Epigenetic pathways can regulate gene expression by controlling and interpreting chromatin modifications. Cancer cells are characterized by altered epigenetic landscapes, and commonly exploit the chromatin regulatory machinery to enforce oncogenic gene expression programs1. Although chromatin alterations are, in principle, reversible and often amenable to drug intervention, the promise of targeting such pathways therapeutically has been limited by an incomplete understanding of cancer-specific dependencies on epigenetic regulators. Here we describe a non-biased approach to probe epigenetic vulnerabilities in acute myeloid leukaemia (AML), an aggressive haematopoietic malignancy that is often associated with aberrant chromatin states2. By screening a custom library of small hairpin RNAs (shRNAs) targeting known chromatin regulators in a genetically defined AML mouse model, we identify the protein bromodomain-containing 4 (Brd4) as being critically required for disease maintenance. Suppression of Brd4 using shRNAs or the small-molecule inhibitor JQ1 led to robust antileukaemic effects in vitro and in vivo, accompanied by terminal myeloid differentiation and elimination of leukaemia stem cells. Similar sensitivities were observed in a variety of human AML cell lines and primary patient samples, revealing that JQ1 has broad activity in diverse AML subtypes. The effects of Brd4 suppression are, at least in part, due to its role in sustaining Myc expression to promote aberrant self-renewal, which implicates JQ1 as a pharmacological means to suppress MYC in cancer. Our results establish small-molecule inhibition of Brd4 as a promising therapeutic strategy in AML and, potentially, other cancers, and highlight the utility of RNA interference (RNAi) screening for revealing epigenetic vulnerabilities that can be exploited for direct pharmacological intervention.
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Gene Expression Omnibus
Chi, P., Allis, C. D. & Wang, G. G. Covalent histone modifications—miswritten, misinterpreted and mis-erased in human cancers. Nature Rev. Cancer 10, 457–469 (2010)
Chen, J., Odenike, O. & Rowley, J. D. Leukaemogenesis: more than mutant genes. Nature Rev. Cancer 10, 23–36 (2010)
Gilliland, D. G., Jordan, C. T. & Felix, C. A. The molecular basis of leukemia. Hematology (Am. Soc. Hematol. Educ. Program) 80–97 (2004)
Figueroa, M. E. et al. DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia. Cancer Cell 17, 13–27 (2010)
Dick, J. E. Stem cell concepts renew cancer research. Blood 112, 4793–4807 (2008)
Wang, J., Hoshino, T., Redner, R. L., Kajigaya, S. & Liu, J. M. ETO, fusion partner in t(8;21) acute myeloid leukemia, represses transcription by interaction with the human N-CoR/mSin3/HDAC1 complex. Proc. Natl Acad. Sci. USA 95, 10860–10865 (1998)
Krivtsov, A. V. et al. H3K79 methylation profiles define murine and human MLL-AF4 leukemias. Cancer Cell 14, 355–368 (2008)
Delhommeau, F. et al. Mutation in TET2 in myeloid cancers. N. Engl. J. Med. 360, 2289–2301 (2009)
Ley, T. J. et al. DNMT3A mutations in acute myeloid leukemia. N. Engl. J. Med. 363, 2424–2433 (2010)
Zuber, J. et al. Toolkit for evaluating genes required for proliferation and survival using tetracycline-regulated RNAi. Nature Biotechnol. 29, 79–83 (2011)
Yokoyama, A. & Cleary, M. L. Menin critically links MLL proteins with LEDGF on cancer-associated target genes. Cancer Cell 14, 36–46 (2008)
Yokoyama, A. et al. The menin tumor suppressor protein is an essential oncogenic cofactor for MLL-associated leukemogenesis. Cell 123, 207–218 (2005)
Wu, S. Y. & Chiang, C. M. The double bromodomain-containing chromatin adaptor Brd4 and transcriptional regulation. J. Biol. Chem. 282, 13141–13145 (2007)
