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      Inactivation of nuclear factor κB by MIP-based drug combinations augments cell death of breast cancer cells

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          Drug combination therapy to treat cancer is a strategic approach to increase successful treatment rate. Optimizing combination regimens is vital to increase therapeutic efficacy with minimal side effects.

          Materials and methods

          In the present study, we evaluated the in vitro cytotoxicity of double and triple combinations consisting of 1′S-1′-acetoxychavicol acetate (ACA), Mycobacterium indicus pranii (MIP) and cisplatin (CDDP) against 14 various human cancer cell lines to address the need for more effective therapy. Our data show synergistic effects in MCF-7 cells treated with MIP:ACA, MIP:CDDP and MIP:ACA:CDDP combinations. The type of interaction between MIP, ACA and CDDP was evaluated based on combination index being <0.8 for synergistic effect. Identifying the mechanism of cell death based on previous studies involved intrinsic apoptosis and nuclear factor kappa B (NF-κB) and tested in Western blot analysis. Inactivation of NF-κB was confirmed by p65 and IκBα, while intrinsic apoptosis pathway activation was confirmed by caspase-9 and Apaf-1 expression.


          All combinations confirmed intrinsic apoptosis activation and NF-κB inactivation.


          Double and triple combination regimens that target induction of the same death mechanism with reduced dosage of each drug could potentially be clinically beneficial in reducing dose-related toxicities.

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          Most cited references 36

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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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            Antimicrobial susceptibility testing: a review of general principles and contemporary practices.

            An important task of the clinical microbiology laboratory is the performance of antimicrobial susceptibility testing of significant bacterial isolates. The goals of testing are to detect possible drug resistance in common pathogens and to assure susceptibility to drugs of choice for particular infections. The most widely used testing methods include broth microdilution or rapid automated instrument methods that use commercially marketed materials and devices. Manual methods that provide flexibility and possible cost savings include the disk diffusion and gradient diffusion methods. Each method has strengths and weaknesses, including organisms that may be accurately tested by the method. Some methods provide quantitative results (eg, minimum inhibitory concentration), and all provide qualitative assessments using the categories susceptible, intermediate, or resistant. In general, current testing methods provide accurate detection of common antimicrobial resistance mechanisms. However, newer or emerging mechanisms of resistance require constant vigilance regarding the ability of each test method to accurately detect resistance.
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              NF-kappaB controls cell growth and differentiation through transcriptional regulation of cyclin D1.

              Accumulating evidence implicates the transcription factor NF-kappaB as a positive mediator of cell growth, but the molecular mechanism(s) involved in this process remains largely unknown. Here we use both a skeletal muscle differentiation model and normal diploid fibroblasts to gain insight into how NF-kappaB regulates cell growth and differentiation. Results obtained with the C2C12 myoblast cell line demonstrate that NF-kappaB functions as an inhibitor of myogenic differentiation. Myoblasts generated to lack NF-kappaB activity displayed defects in cellular proliferation and cell cycle exit upon differentiation. An analysis of cell cycle markers revealed that NF-kappaB activates cyclin D1 expression, and the results showed that this regulatory pathway is one mechanism by which NF-kappaB inhibits myogenesis. NF-kappaB regulation of cyclin D1 occurs at the transcriptional level and is mediated by direct binding of NF-kappaB to multiple sites in the cyclin D1 promoter. Using diploid fibroblasts, we demonstrate that NF-kappaB is required to induce cyclin D1 expression and pRb hyperphosphorylation and promote G(1)-to-S progression. Consistent with results obtained with the C2C12 differentiation model, we show that NF-kappaB also promotes cell growth in embryonic fibroblasts, correlating with its regulation of cyclin D1. These data therefore identify cyclin D1 as an important transcriptional target of NF-kappaB and reveal a mechanism to explain how NF-kappaB is involved in the early phases of the cell cycle to regulate cell growth and differentiation.

                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                01 May 2018
                : 12
                : 1053-1063
                [1 ]Institute of Biological Science (Genetics & Molecular Biology), Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
                [2 ]Department of Biotechnology, Faculty of Applied Sciences, UCSI University, Kuala Lumpur, Malaysia
                [3 ]Centre for Natural Product Research and Drug Discovery (CENAR), University of Malaya, Kuala Lumpur, Malaysia
                [4 ]Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
                [5 ]Pathogen Biology Laboratory, Department of Biotechnology and Bioinformatics, University of Hyderabad, Hyderabad, India
                [6 ]Centre for Research in Biotechnology for Agriculture (CEBAR), University of Malaya, Kuala Lumpur, Malaysia
                Author notes
                Correspondence: Noor Hasima Nagoor, Institute of Biological Science (Genetics & Molecular Biology), Faculty of Science, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur, Malaysia, Tel +60 3 7967 5921, Fax +60 3 7967 5908, Email hasima@ 123456um.edu.my
                © 2018 Subramaniam et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

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