The histone H3 Lys27-specific demethylase UTX (or KDM6A) is targeted by loss-of-function mutations in multiple cancers. Here, we demonstrate that UTX suppresses myeloid leukemogenesis through noncatalytic functions, a property shared with its catalytically inactive Y-chromosome paralog, UTY (or KDM6C). In keeping with this, we demonstrate concomitant loss/mutation of KDM6A (UTX) and UTY in multiple human cancers. Mechanistically, global genomic profiling showed only minor changes in H3K27me3 but significant and bidirectional alterations in H3K27ac and chromatin accessibility; a predominant loss of H3K4me1 modifications; alterations in ETS and GATA-factor binding; and altered gene expression after Utx loss. By integrating proteomic and genomic analyses, we link these changes to UTX regulation of ATP-dependent chromatin remodeling, coordination of the COMPASS complex and enhanced pioneering activity of ETS factors during evolution to AML. Collectively, our findings identify a dual role for UTX in suppressing acute myeloid leukemia via repression of oncogenic ETS and upregulation of tumor-suppressive GATA programs.
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Jenuwein, T. & Allis, C. D. Translating the histone code. Science 293, 1074–1080 (2001).
Agger, K. et al. UTX and JMJD3 are histone H3K27 demethylases involved in HOX gene regulation and development. Nature 449, 731–734 (2007).
Dalgliesh, G. L. et al. Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes. Nature 463, 360–363 (2010).
Bailey, P. et al. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature 531, 47–52 (2016).
Gui, Y. et al. Frequent mutations of chromatin remodeling genes in transitional cell carcinoma of the bladder. Nat. Genet. 43, 875–878 (2011).
Robinson, G. et al. Novel mutations target distinct subgroups of medulloblastoma. Nature 488, 43–48 (2012).
van Haaften, G. et al. Somatic mutations of the histone H3K27 demethylase gene UTX in human cancer. Nat. Genet. 41, 521–523 (2009).
Huether, R. et al. The landscape of somatic mutations in epigenetic regulators across 1,000 paediatric cancer genomes. Nat. Commun. 5, 3630 (2014).
Ntziachristos, P. et al. Contrasting roles of histone 3 lysine 27 demethylases in acute lymphoblastic leukaemia. Nature 514, 513–517 (2014).
Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N. Engl. J. Med. 368, 2059–2074 (2013).
Jankowska, A. M. et al. Mutational spectrum analysis of chronic myelomonocytic leukemia includes genes associated with epigenetic regulation: UTX, EZH2, and DNMT3A. Blood 118, 3932–3941 (2011).
Wouters, B. J. & Delwel, R. Epigenetics and approaches to targeted epigenetic therapy in acute myeloid leukemia. Blood 127, 42–52 (2016).
Greenfield, A. et al. The UTX gene escapes X inactivation in mice and humans. Hum. Mol. Genet. 7, 737–742 (1998).
Van der Meulen, J. et al. The H3K27me3 demethylase UTX is a gender-specific tumor suppressor in T-cell acute lymphoblastic leukemia. Blood 125, 13–21 (2015).
Arcipowski, K. M., Martinez, C. A. & Ntziachristos, P. Histone demethylases in physiology and cancer: a tale of two enzymes, JMJD3 and UTX. Curr. Opin. Genet. Dev. 36, 59–67 (2016).
Walport, L. J. et al. Human UTY(KDM6C) is a male-specific N ϵ-methyl lysyl demethylase. J. Biol. Chem. 289, 18302–18313 (2014).
Van der Meulen, J., Speleman, F. & Van Vlierberghe, P. The H3K27me3 demethylase UTX in normal development and disease. Epigenetics 9, 658–668 (2014).
Skarnes, W. C. et al. A conditional knockout resource for the genome-wide study of mouse gene function. Nature 474, 337–342 (2011).
Faber, Z. J. et al. The genomic landscape of core-binding factor acute myeloid leukemias. Nat. Genet. 48, 1551–1556 (2016).