French, C. A. et al. BRD4–NUT fusion oncogene: a novel mechanism in aggressive carcinoma. Cancer Res. 63, 304–307 (2003)
Filippakopoulos, P. et al. Selective inhibition of BET bromodomains. Nature 468, 1067–1073 (2010)
Nicodeme, E. et al. Suppression of inflammation by a synthetic histone mimic. Nature 468, 1119–1123 (2010)
Zuber, J. et al. Mouse models of human AML accurately predict chemotherapy response. Genes Dev. 23, 877–889 (2009)
Somervaille, T. C. & Cleary, M. L. Identification and characterization of leukemia stem cells in murine MLL-AF9 acute myeloid leukemia. Cancer Cell 10, 257–268 (2006)
Krivtsov, A. V. et al. Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9. Nature 442, 818–822 (2006)
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)
Somervaille, T. C. et al. Hierarchical maintenance of MLL myeloid leukemia stem cells employs a transcriptional program shared with embryonic rather than adult stem cells. Cell Stem Cell 4, 129–140 (2009)
Kim, J. et al. A Myc network accounts for similarities between embryonic stem and cancer cell transcription programs. Cell 143, 313–324 (2010)
Wong, P. et al. The miR-17-92 microRNA polycistron regulates MLL leukemia stem cell potential by modulating p21 expression. Cancer Res. 70, 3833–3842 (2010)
Jang, M. K. et al. The bromodomain protein Brd4 is a positive regulatory component of P-TEFb and stimulates RNA polymerase II-dependent transcription. Mol. Cell 19, 523–534 (2005)
Yang, Z., He, N. & Zhou, Q. Brd4 recruits P-TEFb to chromosomes at late mitosis to promote G1 gene expression and cell cycle progression. Mol. Cell. Biol. 28, 967–976 (2008)
Schuhmacher, M. et al. The transcriptional program of a human B cell line in response to Myc. Nucleic Acids Res. 29, 397–406 (2001)
Schmidt, M., Nazarov, V., Stevens, L., Watson, R. & Wolff, L. Regulation of the resident chromosomal copy of c-myc by c-Myb is involved in myeloid leukemogenesis. Mol. Cell. Biol. 20, 1970–1981 (2000)
Soucek, L. et al. Modelling Myc inhibition as a cancer therapy. Nature 455, 679–683 (2008)
Felsher, D. W. & Bishop, J. M. Reversible tumorigenesis by MYC in hematopoietic lineages. Mol. Cell 4, 199–207 (1999)
Wilson, A. et al. c-Myc controls the balance between hematopoietic stem cell self-renewal and differentiation. Genes Dev. 18, 2747–2763 (2004)
Zuber, J. et al. An integrated approach to dissecting oncogene addiction implicates a Myb coordinated self-renewal program as essential for leukemia maintenance. Genes Dev. 10.1101/gad.1726911 (in the press)
Taylor, J., Schenck, I., Blankenberg, D. & Nekrutenko, A. Using galaxy to perform large-scale interactive data analyses in Curr. Protoc. Bioinformatics Ch. 10, Unit 10.5. (2007)
Dickins, R. A. et al. Probing tumor phenotypes using stable and regulated synthetic microRNA precursors. Nature Genet. 37, 1289–1295 (2005)
Hemann, M. T. et al. An epi-allelic series of p53 hypomorphs created by stable RNAi produces distinct tumor phenotypes in vivo. Nature Genet. 33, 396–400 (2003)
Wei, J. et al. Microenvironment determines lineage fate in a human model of MLL-AF9 leukemia. Cancer Cell 13, 483–495 (2008)
Wunderlich, M. & Mulloy, J. C. Model systems for examining effects of leukemia-associated oncogenes in primary human CD34+ cells via retroviral transduction. Methods Mol. Biol. 538, 263–285 (2009)
Bennett, J. M. et al. Proposals for the classification of the acute leukaemias. French-American-British (FAB) co-operative group. Br. J. Haematol. 33, 451–458 (1976)
Bennett, J. M. et al. Proposed revised criteria for the classification of acute myeloid leukemia. A report of the French-American-British cooperative group. Ann. Intern. Med. 103, 620–625 (1985)
