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      Targeting Glutathione S-transferase M4 in Ewing sarcoma

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          Abstract

          Ewing sarcoma is a malignant pediatric bone and soft tissue tumor. Although the 5-year survival rate of localized disease approaches 75%, the prognosis of metastatic and/or therapy-resistant disease remains dismal despite the wide use of aggressive therapeutic strategies. We previously reported that high expression of glutathione S-transferase M4 (GSTM4) in primary tumors correlates with poor patient outcomes. GSTM4 is required for oncogenic transformation and mediates resistance to chemotherapeutic drugs in Ewing sarcoma cells. Here, we performed RNA-sequencing analyses of Ewing sarcoma cells and combined our results with publicly available datasets to demonstrate that GSTM4 is a major GST specifically expressed in Ewing sarcoma. Pharmacological inhibition of GSTM4 activity using a pan GST inhibitor, 6-(7-nitro-2,1,3-benzoxadiazol-4-ylthio) hexanol (NBDHEX), significantly limited cellular proliferation and oncogenic transformation of Ewing sarcoma cells. Moreover, combined use of NBDHEX and etoposide synergistically increased cytotoxicity, suggesting a role for GSTM4 as an inhibitor of apoptosis. Mechanistic studies revealed that GSTM4 limits apoptosis owing to its ability to interact with Apoptosis Signal-regulating Kinase 1 (ASK1) and inhibit signaling via the c-Jun N-terminal Kinase axis. To exploit our observation that GSTM4 expression is specifically up-regulated in Ewing sarcoma, we tested the effect of a GSTM4-activated anti-cancer agent, O 2-(2,4-dinitrophenyl) 1-[(4-ethoxycarbonyl)piperazin-1-yl]diazen-1-ium-1,2-diolate or JS-K, on tumor growth and survival. We found that JS-K robustly decreased Ewing sarcoma cell viability and xenograft tumor growth and improved overall survival of xenograft mice. Our data suggest that GSTM4 is a novel therapeutic target for the treatment of high GSTM4-expressing Ewing sarcoma. Strategies that combine standard chemotherapy with agents that inhibit GSTM4, that are activated by GSTM4, or that block GSTM4/ASK1 interactions, can potentially be more specific and/or efficacious than standard therapeutic approaches.

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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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            Regulation of JNK signaling by GSTp.

            Studies of low basal Jun N-terminal kinase (JNK) activity in non-stressed cells led us to identify a JNK inhibitor that was purified and identified as glutathione S-transferase Pi (GSTp) and was characterized as a JNK-associated protein. UV irradiation or H2O2 treatment caused GSTp oligomerization and dissociation of the GSTp-JNK complex, indicating that it is the monomeric form of GSTp that elicits JNK inhibition. Addition of purified GSTp to the Jun-JNK complex caused a dose-dependent inhibition of JNK activity. Conversely, immunodepleting GSTp from protein extracts attenuated JNK inhibition. Furthermore, JNK activity was increased in the presence of specific GSTp inhibitors and a GSTp-derived peptide. Forced expression of GSTp decreased MKK4 and JNK phosphorylation which coincided with decreased JNK activity, increased c-Jun ubiquitination and decreased c-Jun-mediated transcription. Co-transfection of MEKK1 and GSTp restored MKK4 phosphorylation but did not affect GSTp inhibition of JNK activity, suggesting that the effect of GSTp on JNK is independent of the MEKK1-MKK4 module. Mouse embryo fibroblasts from GSTp-null mice exhibited a high basal level of JNK activity that could be reduced by forced expression of GSTp cDNA. In demonstrating the relationships between GSTp expression and its association with JNK, our findings provide new insight into the regulation of stress kinases.
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              Gene expression profiling of human sarcomas: insights into sarcoma biology.

              Sarcomas are a biologically complex group of tumors of mesenchymal origin. By using gene expression microarray analysis, we aimed to find clues into the cellular differentiation and oncogenic pathways active in these tumors as well as potential biomarkers and therapeutic targets. We examined 181 tumors representing 16 classes of human bone and soft tissue sarcomas on a 12,601-feature cDNA microarray. Remarkably, 2,766 probes differentially expressed across this sample set clearly delineated the various tumor classes. Several genes of potential biological and therapeutic interest were associated with each sarcoma type, including specific tyrosine kinases, transcription factors, and homeobox genes. We also identified subgroups of tumors within the liposarcomas, leiomyosarcomas, and malignant fibrous histiocytomas. We found significant gene ontology correlates for each tumor group and identified similarity to normal tissues by Gene Set Enrichment Analysis. Mutation analysis done on 275 tumor samples revealed that the high expression of epidermal growth factor receptor (EGFR) in certain tumors was not associated with gene mutations. Finally, to further the investigation of human sarcoma biology, we have created an online, publicly available, searchable database housing the data from the gene expression profiles of these tumors (http://watson.nhgri.nih.gov/sarcoma), allowing the user to interactively explore this data set in depth.
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                Author and article information

                Contributors
                Journal
                Front Pediatr
                Front Pediatr
                Front. Pediatr.
                Frontiers in Pediatrics
                Frontiers Media S.A.
                2296-2360
                06 August 2014
                2014
                : 2
                : 83
                Affiliations
                [1] 1Center for Children’s Cancer Research, Huntsman Cancer Institute, University of Utah , Salt Lake City, UT, USA
                [2] 2Department of Internal Medicine, Division of Hematology and Hematologic Malignancies, University of Utah , Salt Lake City, UT, USA
                [3] 3Microarray and Genomic Analysis Core Facility, Huntsman Cancer Institute, University of Utah , Salt Lake City, UT, USA
                [4] 4Department of Medicinal Chemistry, University of Utah , Salt Lake City, UT, USA
                [5] 5Department of Pediatrics, New York Medical College , Valhalla, NY, USA
                [6] 6Department of Medicine, New York Medical College , Valhalla, NY, USA
                [7] 7Department of Microbiology and Immunology, New York Medical College , Valhalla, NY, USA
                [8] 8Department of Cell Biology and Anatomy, New York Medical College , Valhalla, NY, USA
                [9] 9Department of Pathology, New York Medical College , Valhalla, NY, USA
                [10] 10Division of Pediatric Hematology/Oncology, School of Medicine, University of Utah , Salt Lake City, UT, USA
                Author notes

                Edited by: Charles G. Mullighan, St Jude Children’s Research Hospital, USA

                Reviewed by: David Loeb, Johns Hopkins University, USA; Scott C. Borinstein, Vanderbilt University, USA

                *Correspondence: Wen Luo, Departments of Pediatrics and Pathology, New York Medical College, Grasslands Reservation, Vosburgh Room 101, Valhalla, NY 10595, USA e-mail: wen_luo@ 123456nymc.edu

                Rupeng Zhuo and Kenneth M. Kosak have contributed equally to this work (co-first authors).

                Savita Sankar and Elizabeth T. Wiles also have contributed equally to this work (co-third authors).

                This article was submitted to Pediatric Oncology, a section of the journal Frontiers in Pediatrics.

                Article
                10.3389/fped.2014.00083
                4123608
                25147782
                ecb4b14f-cbbc-4b46-b823-cc5b508cbada
                Copyright © 2014 Zhuo, Kosak, Sankar, Wiles, Sun, Zhang, Ayello, Prestwich, Shami, Cairo, Lessnick and Luo.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 April 2014
                : 23 July 2014
                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 27, Pages: 9, Words: 6330
                Categories
                Pediatrics
                Original Research

                gstm4,ewing sarcoma,nbdhex,js-k,drug resistance
                gstm4, ewing sarcoma, nbdhex, js-k, drug resistance

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