Papaemmanuil, E. et al. Genomic classification and prognosis in acute myeloid leukemia. N. Engl. J. Med. 374, 2209–2221 (2016).
Thieme, S. et al. The histone demethylase UTX regulates stem cell migration and hematopoiesis. Blood 121, 2462–2473 (2013).
Wang, C. et al. UTX regulates mesoderm differentiation of embryonic stem cells independent of H3K27 demethylase activity. Proc. Natl. Acad. Sci. USA 109, 15324–15329 (2012).
Wilson, N. K. et al. Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model. Blood 127, e12–e23 (2016).
Cho, Y. W. et al. PTIP associates with MLL3- and MLL4-containing histone H3 lysine 4 methyltransferase complex. J. Biol. Chem. 282, 20395–20406 (2007).
Foulds, C. E., Nelson, M. L., Blaszczak, A. G. & Graves, B. J. Ras/mitogen-activated protein kinase signaling activates Ets-1 and Ets-2 by CBP/p300 recruitment. Mol. Cell. Biol. 24, 10954–10964 (2004).
Wilson, N. K. et al. Combinatorial transcriptional control in blood stem/progenitor cells: genome-wide analysis of ten major transcriptional regulators. Cell Stem Cell 7, 532–544 (2010).
Morris, S. A. et al. Overlapping chromatin-remodeling systems collaborate genome wide at dynamic chromatin transitions. Nat. Struct. Mol. Biol. 21, 73–81 (2014).
Tzelepis, K. et al. A CRISPR dropout screen identifies genetic vulnerabilities and therapeutic targets in acute myeloid leukemia. Cell Rep. 17, 1193–1205 (2016).
Shpargel, K. B., Starmer, J., Yee, D., Pohlers, M. & Magnuson, T. KDM6 demethylase independent loss of histone H3 lysine 27 trimethylation during early embryonic development. PLoS Genet. 10, e1004507 (2014).
Morales Torres, C., Laugesen, A. & Helin, K. Utx is required for proper induction of ectoderm and mesoderm during differentiation of embryonic stem cells. PLoS One 8, e60020 (2013).
Yoo, K. H. et al. Histone demethylase KDM6A controls the mammary luminal lineage through enzyme-independent mechanisms. Mol. Cell. Biol. 36, 2108–2120 (2016).
Beyaz, S. et al. The histone demethylase UTX regulates the lineage-specific epigenetic program of invariant natural killer T cells. Nat. Immunol. 18, 184–195 (2017).
Wang, S. P. et al. A UTX-MLL4-p300 transcriptional regulatory network coordinately shapes active enhancer landscapes for eliciting transcription. Mol. Cell 67, 308–321.e306 (2017).
Zaret, K. S. & Mango, S. E. Pioneer transcription factors, chromatin dynamics, and cell fate control. Curr. Opin. Genet. Dev. 37, 76–81 (2016).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Ciau-Uitz, A., Wang, L., Patient, R. & Liu, F. ETS transcription factors in hematopoietic stem cell development. Blood Cells Mol. Dis. 51, 248–255 (2013).
May, W. A. et al. Ewing sarcoma 11;22 translocation produces a chimeric transcription factor that requires the DNA-binding domain encoded by FLI1 for transformation. Proc. Natl. Acad. Sci. USA 90, 5752–5756 (1993).
Tomlins, S. A. et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310, 644–648 (2005).
Goldberg, L. et al. Genome-scale expression and transcription factor binding profiles reveal therapeutic targets in transgenic ERG myeloid leukemia. Blood 122, 2694–2703 (2013).
Marcucci, G. et al. Overexpression of the ETS-related gene, ERG, predicts a worse outcome in acute myeloid leukemia with normal karyotype: a Cancer and Leukemia Group B study. J. Clin. Oncol. 23, 9234–9242 (2005).
Gao, J., Chen, Y. H. & Peterson, L. C. GATA family transcriptional factors: emerging suspects in hematologic disorders. Exp. Hematol. Oncol. 4, 28 (2015).