Vardiman, J. W. et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood 114, 937–951 (2009)
Reich, M. et al. GenePattern 2.0. Nature Genet. 38, 500–501 (2006)
Steger, D. J. et al. DOT1L/KMT4 recruitment and H3K79 methylation are ubiquitously coupled with gene transcription in mammalian cells. Mol. Cell. Biol. 28, 2825–2839 (2008)
Zeng, P. Y., Vakoc, C. R., Chen, Z. C., Blobel, G. A. & Berger, S. L. In vivo dual cross-linking for identification of indirect DNA-associated proteins by chromatin immunoprecipitation. Biotechniques 41, 694–698 (2006)
We thank B. Ma, S. Muller and M. Weissenboeck for technical assistance; J. Simon, E. Earl and L. Bianco for support with mouse work; C. dos Santos for assistance with LSK FACS analysis; S. Hearn for microscopy support; G. Hannon, K. Chang, and E. Hodges for shRNA technology support; A. Gordon and M. Hammell for bioinformatics support; L. Dow for assistance with mouse pathology sample preparation; and G. Blobel for comments on the manuscript. We thank the Don Monti Memorial Research Foundation and Laurie Strauss Leukemia Foundation for research support. J.Z. was supported by a research fellowship from the German Research Foundation (DFG) and by the Andrew Seligson Memorial Clinical Fellowship at CSHL; A.R.R. was supported by an NIH traineeship and the Barbara McClintock fellowship; J.E.B and J.Q. are supported by the Damon-Runyon Cancer Research Foundation and Smith Family Foundation. P.B. is supported by a Damon Runyon-Lilly Clinical Investigator Award and a Leukemia and Lymphoma Society (LLS) Translational Research Program Grant, and is an LLS Scholar in Clinical Research. S.W.L. is supported by a Specialized Center of Research (SCOR) grant from the Leukemia and Lymphoma Society of America, a Cancer Target Discovery and Development (CTD2) grant from the National Cancer Institute, and by the Howard Hughes Medical Institute; C.R.V., J.S. and E.W. are supported by the CSHL President’s Council and the SASS Foundation for Medical Research.
The authors declare no competing financial interests.
This file contains sequences of primers used in this study and Supplementary Figures 1-26 with legends. (PDF 24057 kb)
This file contains the sequences and primary screening performance of the custom shRNA library, including 1094 negative control shRNAs (designated PC and NC, respectively). shRNAs were designated by the number of the first nucleotide of the 22-nt target site in the mRNA transcript at the time of design. Provided are sequences of the 22-nt guide strands as well as a 97-nt oligonucleotides serving as templates for shRNA cloning using PCR. The relative abundance of each shRNA in the pool at the start (T0) and the endpoint (T14) of the screen is provided as normalized deep sequencing reads in two independent replicates (A and B). The relative change in representation is calculated as the ratio of reads in T14 compared to reads in T0 for both replicates. Only shRNAs with sufficient read numbers for evaluating depletion (>500 reads in both replicates, 1072 shRNAs = 97%) were analyzed. Scorers were defined as genes for which at least 2 shRNAs showed more than 20fold (T14/T0 < 0.05) in both replicates. (XLS 444 kb)
This file contains the gene sets used for Gene Set Enrichment Analysis (GSEA). Mouse genesets were obtained were converted into human gene names using bioDBNet dbWalk (http://biodbnet.abcc.ncifcrf.gov/db/dbWalk.php) or manually using the NCBI database. (XLS 84 kb)
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Zuber, J., Shi, J., Wang, E. et al. RNAi screen identifies Brd4 as a therapeutic target in acute myeloid leukaemia. Nature 478, 524–528 (2011). https://doi.org/10.1038/nature10334
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