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      Hitting two oncogenic machineries in cancer cells: cooperative effects of the multi-kinase inhibitor ponatinib and the BET bromodomain blockers JQ1 or dBET1 on human carcinoma cells

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          Abstract

          In recent years, numerous new targeted drugs, including multi-kinase inhibitors and epigenetic modulators have been developed for cancer treatment. Ponatinib blocks a variety of tyrosine kinases including ABL and fibroblast growth factor receptor (FGFR), and the BET bromodomain (BRD) antagonists JQ1 and dBET1 impede MYC oncogene expression. Both drugs have demonstrated substantial anti-cancer efficacy against several hematological malignancies. Solid tumors, on the other hand, although frequently driven by FGFR and/or MYC, are often unresponsive to these drugs. This is due, at least in part, to compensatory feedback-loops in the kinome and transcription network of these tumors, which are activated in response to drug exposure. Therefore, we hypothesized that the combination of the multi-kinase inhibitor ponatinib with transcription modulators such as JQ1 or dBET1 might overcome this therapeutic recalcitrance. Using 3H-thymidine uptake, cell cycle analysis, and caspase-3 or Annexin V labeling, we demonstrate that single drugs induce moderate dose-dependent growth-inhibition and/or apoptosis in colon (HCT116, HT29), breast (MCF-7, SKBR3) and ovarian (A2780, SKOV3) cancer cells. Ponatinib elicited primarily apoptosis, while JQ1 and dBET1 caused G0/G1 cell cycle arrest and very mild cell death. Phospho-FGFR and MYC, major targets of ponatinib and BET inhibitors, were downregulated after treatment with single drugs. Remarkably, ponatinib was found to sensitize cells to BET antagonists by enhancing apoptotic cell death, and this effect was associated with downregulation of MYC. In summary, our data shows that ponatinib sensitizes colon, breast, and ovarian cancer cells to BET bromodomain inhibitors. Further studies are warranted to determine the clinical value of this phenomenon.

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          Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors.

          A generalized method for analyzing the effects of multiple drugs and for determining summation, synergism and antagonism has been proposed. The derived, generalized equations are based on kinetic principles. The method is relatively simple and is not limited by whether the dose-effect relationships are hyperbolic or sigmoidal, whether the effects of the drugs are mutually exclusive or nonexclusive, whether the ligand interactions are competitive, noncompetitive or uncompetitive, whether the drugs are agonists or antagonists, or the number of drugs involved. The equations for the two most widely used methods for analyzing synergism, antagonism and summation of effects of multiple drugs, the isobologram and fractional product concepts, have been derived and been shown to have limitations in their applications. These two methods cannot be used indiscriminately. The equations underlying these two methods can be derived from a more generalized equation previously developed by us (59). It can be shown that the isobologram is valid only for drugs whose effects are mutually exclusive, whereas the fractional product method is valid only for mutually nonexclusive drugs which have hyperbolic dose-effect curves. Furthermore, in the isobol method, it is laborious to find proper combinations of drugs that would produce an iso-effective curve, and the fractional product method tends to give indication of synergism, since it underestimates the summation of the effect of mutually nonexclusive drugs that have sigmoidal dose-effect curves. The method described herein is devoid of these deficiencies and limitations. The simplified experimental design proposed for multiple drug-effect analysis has the following advantages: It provides a simple diagnostic plot (i.e., the median-effect plot) for evaluating the applicability of the data, and provides parameters that can be directly used to obtain a general equation for the dose-effect relation; the analysis which involves logarithmic conversion and linear regression can be readily carried out with a simple programmable electronic calculator and does not require special graph paper or tables; and the simplicity of the equation allows flexibility of application and the use of a minimum number of data points. This method has been used to analyze experimental data obtained from enzymatic, cellular and animal systems.
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            AP24534, a pan-BCR-ABL inhibitor for chronic myeloid leukemia, potently inhibits the T315I mutant and overcomes mutation-based resistance.

            Inhibition of BCR-ABL by imatinib induces durable responses in many patients with chronic myeloid leukemia (CML), but resistance attributable to kinase domain mutations can lead to relapse and a switch to second-line therapy with nilotinib or dasatinib. Despite three approved therapeutic options, the cross-resistant BCR-ABL(T315I) mutation and compound mutants selected on sequential inhibitor therapy remain major clinical challenges. We report design and preclinical evaluation of AP24534, a potent, orally available multitargeted kinase inhibitor active against T315I and other BCR-ABL mutants. AP24534 inhibited all tested BCR-ABL mutants in cellular and biochemical assays, suppressed BCR-ABL(T315I)-driven tumor growth in mice, and completely abrogated resistance in cell-based mutagenesis screens. Our work supports clinical evaluation of AP24534 as a pan-BCR-ABL inhibitor for treatment of CML.
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              Analysis of minimal residual disease by Ig/TCR gene rearrangements: guidelines for interpretation of real-time quantitative PCR data.

              Most modern treatment protocols for acute lymphoblastic leukaemia (ALL) include the analysis of minimal residual disease (MRD). To ensure comparable MRD results between different MRD-polymerase chain reaction (PCR) laboratories, standardization and quality control are essential. The European Study Group on MRD detection in ALL (ESG-MRD-ALL), consisting of 30 MRD-PCR laboratories worldwide, has developed guidelines for the interpretation of real-time quantitative PCR-based MRD data. The application of these guidelines ensures identical interpretation of MRD data between different laboratories of the same MRD-based clinical protocol. Furthermore, the ESG-MRD-ALL guidelines will facilitate the comparison of MRD data obtained in different treatment protocols, including those with new drugs.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                29 May 2018
                29 May 2018
                : 9
                : 41
                : 26491-26506
                Affiliations
                1 Department of Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
                2 Ludwig Boltzmann Cluster Oncology, Medical University of Vienna, Vienna, Austria
                3 Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
                4 Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria
                Author notes
                Correspondence to: Thomas W. Grunt, thomas.grunt@ 123456meduniwien.ac.at
                Article
                25474
                10.18632/oncotarget.25474
                5995173
                29899872
                7c339188-8258-4eab-9578-9edace650665
                Copyright: © 2018 Bauer et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 January 2018
                : 10 May 2018
                Categories
                Research Paper

                Oncology & Radiotherapy
                brd4 degrader,dbet1,drug combination,jq1,ponatinib
                Oncology & Radiotherapy
                brd4 degrader, dbet1, drug combination, jq1, ponatinib

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