Hahn, C. N. et al. Heritable GATA2 mutations associated with familial myelodysplastic syndrome and acute myeloid leukemia. Nat. Genet. 43, 1012–1017 (2011).
Greif, P. A. et al. GATA2 zinc finger 1 mutations associated with biallelic CEBPA mutations define a unique genetic entity of acute myeloid leukemia. Blood 120, 395–403 (2012).
Gröschel, S. et al. A single oncogenic enhancer rearrangement causes concomitant EVI1 and GATA2 deregulation in leukemia. Cell 157, 369–381 (2014).
Miller, S. A., Mohn, S. E. & Weinmann, A. S. Jmjd3 and UTX play a demethylase-independent role in chromatin remodeling to regulate T-box family member-dependent gene expression. Mol. Cell 40, 594–605 (2010).
Lee, S., Lee, J. W. & Lee, S. K. UTX, a histone H3-lysine 27 demethylase, acts as a critical switch to activate the cardiac developmental program. Dev. Cell 22, 25–37 (2012).
Local, A. et al. Identification of H3K4me1-associated proteins at mammalian enhancers. Nat. Genet. 50, 73–82 (2018).
Forsberg, L. A. et al. Mosaic loss of chromosome Y in peripheral blood is associated with shorter survival and higher risk of cancer. Nat. Genet. 46, 624–628 (2014).
Dumanski, J. P. et al. Smoking is associated with mosaic loss of chromosome Y. Science 347, 81–83 (2015).
Zhou, W. et al. Mosaic loss of chromosome Y is associated with common variation near TCL1A. Nat. Genet. 48, 563–568 (2016).
Kogan, S. C. et al. Bethesda proposals for classification of nonlymphoid hematopoietic neoplasms in mice. Blood 100, 238–245 (2002).
Morse, H. C. III et al. Bethesda proposals for classification of lymphoid neoplasms in mice. Blood 100, 246–258 (2002).
Koike-Yusa, H. et al. Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library. Nat. Biotechnol. 32, 267–273 (2014).
Yan, M. et al. A previously unidentified alternatively spliced isoform of t(8;21) transcript promotes leukemogenesis. Nat. Med. 12, 945–949 (2006).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Xu, S., Grullon, S., Ge, K. & Peng, W. Spatial clustering for identification of ChIP-enriched regions (SICER) to map regions of histone methylation patterns in embryonic stem cells. Methods Mol. Biol. 1150, 97–111 (2014).
Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481, 389–393 (2012).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
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).
Kent, W. J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).
Hulsen, T., de Vlieg, J. & Alkema, W. BioVenn: a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams. BMC Genomics 9, 488 (2008).
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Kumasaka, N., Knights, A. J. & Gaffney, D. J. Fine-mapping cellular QTLs with RASQUAL and ATAC-seq. Nat. Genet. 48, 206–213 (2016).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Pardo, M. et al. An expanded Oct4 interaction network: implications for stem cell biology, development, and disease. Cell Stem Cell 6, 382–395 (2010).
Käll, L., Canterbury, J. D., Weston, J., Noble, W. S. & MacCoss, M. J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods 4, 923–925 (2007).
Brosch, M., Yu, L., Hubbard, T. & Choudhary, J. Accurate and sensitive peptide identification with Mascot Percolator. J. Proteome Res. 8, 3176–3181 (2009).
Spivak, M., Weston, J., Bottou, L., Käll, L. & Noble, W. S. Improvements to the percolator algorithm for peptide identification from shotgun proteomics data sets. J. Proteome Res. 8, 3737–3745 (2009).
Teo, G. et al. SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software. J. Proteomics 100, 37–43 (2014).
Jones, D. et al. cgpCaVEManWrapper: simple execution of CaVEMan in order to detect somatic single nucleotide variants in NGSdata. Curr. Protoc. Bioinformatics 56, 15.10.11–15.10.18 (2016).
