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      Inhibition of fatty acid desaturation is detrimental to cancer cell survival in metabolically compromised environments

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          Abstract

          Background

          Enhanced macromolecule biosynthesis is integral to growth and proliferation of cancer cells. Lipid biosynthesis has been predicted to be an essential process in cancer cells. However, it is unclear which enzymes within this pathway offer the best selectivity for cancer cells and could be suitable therapeutic targets.

          Results

          Using functional genomics, we identified stearoyl-CoA desaturase (SCD), an enzyme that controls synthesis of unsaturated fatty acids, as essential in breast and prostate cancer cells. SCD inhibition altered cellular lipid composition and impeded cell viability in the absence of exogenous lipids. SCD inhibition also altered cardiolipin composition, leading to the release of cytochrome C and induction of apoptosis. Furthermore, SCD was required for the generation of poly-unsaturated lipids in cancer cells grown in spheroid cultures, which resemble those found in tumour tissue. We also found that SCD mRNA and protein expression is elevated in human breast cancers and predicts poor survival in high-grade tumours. Finally, silencing of SCD in prostate orthografts efficiently blocked tumour growth and significantly increased animal survival.

          Conclusions

          Our data implicate lipid desaturation as an essential process for cancer cell survival and suggest that targeting SCD could efficiently limit tumour expansion, especially under the metabolically compromised conditions of the tumour microenvironment.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40170-016-0146-8) contains supplementary material, which is available to authorized users.

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          Most cited references 46

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          Regulation of cancer cell metabolism.

          Interest in the topic of tumour metabolism has waxed and waned over the past century of cancer research. The early observations of Warburg and his contemporaries established that there are fundamental differences in the central metabolic pathways operating in malignant tissue. However, the initial hypotheses that were based on these observations proved inadequate to explain tumorigenesis, and the oncogene revolution pushed tumour metabolism to the margins of cancer research. In recent years, interest has been renewed as it has become clear that many of the signalling pathways that are affected by genetic mutations and the tumour microenvironment have a profound effect on core metabolism, making this topic once again one of the most intense areas of research in cancer biology.
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            Supervised risk predictor of breast cancer based on intrinsic subtypes.

            PURPOSE To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based "intrinsic" subtypes luminal A, luminal B, HER2-enriched, and basal-like. METHODS A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%. CONCLUSION Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.
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              Metabolic reprogramming: a cancer hallmark even warburg did not anticipate.

              Cancer metabolism has long been equated with aerobic glycolysis, seen by early biochemists as primitive and inefficient. Despite these early beliefs, the metabolic signatures of cancer cells are not passive responses to damaged mitochondria but result from oncogene-directed metabolic reprogramming required to support anabolic growth. Recent evidence suggests that metabolites themselves can be oncogenic by altering cell signaling and blocking cellular differentiation. No longer can cancer-associated alterations in metabolism be viewed as an indirect response to cell proliferation and survival signals. We contend that altered metabolism has attained the status of a core hallmark of cancer. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                barrie.peck@icr.ac.uk
                almut.schulze@uni-wuerzburg.de
                Journal
                Cancer Metab
                Cancer Metab
                Cancer & Metabolism
                BioMed Central (London )
                2049-3002
                1 April 2016
                1 April 2016
                2016
                : 4
                Affiliations
                [ ]Gene Expression Analysis Laboratory, Cancer Research UK London Research Institute, 44 Lincoln’s Inn Fields, London, WC2A 3LY UK
                [ ]Cancer Research UK, Beatson Institute, Switchback Rd, Glasgow, G61 1BD UK
                [ ]Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT UK
                [ ]Department for Biochemistry and Molecular Biology, Theodor-Boveri-Institute, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
                [ ]Molecular Oncology Laboratories, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS UK
                [ ]High Throughput Screening Facility, The Francis Crick Institute, Lincoln`s Inn Fields Laboratories, 44 Lincoln`s Inn Fields, London, WC2A 3LY UK
                [ ]Bioinformatics and Biostatistics Service, The Francis Crick Institute, Lincoln`s Inn Fields Laboratories, 44 Lincoln`s Inn Fields, London, WC2A 3LY UK
                [ ]Experimental Histopathology, The Francis Crick Institute, Lincoln`s Inn Fields Laboratories, 44 Lincoln`s Inn Fields, London, WC2A 3LY UK
                [ ]Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN UK
                [ ]AstraZeneca, Mereside, Alderley Park, Macclesfield, SK10 4TG UK
                [ ]Comprehensive Cancer Center Mainfranken, Josef-Schneider-Str. 6, 97080 Würzburg, Germany
                [ ]Present address: The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, SW3 6JB UK
                Article
                146
                10.1186/s40170-016-0146-8
                4818530
                27042297
                © Peck et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000289, Cancer Research UK (GB);
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council (GB);
                Funded by: FundRef http://dx.doi.org/10.13039/501100005972, Deutsche Krebshilfe;
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
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                Research
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                © The Author(s) 2016

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