Integrative analysis of clinical and bioinformatics databases to identify anticancer properties of digoxin

Yokoyama, S.; Sugimoto, Yasuhiro; Nakagawa, Chihiro; Hosomi, Kouichi; Takada, Mitsutaka

doi:10.1038/s41598-019-53392-y

Cited by 8 publications

(3 citation statements)

References 48 publications

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“…In the past decades, the potential of cardiac glycosides as anticancer agents has been evaluated in various solid tumors and hematologic malignancies in multiple preclinical and clinical studies, originally arising from the epidemiological evidence of a lower risk of certain cancers in patients under treatment with cardiac glycosides [ 15 , 45 ]. Recent technologies, e.g., in silico analysis and high-throughput screening, oftentimes predicted cardiac glycosides as potential candidates for repurposing for cancer therapeutics [ 14 , 46 , 47 ].…”

Section: Discussionmentioning

confidence: 99%

Cardiac glycoside ouabain efficiently targets leukemic stem cell apoptotic machinery independent of cell differentiation status

Poohadsuan,

O’Doherty,

Owattanapanich

et al. 2023

Cell Commun Signal

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Background Acute myeloid leukemia (AML) is an aggressive hematologic malignancy characterized by an accumulation of immature leukemic myeloblasts initiating from leukemic stem cells (LSCs)—the subpopulation that is also considered the root cause of chemotherapy resistance. Repurposing cardiac glycosides to treat cancers has gained increasing attention and supporting evidence, but how cardiac glycosides effectively target LSCs, e.g., whether it involves cell differentiation, remains largely unexplored. Methods Digoxin, a user-designed digitoxigenin-α-L-rhamnoside (D6-MA), and ouabain were tested against various human AML-derived cells with different maturation phenotypes. Herein, we established two study models to specifically determine the effects of cardiac glycosides on LSC death and differentiation—one allowed change in dynamics of LSCs and leukemic progenitor cells (LPCs), while another maintained their undifferentiated status. Regulatory mechanisms underlying cardiac glycoside-induced cytotoxicity were investigated and linked to cell cycle distribution and apoptotic machinery. Results Primitive AML cells containing CD34+ LSCs/LPCs were very responsive to nanomolar concentrations of cardiac glycosides, with ouabain showing the greatest efficiency. Ouabain preferentially induces caspase-dependent apoptosis in LSCs, independent of its cell differentiation status, as evidenced by (i) the tremendous induction of apoptosis by ouabain in AML cells that acquired less than 15% differentiation and (ii) the higher rate of apoptosis in enriched LSCs than in LPCs. We sorted LSCs and LPCs according to their cell cycle distribution into G0/G1, S, and G2/M cells and revealed that G0/G1 cells in LSCs, which was its major subpopulation, were the top ouabain responders, indicating that the difference in ouabain sensitivity between LSCs and LPCs involved both distinct cell cycle distribution and intrinsic apoptosis regulatory mechanisms. Further, Mcl-1 and c-Myc, which were differentially expressed in LSCs and LPCs, were found to be the key apoptosis mediators that determined ouabain sensitivity in AML cells. Ouabain induces a more rapid loss of Mcl-1 and c-Myc in LSCs than in LPCs via the mechanisms that in part involve an inhibition of Mcl-1 protein synthesis and an induction of c-Myc degradation. Conclusions Our data provide new insight for repurposing cardiac glycosides for the treatment of relapsed/refractory AML through targeting LSCs via distinct cell cycle and apoptosis machinery.

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Section: Discussionmentioning

confidence: 99%

Cardiac glycoside ouabain efficiently targets leukemic stem cell apoptotic machinery independent of cell differentiation status

Poohadsuan,

O’Doherty,

Owattanapanich

et al. 2023

Cell Commun Signal

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“…The CMap database contains over one million gene expression signatures upon treatment of a variety of cell types with many different perturbagens (from small-molecule compounds to gene overexpression and gene knockdown reagents). This resource has been successfully used in various studies in the field of cancer research to identify new candidates based on original signatures and to propose new drug repurposing opportunities (see for instance [ 22 , 23 , 24 , 25 ]). Changes in gene expression that arise from treatment with nearly 2500 perturbagens were compared with the expression signature deduced from our correlation analysis to find similarities.…”