Ye, K., Schulz, M. H., Long, Q., Apweiler, R. & Ning, Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 25, 2865–2871 (2009).
Raine, K. M. et al. cgpPindel: Identifying somatically acquired insertion and deletion events from paired end sequencing. Curr. Protoc. Bioinformatics 52, 15.7.1–15.7.12 (2015).
Boeva, V. et al. Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data. Bioinformatics 28, 423–425 (2012).
This study was primarily funded by a joint Bloodwise Program Grant (17006) to B.J.P.H. and G.S.V. Work in the laboratory of B.J.P.H. is also funded by an ERC consolidator award (grant 647685 COMAL), a Cancer Research UK program award, the Medical Research Council, (MRC) the Wellcome Trust (WT) and the Cambridge NIHR BRC. We acknowledge the WT/MRC Center grant (097922/Z/11/Z) and support from WT strategic award 100140. G.S.V. is funded by a Cancer Research UK Senior Cancer Research Fellowship (C22324/A23015). The laboratory of G.S.V. is also supported by the Kay Kendall Leukemia Fund and core funding from the Sanger Institute (WT098051).
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Integrated supplementary information
Supplementary Figure 1 Additional blood count results from sick Utx−/− vs Utx+/+ mice. Exome sequencing.
(a) WBC (b) PLT and (c) HGB counts of diseased Utx+/+, Utx+/− and Utx−/− mice; the mean ± s.e.m is shown; n = number of mice per genotype. P value was determined by one-way ANOVA with Bonferroni correction; for PLT: t = 2.733, df=56; for HGB: t = 2.43; df = 56. (d) Mutated genes and (e) copy-number changes (from exome sequencing) in 7 individual Utx−/− AMLs. (f) Deletion of Utx exon3 in comparison to exon4 was detected in all Utx−/− AMLs. The mean ± s.e.m is shown; n = number of mice; P by two-sided t-test (t = 13, df = 12). (g) c-KIT+ BM cells were isolated form Utx+/+ and Utx−/−mice (n = 3 mice per genotype) and transduced with lentivral vectors expressing AML-ETO9a. Cells were transplanted into lethally irradiated syngeneic recipient mice and mouse survival was monitored. (h) Kaplan-Meier survival curves of mice transplanted with Utx−/−; AML-ETO9a and control Utx+/+; AML-ETO9a cells; n = number of mice; P by Log-rank (Mantel-Cox) test, df = 1. (i) Spleen sizes of mice in h, the mean ± s.e.m is shown; n = number of mice; P by two-sided t-test (t = 2.798, df = 15).
(a) Gating strategy and fluorophores used for separation of LT-HSC, ST-HSC, LSK, MPP, LMPP as well as (b) GMP, CMP, MEP and (c) CLP populations in Utx+/+ and Utx−/−mice.
(a) Cell numbers from pre-leukemic Utx+/+, Utx+/−, and Utx−/− in a serial re-plating assay (for Utx+/+ vs Utx−/− in plating: 1, t = 7.018; df = 25; plating 2, t = 8.668, df = 25; plating 4 t = 3.342, df = 19). Mature cell frequencies in pre-leukemic (b) BM and (c) spleen as well as (c) PLT counts in Utx+/+, Utx+/−,and Utx−/− mice (t = 2.977, df = 27). (e) Relative mature cell frequencies in blood of 36-week old mice; P calculated vs Utx+/+ control; only significant P values are shown. For Utx+/+ vs Utx−/− comparison, MAC1 (t = 6.718, df = 15), B220 (4.442, df = 15); for Utx+/+ vs Utx+/− comparison, MAC1 (t = 2.571; df = 15) (f) WBC (t = 3.879, df = 15) and (g) PLT counts (t = 6.487, df = 15) from aged (36-week-old) Utx+/+, Utx+/− and Utx−/−. (h) Spleen (i) liver weights, (j) WBC, (k) PLT and (l) HGB in aged (for 22 months) Utx+/Y, and Utx−/Y. The mean ± s.e.m is shown; n = number of mice per genotype. In a, d, e, f, and g, P value was determined by one-way ANOVA with Bonferroni correction. In b, c, h-i P was determined by two-sided t-test as ns.
