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      Propranolol potentiates the anti-angiogenic effects and anti-tumor efficacy of chemotherapy agents: implication in breast cancer treatment

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          Abstract

          Recent clinical evidence revealed that the use of beta-blockers such as propranolol, prior to diagnosis or concurrently with chemotherapy, could increase relapse-free and overall survival in breast cancer patients. We therefore hypothesized that propranolol may be able to increase the efficacy of chemotherapy either through direct effects on cancer cells or via anti-angiogenic mechanisms. In vitro proliferation assay showed that propranolol (from 50-100 μM) induces dose-dependent anti-proliferative effects in a panel of 9 human cancer and “normal” cell lines. Matrigel assays revealed that propranolol displays potent anti-angiogenic properties at non-toxic concentrations (<50 μM) but exert no vascular-disrupting activity. Combining chemotherapeutic drugs, such as 5-fluorouracil (5-FU) or paclitaxel, with propranolol at the lowest effective concentration resulted in synergistic, additive or antagonistic effects on cell proliferation in vitro depending on the cell type and the dose of chemotherapy used. Interestingly, breast cancer and vascular endothelial cells were among the most responsive to these combinations. Furthermore, Matrigel assays indicated that low concentrations of propranolol (10 – 50 μM) potentiated the anti-angiogenic effects of 5-FU and paclitaxel. Using an orthotopic xenograft model of triple-negative breast cancer, based on injection of luciferase-expressing MDA-MB-231 cells in the mammary fat pad of nude mice, we showed that propranolol, when used alone, induced only transient anti-tumor effects, if at all, and did not increase median survival. However, the combination of propranolol with chemotherapy resulted in more profound and sustained anti-tumor effects and significantly increased the survival benefits induced by chemotherapy alone (+19% and +79% in median survival for the combination as compared with 5-FU alone and paclitaxel alone, respectively; p<0.05). Collectively our results show that propranolol can potentiate the anti-angiogenic effects and anti-tumor efficacy of chemotherapy. The current study, together with retrospective clinical data, strongly suggests that the use of propranolol concurrently with chemotherapy may improve the outcome of breast cancer patients, thus providing a strong rationale for the evaluation of this drug combination in prospective clinical studies.

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          Most cited references 48

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          Drug combination studies and their synergy quantification using the Chou-Talalay method.

          This brief perspective article focuses on the most common errors and pitfalls, as well as the do's and don'ts in drug combination studies, in terms of experimental design, data acquisition, data interpretation, and computerized simulation. The Chou-Talalay method for drug combination is based on the median-effect equation, derived from the mass-action law principle, which is the unified theory that provides the common link between single entity and multiple entities, and first order and higher order dynamics. This general equation encompasses the Michaelis-Menten, Hill, Henderson-Hasselbalch, and Scatchard equations in biochemistry and biophysics. The resulting combination index (CI) theorem of Chou-Talalay offers quantitative definition for additive effect (CI = 1), synergism (CI 1) in drug combinations. This theory also provides algorithms for automated computer simulation for synergism and/or antagonism at any effect and dose level, as shown in the CI plot and isobologram, respectively.
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            Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors.

             P Talalay,  T C Chou (1984)
            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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              Drug repositioning: identifying and developing new uses for existing drugs.

               K B Thor,  T T Ashburn (2004)
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                Author and article information

                Affiliations
                1Children's Cancer Institute Australia, Lowy Cancer Research Centre, UNSW, Randwick, NSW, Australia
                2Pharmacokinetics Unit, UMR-MD3, Aix-Marseille Univ, Marseille, France
                3INSERM UMR 911, Centre de Recherche en Oncologie biologique et en Oncopharmacologie, Aix-Marseille Univ, Marseille
                4Hematology & Pediatric Oncology Department, La Timone University Hospital of Marseille, France
                5Metronomics Global Health Initiative, Marseille, France
                Université Pierre et Marie Curie - Univ Paris 6, CNRS UMR 7211, INSERM U959, Paris, France
                Author notes
                Correspondence to:Eddy Pasquier, PhD, epasquier@123456ccia.unsw.edu.au
                Nicolas André, MD,PhD, nicolas.andre@123456ap-hm.fr
                Journal
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                October 2011
                17 October 2011
                : 2
                : 10
                : 797-809
                3248157
                22006582
                Copyright: © 2011 Pasquier et al.

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

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                Research Papers

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