ArticleNPJ precision oncology2021
The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia.
Article in NPJ precision oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- Severe toxicities in amazonian populations and the role of precision medicine in acute lymphoblastic leukemia treatment.Scientific reports · 2024Article
- AlphaML: A clear, legible, explainable, transparent, and elucidative binary classification platform for tabular data.Patterns (New York, N.Y.) · 2024Article
- Transcriptome Analysis of Beta-Catenin-Related Genes in CD34+ Haematopoietic Stem and Progenitor Cells from Patients with AML.Mediterranean journal of hematology and infectious diseases · 2024Article
- A Receptor Tyrosine Kinase Inhibitor Sensitivity Prediction Model Identifies AXL Dependency in Leukemia.International journal of molecular sciences · 2023Article
- Sprouty4 at the crossroads of Trk neurotrophin receptor signaling suppression by glucocorticoids.Frontiers in molecular neuroscience · 2023Article
- A deep tabular data learning model predicting cisplatin sensitivity identifies BCL2L1 dependency in cancer.Computational and structural biotechnology journal · 2023Article
- Analyses of Transcriptomics Cell Signalling for Pre-Screening Applications in the Integrated Approach for Testing and Assessment of Non-Genotoxic Carcinogens.International journal of molecular sciences · 2022Review
- Article
- SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets.Genomics, proteomics & bioinformatics · 2022Article
- PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis.Nucleic acids research · 2022Article
- Phosphorylation-Dependent Regulation of WNT/Beta-Catenin Signaling.Frontiers in oncology · 2022Review
- DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal.Nucleic acids research · 2021Article
- Machine learning in the prediction of cancer therapy.Computational and structural biotechnology journal · 2021Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.