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      The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells

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          Abstract

          • Increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response genes is found in breast cancer cells with acquired resistance to lapatinib.

          • The glucose deprivation response gene network correlated significantly with high clinical relapse rates in ErbB2-positive breast cancer patients.

          • Chemical genomics bioinformatics data mining identified drugs that target the glucose deprivation response networks to reduced survival of resistant cells.

          Abstract

          Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network-based computational analysis of global gene expression data from matched sensitive and acquired drug-resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2-positive breast cancer patients. Further, forcing drug-sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.

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          Most cited references14

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          Cancer. Addiction to oncogenes--the Achilles heal of cancer.

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            Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade.

            A number of microarray studies have reported distinct molecular profiles of breast cancers (BC), such as basal-like, ErbB2-like, and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER) -positive subtypes has been inconsistent. Therefore, refinement of their molecular definition is needed. We have previously reported a gene expression grade index (GGI), which defines histologic grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high-or low-genomic grade subgroups and compared these with previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biologic pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple data sets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC.
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              Oncogene addiction: setting the stage for molecularly targeted cancer therapy.

              In pugilistic parlance, the one-two punch is a devastating combination of blows, with the first punch setting the stage and the second delivering the knock-out. This analogy can be extended to molecularly targeted cancer therapies, with oncogene addiction serving to set the stage for tumor cell killing by a targeted therapeutic agent. While in vitro and in vivo examples abound documenting the existence of this phenomenon, the mechanistic underpinnings that govern oncogene addiction are just beginning to emerge. Our current inability to fully exploit this weakness of cancer cells stems from an incomplete understanding of oncogene addiction, which nonetheless represents one of the rare chinks in the formidable armor of cancer cells.
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                Author and article information

                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2012
                31 July 2012
                31 July 2012
                : 8
                : 596
                Affiliations
                [1 ]Department of Systems Biology, The University of Texas MD Anderson Cancer Center , Houston, TX, USA
                [2 ]Chemical and Biomolecular Engineering Department, Rice University , Houston, TX, USA
                Author notes
                [a ]Department of Systems Biology, The University of Texas MD Anderson Cancer Center , 7435 Fannin Street, Unit 0950, Houston, TX 77054, USA. Tel.: +1 713 563 4227; Fax: +1 713 563 4235; pram@ 123456mdanderson.org
                Article
                msb201225
                10.1038/msb.2012.25
                3421441
                22864381
                f447e6fd-ed59-4484-8f12-eeaa7b515132
                Copyright © 2012, EMBO and Macmillan Publishers Limited

                This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial Share Alike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.

                History
                : 02 September 2011
                : 01 June 2012
                Categories
                Article

                Quantitative & Systems biology
                signal transduction,computational methods,bioinformatics,functional genomics,metabolic and regulatory networks

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