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      Identification of a tumor-promoter cholesterol metabolite in human breast cancers acting through the glucocorticoid receptor

      research-article
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      Proceedings of the National Academy of Sciences of the United States of America
      National Academy of Sciences
      breast cancer, oncometabolism, dendrogenin A, therapy, nuclear receptor

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          Significance

          Cholesterol and its transformation into cholesterol-5,6-epoxides (5,6-EC) was long suspected as contributing to breast cancer (BC) pathogenesis, before it was found that 5,6-EC metabolism controls BC development and is deregulated in breast cancers. Herein, we studied in tumor cells and human samples how 5,6-EC metabolism deregulation promotes tumor progression. We have discovered a pathway in BCs producing an oncometabolite derived from 5,6-EC, through the action of the cortisol-inactivating enzyme, and identified the glucocorticoid receptor (GR) as the target mediating its proliferative effects. Inhibition of its production or GR significantly blocked its action on BC progression. Thus, targeting this oncometabolism and GR represents a new opportunity for therapeutic intervention in BCs and potentially other cancers presenting such deregulations.

          Abstract

          Breast cancer (BC) remains the primary cause of death from cancer among women worldwide. Cholesterol-5,6-epoxide (5,6-EC) metabolism is deregulated in BC but the molecular origin of this is unknown. Here, we have identified an oncometabolism downstream of 5,6-EC that promotes BC progression independently of estrogen receptor α expression. We show that cholesterol epoxide hydrolase (ChEH) metabolizes 5,6-EC into cholestane-3β,5α,6β-triol, which is transformed into the oncometabolite 6-oxo-cholestan-3β,5α-diol (OCDO) by 11β-hydroxysteroid-dehydrogenase-type-2 (11βHSD2). 11βHSD2 is known to regulate glucocorticoid metabolism by converting active cortisol into inactive cortisone. ChEH inhibition and 11βHSD2 silencing inhibited OCDO production and tumor growth. Patient BC samples showed significant increased OCDO levels and greater ChEH and 11βHSD2 protein expression compared with normal tissues. The analysis of several human BC mRNA databases indicated that 11βHSD2 and ChEH overexpression correlated with a higher risk of patient death, highlighting that the biosynthetic pathway producing OCDO is of major importance to BC pathology. OCDO stimulates BC cell growth by binding to the glucocorticoid receptor (GR), the nuclear receptor of endogenous cortisol. Interestingly, high GR expression or activation correlates with poor therapeutic response or prognosis in many solid tumors, including BC. Targeting the enzymes involved in cholesterol epoxide and glucocorticoid metabolism or GR may be novel strategies to prevent and treat BC.

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          Most cited references38

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          Is Open Access

          bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analyses

          We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a ‘prognostic module’. In this study, we develop a new module called ‘correlation module’, which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a ‘tested’ gene. A gene ontology (GO) mining function is also proposed to explore GO ‘biological process’, ‘molecular function’ and ‘cellular component’ terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a ‘tested’ gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies’ conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer. Database URL: http://bcgenex.centregauducheau.fr
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            Activation of the glucocorticoid receptor is associated with poor prognosis in estrogen receptor-negative breast cancer.

            Estrogen receptor-negative (ER(-)) breast cancers have limited treatment options and are associated with earlier relapses. Because glucocorticoid receptor (GR) signaling initiates antiapoptotic pathways in ER(-) breast cancer cells, we hypothesized that activation of these pathways might be associated with poor prognosis in ER(-) disease. Here we report findings from a genome-wide study of GR transcriptional targets in a premalignant ER(-) cell line model of early breast cancer (MCF10A-Myc) and in primary early-stage ER(-) human tumors. Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) coupled to time-course expression profiling led us to identify epithelial-to-mesenchymal transition (EMT) pathways as an important aspect associated with GR activation. We validated these findings by carrying out a meta-analysis of primary breast tumor gene expression from 1,378 early-stage breast cancer patients with long-term clinical follow-up, confirming that high levels of GR expression significantly correlated with shorter relapse-free survival in ER(-) patients who were treated or untreated with adjuvant chemotherapy. Notably, in ER(+) breast cancer patients, high levels of GR expression in tumors were significantly associated with better outcome relative to low levels of GR expression. Gene expression analysis revealed that ER(-) tumors expressing high GR levels exhibited differential activation of EMT, cell adhesion, and inflammation pathways. Our findings suggest a direct transcriptional role for GR in determining the outcome of poor-prognosis ER(-) breast cancers.
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              • Abstract: found
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              Is Open Access

