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      Urolithin A gains in antiproliferative capacity by reducing the glycolytic potential via the p53/TIGAR axis in colon cancer cells

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      Carcinogenesis
      Oxford University Press

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          Abstract

          Urolithin A inhibits growth of colon cancer cells alone and synergistically in combination with oxaliplatin. Those activities are markedly supported by activation of the p53/TIGAR axis and subsequent reduction of the cellular glycolytic potential by urolithin A.

          Abstract

          Polyphenols have shown promising bioactivity in experimental in vitro and in vivo models for cancer chemoprevention. However, consumed orally, they are often transformed by gut microbes into new active principles with so far incompletely deciphered molecular mechanisms. Here, enterolacton, S-equol and urolithin A as representatives of metabolites of lignans, isoflavones and ellagitannins, respectively, were examined for their impact on HCT116 colon cancer cell growth, cooperativity with oxaliplatin and p53 dependency in vitro. Whereas enterolacton and S-equol (≤60 µM) did not elicit growth inhibition or positive cooperativity with oxaliplatin, urolithin A showed an IC 50 value of 19 µM (72 h) and synergism with oxaliplatin. Urolithin A induced p53 stabilization and p53 target gene expression, and absence of p53 significantly dampened the antiproliferative effect of urolithin A (IC 50(p53−/−) = 38 µM). P53 was dispensable for the G 2/M arrest in HCT116 cells but required for induction of a senescence-like phenotype upon long-term exposure and for the observed synergism with oxaliplatin. Moreover, extracellular flux analyses and knockdown approaches uncovered a reduced glycolytic potential via the p53/TIGAR axis which was linked to the higher susceptibility of wildtype cells to urolithin A. Overall, the p53 status turned out to be an important determinant for the potential benefit of dietary ellagitannins in cancer chemoprevention or use in adjuvant therapy.

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          Most cited references40

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          On the origin of cancer cells.

          O WARBURG (1956)
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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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              TIGAR, a p53-Inducible Regulator of Glycolysis and Apoptosis

              The p53 tumor-suppressor protein prevents cancer development through various mechanisms, including the induction of cell-cycle arrest, apoptosis, and the maintenance of genome stability. We have identified a p53-inducible gene named TIGAR (TP53-induced glycolysis and apoptosis regulator). TIGAR expression lowered fructose-2,6-bisphosphate levels in cells, resulting in an inhibition of glycolysis and an overall decrease in intracellular reactive oxygen species (ROS) levels. These functions of TIGAR correlated with an ability to protect cells from ROS-associated apoptosis, and consequently, knockdown of endogenous TIGAR expression sensitized cells to p53-induced death. Expression of TIGAR may therefore modulate the apoptotic response to p53, allowing survival in the face of mild or transient stress signals that may be reversed or repaired. The decrease of intracellular ROS levels in response to TIGAR may also play a role in the ability of p53 to protect from the accumulation of genomic damage.
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                Author and article information

                Journal
                Carcinogenesis
                Carcinogenesis
                carcin
                Carcinogenesis
                Oxford University Press (UK )
                0143-3334
                1460-2180
                March 2019
                12 November 2018
                12 November 2018
                : 40
                : 1
                : 93-101
                Affiliations
                Department of Pharmacognosy, University of Vienna, Vienna, Austria
                Author notes
                To whom correspondence should be addressed. Tel: +43 1 4277 55993; Fax: +43 1 4277 855270; Email: elke.heiss@ 123456univie.ac.at
                Article
                bgy158
                10.1093/carcin/bgy158
                6412115
                30418550
                7eea93e8-5a30-49f7-9b43-e840b5af6d06
                © The Author(s) 2018. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 04 July 2018
                : 16 October 2018
                : 07 November 2018
                Page count
                Pages: 9
                Funding
                Funded by: Austrian Science Fund 10.13039/501100002428
                Award ID: FWF P293932
                Funded by: Herzfelder'sche Familienstiftung 10.13039/501100003494
                Categories
                Inflammation, Microenvironment and Prevention

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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