Kinases have been running like a thread through Dr. Julhash Uddin Kazi’s career. They also played the lead part in the Lund University’s Associate Professor of Molecular Medicine’s recent Nature Precision Oncology publication titled: The Aurora kinase/β-catenin axis contributes to dexamethasone resistance in leukemia. By combining different methodologies, including multiplex kinase activity profiling, Kazi generated very promising data. “If you want to learn exactly what is going on in a cell you need to go back to its roots by studying kinases.” The study’s results are very promising and might become of great relevance in the treatment of children suffering from acute lymphoblastic leukemia (ALL).
“ALL is currently the most common pediatric malignancy and has the higher cancer-related mortality rate due to relapse or treatment-related toxic effects. This shows a great need for improving the existing treatments by not only identifying new molecular targets but also by identifying patients who require less intensive therapy,” says Kazi. “The aim is to not let the drug kill, but to make its treatment stronger.”
For this study pathway enrichment, kinase regulation and kinase inhibition data were combined. PamGene’s multiplex kinase activity profiling technology was used to measure kinase activity. “PamGene’s peptide substrate-based kinase profiling has been demonstrated to be a powerful technique for determining kinase activity and therefore was one of our technologies of choice. At the time our study took place we had the opportunity to use an in-house PamStation. We performed our own assay preparations and analyzed the data, which was all very easy and friendly to use.”
“We hypothesized that glucocorticoid treatments, like dexamethasone and prednisolone, will modulate the core cellular signaling by altering the activation of protein kinases,” Kazi continues. “While comparing kinase activity enrichment between DMSO and dexamethasone-treated cells, we observed that the activity of protein tyrosine kinases was completely downregulated in dexamethasone-treated cells and the activity of several protein serine/threonine kinases was upregulated. Additional analysis, including using a panel of 378 kinase inhibitors, lead to the observation that all cell lines that were either sensitive or resistant to dexamethasone were highly responsive to inhibitors targeting Aurora kinases, PLK’s and PI3K/mTOR pathway components.”
“Combining machine learning algorithm with gene expression data made us conclude that our model is useful for classification of patients. As a next step will commence a study to collect clinical data to complement the study.”
Data generated on Lund University’s in-house PamStation has been at the basis of at least 3 publications. Dr. Julhash Kazi’s publications can be accessed via the links shown below.
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