Section: Methodsmentioning

confidence: 99%

Quantitative Analysis of Cell Aggregation Dynamics Identifies HDAC Inhibitors as Potential Regulators of Cancer Cell Clustering

Gava

Pignolet

Déjean

et al. 2021

Cancers

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Characterization of the molecular mechanisms involved in tumor cell clustering could open the way to new therapeutic strategies. Towards this aim, we used an in vitro quantitative procedure to monitor the anchorage-independent cell aggregation kinetics in a panel of 25 cancer cell lines. The analysis of the relationship between selected aggregation dynamic parameters and the gene expression data for these cell lines from the CCLE database allowed identifying genes with expression significantly associated with aggregation parameter variations. Comparison of these transcripts with the perturbagen signatures from the Connectivity Map resource highlighted that they were strongly correlated with the transcriptional signature of most histone deacetylase (HDAC) inhibitors. Experimental evaluation of two HDAC inhibitors (SAHA and ISOX) showed that they inhibited the initial step of in vitro tumor cell aggregation. This validates our findings and reinforces the potential interest of HDCA inhibitors to prevent metastasis spreading.

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“… 14 In addition, the usefulness of an integrative approach using both real-world data and bioinformatics databases has been reported. 15 , 16 In this study, we employed an integrative approach to investigate the relationship between antipsychotics and RA using multiple databases.…”

Section: Introductionmentioning

confidence: 99%

Repurposing haloperidol for the treatment of rheumatoid arthritis: an integrative approach using data mining techniques

Nakagawa

Yokoyama

Hosomi

et al. 2021

Therapeutic Advances in Musculoskeletal

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Introduction: Treatment of rheumatoid arthritis (RA) has advanced with the introduction of biological disease-modifying antirheumatic drugs. However, more than 20% of patients with RA still have moderate or severe disease activity. Hence, novel antirheumatic drugs are required. Recently, drug repurposing, a process of identifying new indications for existing drugs, has received great attention. Furthermore, a few reports have shown that antipsychotics are capable of affecting several cytokines that are also modulated by existing antirheumatic drugs. Therefore, we investigated the association between antipsychotics and RA by data mining using real-world data and bioinformatics databases. Methods: Disproportionality and sequence symmetry analyses were employed to identify the associations between the investigational drugs and RA using the US Food and Drug Administration Adverse Event Reporting System (2004–2016) and JMDC administrative claims database (January 2005–April 2017; JMDC Inc., Tokyo, Japan), respectively. The reporting odds ratio (ROR) and information component (IC) were used in the disproportionality analysis to indicate a signal. The adjusted sequence ratio (SR) was used in the sequence symmetry analysis to indicate a signal. The bioinformatics analysis suite, BaseSpace Correlation Engine (Illumina, CA, USA) was employed to explore the molecular mechanisms associated with the potential candidates identified by the drug-repurposing approach. Results: A potential inverse association between the antipsychotic haloperidol and RA, which exhibited significant inverse signals with ROR, IC, and adjusted SR, was found. Furthermore, the results suggested that haloperidol may exert antirheumatic effects by modulating various signaling pathways, including cytokine and chemokine signaling, major histocompatibility complex class-II antigen presentation, and Toll-like receptor cascade pathways. Conclusion: Our drug-repurposing approach using data mining techniques identified haloperidol as a potential antirheumatic drug candidate.

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Integrative analysis of clinical and bioinformatics databases to identify anticancer properties of digoxin

Cited by 8 publications

References 48 publications

Cardiac glycoside ouabain efficiently targets leukemic stem cell apoptotic machinery independent of cell differentiation status

Cardiac glycoside ouabain efficiently targets leukemic stem cell apoptotic machinery independent of cell differentiation status

Quantitative Analysis of Cell Aggregation Dynamics Identifies HDAC Inhibitors as Potential Regulators of Cancer Cell Clustering

Repurposing haloperidol for the treatment of rheumatoid arthritis: an integrative approach using data mining techniques

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