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Aberrant signalling by protein kinase CK2 in imatinib-resistant chronic myeloid leukaemia cells: biochemical evidence and therapeutic perspectives.

ABSTRACT: Chronic myeloid leukaemia (CML) is driven by the fusion protein Bcr-Abl, a constitutively active tyrosine kinase playing a crucial role in initiation and maintenance of CML phenotype. Despite the great efficacy of the Bcr-Abl-specific inhibitor imatinib, resistance to this drug is recognized as a major problem in CML treatment. We found that in LAMA84 cells, characterized by imatinib-resistance caused by BCR-ABL1 gene amplification, the pro-survival protein kinase CK2 is up-regulated as compared to the sensitive cells. CK2 exhibits a higher protein-level and a parallel enhancement of catalytic activity. Consistently, CK2-catalysed phosphorylation of Akt-Ser129 is increased. CK2 co-localizes with Bcr-Abl in the cytoplasmic fraction as judged by subcellular fractionation and fluorescence immunolocalization. CK2 and Bcr-Abl are members of the same multi-protein complex(es) in imatinib-resistant cells as demonstrated by co-immunoprecipitation and co-sedimentation in glycerol gradients. Cell treatment with CX-4945, a CK2 inhibitor currently in clinical trials, counteracts CK2/Bcr-Abl interaction and causes cell death by apoptosis. Interestingly, combination of CX-4945 with imatinib displays a synergistic effect in reducing cell viability. Consistently, knockdown of CK2α expression by siRNA restores the sensitivity of resistant LAMA84 cells to low imatinib concentrations. Remarkably, the CK2/Bcr-Abl interaction and the sensitization towards imatinib obtained by CK2-inhibition in LAMA84 is observable also in other imatinib-resistant CML cell lines. These results demonstrate that CK2 contributes to strengthen the imatinib-resistance phenotype of CML cells conferring survival advantage against imatinib. We suggest that CK2 inhibition might be a promising tool for combined strategies in CML therapy.

SUBMITTER: Borgo C

PROVIDER: S-EPMC5528438 | biostudies-other | 2013 Dec

REPOSITORIES: biostudies-other

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Project description:BackgroundThe Gab2 docking protein acts as an important signal amplifier downstream of various growth factor receptors and Bcr-Abl, the driver of chronic myeloid leukaemia (CML). Despite the success of Bcr-Abl tyrosine kinase inhibitors (TKI) in the therapy of CML, TKI-resistance remains an unsolved problem in the clinic. We have recently shown that Gab2 signalling counteracts the efficacy of four distinct Bcr-Abl inhibitors. In the course of that project, we noticed that two clinically relevant drugs, imatinib and dasatinib, provoke distinct alterations in the electrophoretic mobility of Gab2, its signalling output and protein interactions. As the signalling potential of the docking protein is highly modulated by its phosphorylation status, we set out to obtain more insights into the impact of TKIs on Gab2 phosphorylation.FindingsUsing stable isotope labelling by amino acids in cell culture (SILAC)-based quantitative mass spectrometry (MS), we show now that imatinib and dasatinib provoke distinct effects on the phosphorylation status and interactome of Gab2. This study identifies several new phosphorylation sites on Gab2 and confirms many sites previously known from other experimental systems. At equimolar concentrations, dasatinib is more effective in preventing Gab2 tyrosine and serine/threonine phosphorylation than imatinib. It also affects the phosphorylation status of more residues than imatinib. In addition, we also identify novel components of the Gab2 signalling complex, such as casein kinases, stathmins and PIP1 as well as known interaction partners whose association with Gab2 is disrupted by imatinib and/or dasatinib.ConclusionsBy using MS-based proteomics, we have identified new and confirmed known phosphorylation sites and interaction partners of Gab2, which may play an important role in the regulation of this docking protein. Given the growing importance of Gab2 in several tumour entities we expect that our results will help to understand the complex regulation of Gab2 and how this docking protein can contribute to malignancy.

Project description:BackgroundTreatment of patients with chronic myeloid leukaemia (CML) has become increasingly difficult in recent years due to the variety of treatment options available and challenge deciding on the most appropriate treatment strategy for an individual patient. To facilitate the treatment strategy decision, disease assessment should involve molecular response to initial treatment for an individual patient. Patients predicted not to achieve major molecular response (MMR) at 24 months to frontline imatinib may be better treated with alternative frontline therapies, such as nilotinib or dasatinib. The aims of this study were to i) understand the clinical prediction 'rules' for predicting MMR at 24 months for CML patients treated with imatinib using clinical, molecular, and cell count observations (predictive factors collected at diagnosis and categorised based on available knowledge) and ii) develop a predictive model for CML treatment management. This predictive model was developed, based on CML patients undergoing imatinib therapy enrolled in the TIDEL II clinical trial with an experimentally identified achieving MMR group and non-achieving MMR group, by addressing the challenge as a machine learning problem. The recommended model was validated externally using an independent data set from King Faisal Specialist Hospital and Research Centre, Saudi Arabia.Principle findingsThe common prognostic scores yielded similar sensitivity performance in testing and validation datasets and are therefore good predictors of the positive group. The G-mean and F-score values in our models outperformed the common prognostic scores in testing and validation datasets and are therefore good predictors for both the positive and negative groups. Furthermore, a high PPV above 65% indicated that our models are appropriate for making decisions at diagnosis and pre-therapy. Study limitations include that prior knowledge may change based on varying expert opinions; hence, representing the category boundaries of each predictive factor could dramatically change performance of the models.

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Aberrant signalling by protein kinase CK2 in imatinib-resistant chronic myeloid leukaemia cells: biochemical evidence and therapeutic perspectives.

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