The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia

Abstract Glucocorticoids, such as dexamethasone and prednisolone, are widely used in cancer treatment. Different hematological malignancies respond differently to this treatment which, as could be expected, correlates with treatment outcome. In this study, we have used a glucocorticoid-induced gene...

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Main Authors: Kinjal Shah, Mehreen Ahmed, Julhash U. Kazi
Format: Article
Language:English
Published: Nature Publishing Group 2021-02-01
Series:npj Precision Oncology
Online Access:https://doi.org/10.1038/s41698-021-00148-5
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spelling doaj-8d171ef063c246f09213d55170975b312021-04-02T18:56:56ZengNature Publishing Groupnpj Precision Oncology2397-768X2021-02-015111210.1038/s41698-021-00148-5The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemiaKinjal Shah0Mehreen Ahmed1Julhash U. Kazi2Division of Translational Cancer Research, Department of Laboratory Medicine, Lund UniversityDivision of Translational Cancer Research, Department of Laboratory Medicine, Lund UniversityDivision of Translational Cancer Research, Department of Laboratory Medicine, Lund UniversityAbstract Glucocorticoids, such as dexamethasone and prednisolone, are widely used in cancer treatment. Different hematological malignancies respond differently to this treatment which, as could be expected, correlates with treatment outcome. In this study, we have used a glucocorticoid-induced gene signature to develop a deep learning model that can predict dexamethasone sensitivity. By combining gene expression data from cell lines and patients with acute lymphoblastic leukemia, we observed that the model is useful for the classification of patients. Predicted samples have been used to detect deregulated pathways that lead to dexamethasone resistance. Gene set enrichment analysis, peptide substrate-based kinase profiling assay, and western blot analysis identified Aurora kinase, S6K, p38, and β-catenin as key signaling proteins involved in dexamethasone resistance. Deep learning-enabled drug synergy prediction followed by in vitro drug synergy analysis identified kinase inhibitors against Aurora kinase, JAK, S6K, and mTOR that displayed synergy with dexamethasone. Combining pathway enrichment, kinase regulation, and kinase inhibition data, we propose that Aurora kinase or its several direct or indirect downstream kinase effectors such as mTOR, S6K, p38, and JAK may be involved in β-catenin stabilization through phosphorylation-dependent inactivation of GSK-3β. Collectively, our data suggest that activation of the Aurora kinase/β-catenin axis during dexamethasone treatment may contribute to cell survival signaling which is possibly maintained in patients who are resistant to dexamethasone.https://doi.org/10.1038/s41698-021-00148-5
collection DOAJ
language English
format Article
sources DOAJ
author Kinjal Shah
Mehreen Ahmed
Julhash U. Kazi
spellingShingle Kinjal Shah
Mehreen Ahmed
Julhash U. Kazi
The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
npj Precision Oncology
author_facet Kinjal Shah
Mehreen Ahmed
Julhash U. Kazi
author_sort Kinjal Shah
title The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
title_short The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
title_full The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
title_fullStr The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
title_full_unstemmed The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
title_sort aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia
publisher Nature Publishing Group
series npj Precision Oncology
issn 2397-768X
publishDate 2021-02-01
description Abstract Glucocorticoids, such as dexamethasone and prednisolone, are widely used in cancer treatment. Different hematological malignancies respond differently to this treatment which, as could be expected, correlates with treatment outcome. In this study, we have used a glucocorticoid-induced gene signature to develop a deep learning model that can predict dexamethasone sensitivity. By combining gene expression data from cell lines and patients with acute lymphoblastic leukemia, we observed that the model is useful for the classification of patients. Predicted samples have been used to detect deregulated pathways that lead to dexamethasone resistance. Gene set enrichment analysis, peptide substrate-based kinase profiling assay, and western blot analysis identified Aurora kinase, S6K, p38, and β-catenin as key signaling proteins involved in dexamethasone resistance. Deep learning-enabled drug synergy prediction followed by in vitro drug synergy analysis identified kinase inhibitors against Aurora kinase, JAK, S6K, and mTOR that displayed synergy with dexamethasone. Combining pathway enrichment, kinase regulation, and kinase inhibition data, we propose that Aurora kinase or its several direct or indirect downstream kinase effectors such as mTOR, S6K, p38, and JAK may be involved in β-catenin stabilization through phosphorylation-dependent inactivation of GSK-3β. Collectively, our data suggest that activation of the Aurora kinase/β-catenin axis during dexamethasone treatment may contribute to cell survival signaling which is possibly maintained in patients who are resistant to dexamethasone.
url https://doi.org/10.1038/s41698-021-00148-5
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