              A refined molecular taxonomy of breast cancer

              The current histoclinical breast cancer classification is simple but imprecise. Several molecular classifications of breast cancers based on expression profiling have been proposed as alternatives. However, their reliability and clinical utility have been repeatedly questioned, notably because most of them were derived from relatively small initial patient populations. We analyzed the transcriptomes of 537 breast tumors using three unsupervised classification methods. A core subset of 355 tumors was assigned to six clusters by all three methods. These six subgroups overlapped with previously defined molecular classes of breast cancer, but also showed important differences, notably the absence of an ERBB2 subgroup and the division of the large luminal ER+ group into four subgroups, two of them being highly proliferative. Of the six subgroups, four were ER+/PR+/AR+, one was ER−/PR−/AR+ and one was triple negative (AR−/ER−/PR−). ERBB2-amplified tumors were split between the ER−/PR−/AR+ subgroup and the highly proliferative ER+ LumC subgroup. Importantly, each of these six molecular subgroups showed specific copy-number alterations. Gene expression changes were correlated to specific signaling pathways. Each of these six subgroups showed very significant differences in tumor grade, metastatic sites, relapse-free survival or response to chemotherapy. All these findings were validated on large external datasets including more than 3000 tumors. Our data thus indicate that these six molecular subgroups represent well-defined clinico-biological entities of breast cancer. Their identification should facilitate the detection of novel prognostic factors or therapeutical targets in breast cancer.

                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                31 October 2017
                12 October 2017
                : 114
                : 44
                : E9346-E9355
                Affiliations
                [1] aTeam “Cholesterol Metabolism and Therapeutic Innovations,” Cancer Research Center of Toulouse (CRCT), UMR 1037, Université de Toulouse , CNRS, Inserm, UPS, 31037 Toulouse, France;
                [2] b Université Paul Sabatier , 31062 Toulouse, France;
                [3] c Affichem , 31400 Toulouse, France;
                [4] dInstitut Claudius Regaud, Institut Universitaire du Cancer Toulouse-Oncopole , 31059 Toulouse, France;
                [5] e Vascular Biology, Atherothrombosis & Mass Spectrometry Laboratory , Sapienza University of Rome, 04100 Latina, Italy;
                [6] fl'Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, University of Montpellier , F-34298 Montpellier, France;
                [7] gINSERM/UPS-US006/Centre Régional d'Exploration Fonctionnelle et Ressources Expérimentales, Service d’Histopathologie, Centre Hospitalier Universitaire Purpan , 31024 Toulouse, France;
                [8] hPôle Technologique, Cancer Research Center of Toulouse (CRCT), Plateau Interactions Moléculaires, INSERM-UMR1037 , 31037 Toulouse, France
                Author notes
                2To whom correspondence may be addressed. Email: marc.poirot@ 123456inserm.fr or sandrine.poirot@ 123456inserm.fr .

                Edited by Christopher K. Glass, University of California, San Diego, La Jolla, CA, and approved September 15, 2017 (received for review May 13, 2017)

                Author contributions: M.P. and S.S.-P. designed research; M.V., P.d.M., A. Mallinger, F.D., E.H.-C., J.L., N.S., R.S., G.S., A. Mougel, E.N., L.M., E.B., C.Z., M.L.-T., T.A.S., R.D.-P., C.F., L.L., M.R., M.P., and S.S.-P. performed research; M.V., P.d.M., A. Mallinger, F.D., E.H.-C., J.L., N.S., R.S., G.S., A. Mougel, E.N., L.M., E.B., L.I., C.Z., M.L.-T., L.C., T.F., V.C., T.A.S., P.R., R.D.-P., C.F., L.L., F.L., M.R., M.P., and S.S.-P. analyzed data; and M.P. and S.S.-P. wrote the paper.

                1M.V., P.d.M., and A. Mallinger contributed equally to this work.

                Article
                PMC5676900 PMC5676900 5676900 201707965
                10.1073/pnas.1707965114
                5676900
                29078321
                b5a084d9-2cff-4d56-a1a0-98fbf8f1a61f
                Published under the PNAS license.
                History
                Page count
                Pages: 10
                Categories
                PNAS Plus
                Biological Sciences
                Medical Sciences
                PNAS Plus

                nuclear receptor,breast cancer,oncometabolism,dendrogenin A,therapy

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