For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
88
views
17
references
 Top references
cited by
243
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      431
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: not found

      Response and resistance to BET bromodomain inhibitors in triple-negative breast cancer.

      Author(s): 1 , 2 , 1 , 2 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 1 , 1 , 1 , 2 , 1 , 2 , 4 , 1 , 2 , 1 , 6 , 7 , 3 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 7 , 1 , 2 , 1 , 8 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 9 , 9 , 10 , 10 , 11 , 11 , 1 , 2 , 1 , 2 , 2 , 3 , 7 , 1 , 9 , 1 , 2 , 9 , 3 , 9 , 12 , 3 , 1 , 2 , 12 , 1 , 2 , 9 , 12
      Publication date (Electronic):
      Journal: Nature
      Publisher: Springer Nature

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Triple-negative breast cancer (TNBC) is a heterogeneous and clinically aggressive disease for which there is no targeted therapy. BET bromodomain inhibitors, which have shown efficacy in several models of cancer, have not been evaluated in TNBC. These inhibitors displace BET bromodomain proteins such as BRD4 from chromatin by competing with their acetyl-lysine recognition modules, leading to inhibition of oncogenic transcriptional programs. Here we report the preferential sensitivity of TNBCs to BET bromodomain inhibition in vitro and in vivo, establishing a rationale for clinical investigation and further motivation to understand mechanisms of resistance. In paired cell lines selected for acquired resistance to BET inhibition from previously sensitive TNBCs, we failed to identify gatekeeper mutations, new driver events or drug pump activation. BET-resistant TNBC cells remain dependent on wild-type BRD4, which supports transcription and cell proliferation in a bromodomain-independent manner. Proteomic studies of resistant TNBC identify strong association with MED1 and hyper-phosphorylation of BRD4 attributable to decreased activity of PP2A, identified here as a principal BRD4 serine phosphatase. Together, these studies provide a rationale for BET inhibition in TNBC and present mechanism-based combination strategies to anticipate clinical drug resistance.

          Related collections

          Most cited references17

          • Record: found
          • Abstract: found
          • Article: not found

          Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors.

          P Talalay, T C Chou (1984)
          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.
          Article 0 comments Cited 858 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The CRAPome: a Contaminant Repository for Affinity Purification Mass Spectrometry Data

            Dattatreya Mellacheruvu, Zachary Wright, Amber L Couzens … (2013)
            Affinity purification coupled with mass spectrometry (AP-MS) is now a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (e.g. proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. While the standard approach is to identify nonspecific interactions using one or more negative controls, most small-scale AP-MS studies do not capture a complete, accurate background protein set. Fortunately, negative controls are largely bait-independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the Contaminant Repository for Affinity Purification (the CRAPome) and describe the use of this resource to score protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely available online at www.crapome.org.
            Article 0 comments Cited 646 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The JAK2/STAT3 signaling pathway is required for growth of CD44⁺CD24⁻ stem cell-like breast cancer cells in human tumors.

              Lauren L. C. Marotta, Vanessa Almendro, Andriy Marusyk … (2011)
              Intratumor heterogeneity is a major clinical problem because tumor cell subtypes display variable sensitivity to therapeutics and may play different roles in progression. We previously characterized 2 cell populations in human breast tumors with distinct properties: CD44+CD24- cells that have stem cell-like characteristics, and CD44-CD24+ cells that resemble more differentiated breast cancer cells. Here we identified 15 genes required for cell growth or proliferation in CD44+CD24- human breast cancer cells in a large-scale loss-of-function screen and found that inhibition of several of these (IL6, PTGIS, HAS1, CXCL3, and PFKFB3) reduced Stat3 activation. We found that the IL-6/JAK2/Stat3 pathway was preferentially active in CD44+CD24- breast cancer cells compared with other tumor cell types, and inhibition of JAK2 decreased their number and blocked growth of xenografts. Our results highlight the differences between distinct breast cancer cell types and identify targets such as JAK2 and Stat3 that may lead to more specific and effective breast cancer therapies.
              Article 0 comments Cited 363 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (iso-abbrev): Nature
                Title: Nature
                Publisher: Springer Nature
                ISSN (Electronic): 1476-4687
                ISSN (Print): 0028-0836
                Publication date (Electronic): Jan 21 2016
                Volume: 529
                Issue: 7586
                Affiliations
                [1 ] Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA.
                [2 ] Department of Medicine, Brigham and Women's Hospital, and Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA.
                [3 ] Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
                [4 ] Princess Margaret Cancer Center/University Health Network, Toronto, Ontario M5G1L7, Canada.
                [5 ] Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G2M9, Canada.
                [6 ] Harvard University, Cambridge, Massachusetts 02138, USA.
                [7 ] Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
                [8 ] Department of Pathology, Brigham and Women's Hospital, and Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115, USA.
                [9 ] Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA.
                [10 ] Simmons Comprehensive Cancer Center, Departments of Biochemistry and Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
                [11 ] Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA.
                [12 ] Broad Institute, Cambridge, Massachusetts 02142, USA.
                Article
                Publisher Item ID: nature16508 Mid ID: NIHMS742790
                DOI: 10.1038/nature16508
                PMC ID: 4854653
                PubMed ID: 26735014
                SO-VID: 82256476-3233-4a6f-8b6a-a1dd5288a5c4
                History

                Data availability:

                Comments

                Comment on this article

                scite_

                Similar content431

                See all similar

                Cited by238

                See all cited by

                Most referenced authors1,402

                See all reference authors