorprothixene, a dopamine receptor antagonist, could effectively inhibit growth of AML cells from different subtypes. RNA-seq analysis suggested that chlorprothixene perturbed a series of crucial biological processes such as cell cycle, apoptosis, and autophagy in AML cells. Further investigations indicated that chlorprothixene could induce both apoptosis and autophagy in AML cells, and apoptosis and autophagy could act as partners to induce cell death cooperatively. Remarkably, chlorprothixene was found to inhibit tumor growth and induce in situ leukemic cell apoptosis in the murine xenograft model. Furthermore, chlorprothixene treatment could reduce the level of oncofusion proteins PML-RARα and AML1-ETO, thus elevate the expression of apoptosis-related genes, and lead to AML cell death. Our results provided new insights for drug repositioning of AML therapy and confirmed that chlorprothixene might be a potential candidate for treatment of different subtypes of AML by reducing expression of oncofusion proteins. DATABASE: RNA-seq data are available in GEO database under the accession number GSE124316.
© 2019 Federation of European Biochemical Societies.

Entities:  

Keywords:  acute myeloid leukemia; apoptosis; autophagy; chlorprothixene; oncoprotein

Year:  2019        PMID: 31625692     DOI: 10.1111/febs.15102

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  4 in total

1.  A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences.

Authors:  Jian He; Yanling Wu; Xuemei Pu; Menglong Li; Yanzhi Guo
Journal:  Int J Mol Sci       Date:  2022-02-03       Impact factor: 5.923

Review 2.  The dual role of autophagy in acute myeloid leukemia.

Authors:  Wonhyoung Seo; Prashanta Silwal; Ik-Chan Song; Eun-Kyeong Jo
Journal:  J Hematol Oncol       Date:  2022-05-07       Impact factor: 23.168

3.  Machine Learning Enabled Structure-Based Drug Repurposing Approach to Identify Potential CYP1B1 Inhibitors.

Authors:  Baddipadige Raju; Gera Narendra; Himanshu Verma; Manoj Kumar; Bharti Sapra; Gurleen Kaur; Subheet Kumar Jain; Om Silakari
Journal:  ACS Omega       Date:  2022-08-31

Review 4.  Dopamine Receptors in Cancer: Are They Valid Therapeutic Targets?

Authors:  Arely Rosas-Cruz; Nohemí Salinas-Jazmín; Marco A Velasco- Velázquez
Journal:  Technol Cancer Res Treat       Date:  2021 Jan-Dec
  4 in total

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