(a) Spleen weights of pre-leukemic Utx+/Y, and Utx−/Y. (b) HSPC/Lin- and (c) LT-HSC/ST-HSC frequency in BM cells from Utx+/Y, and Utx−/Y. (d) LK, CMP, GMP, MEP and (e) CLP frequency in BM from pre-leukemic Utx+/Y, and Utx−/Y. (f) BM colonies from Utx+/Y, and Utx−/Y in a serial re-plating assay. (g) Mature cell frequencies in pre-leukemic BM and (h) spleen as well as (i) PLT counts in Utx+/Y, and Utx−/Y mice. In a-i the mean ± s.e.m is shown; n = number of mice per genotype, P by two-sided t-test. For CLP, t = 4.206, df = 10; for MEP, t = 5.028, df = 8. Only significant P values are shown.
(a) Proportion of differential H3K27ac peaks at non-promoter regions overlapped with promoter-interacting regions (PIRs). Based on promoter capture Hi-C data in HPC-7 cell line, a total number of 54,339 PIRs were defined as HindIII digested fragments that form significant interactions (CHiCAGO score ≥5) with promoter baits. (b) Regions marked by increased H3K27ac in Utx−/− vs Utx+/+ HSPCs interact with the Pax5 promoter in HPC-7 cells. (c) Regions marked by decreased H3K27ac in Utx−/− vs Utx+/+ HSPCs interact with the Map4k5 promoter in HPC-7 cells.(d) Immunoblots showing global levels of H3K27me3, H3K27ac and UTX protein in the Utx−/− and Utx+/+ pre-leukemic mouse BM cells. Histone 3 (H3) was used as protein loading control. Results of one representative experiment are shown (n = 3 experiments). Uncropped images are shown in Supplementary Fig. 12 (e) Overlap of peaks and (f) peak-associated genes between UTX-bound sites (6734 loci) and all differential H3K27ac modifications (2916 loci). Differential H3K27ac peaks (FDR<1%, -1.5>FC>1.5) were defined by DiffBind tool; n = 2 mice per genotype. (g) Genomic snapshot of UTX and PU.1 demonstrates enhanced PU.1 binding in the promoter region of Ets1, Ets2 and Fli1 in the absence of Utx. UTX also binds to the promoter of these genes in Utx+/+ mice. In e, P by Fisher's exact test for peak comparisons; in f, P by hypergeometric test for gene comparisons.
(a) Overlap of peaks between PU.1-enriched sites and increased H3K27ac or (b) gained H3K4me1 sites. (c) Overlap of peaks and (d) peak-associated genes between UTX-bound regions (2916 genes) and regions with loss of H3K27ac sites (2054 genes) in the Utx−/−. (e) Genomic snapshot of UTX, H3K27ac, H3K27me3 ChIP-seq in Utx+/+ and Utx−/− Lin− at the Cul4a locus showing no direct co-localisation of UTX binding with changes in H3K27ac. Instead UTX binds in proximity to these changes. (f) Co-IP showing association between UTX and both SMARCA4 and CHD4. Uncropped images are shown in Supplementary Fig. S12 P by Fisher's exact test for peak comparisons; P by hypergeometric test for gene comparisons. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype for H3K27ac, H3K4me1 and UTX; n = 3 mice per genotype for PU.1 ChIP-seq.
Supplementary Figure 7 Correlation of closed chromatin regions with UTX binding and altered H3K27ac.
(a) Intersection of peaks between differentially closed chromatin and loss of H3K27ac followed by motif analysis of overlapping sites; number indicates motif rank. (b) Comparison of downregulated genes to closed chromatin regions in Utx−/− followed by motif analysis of the overlap; number indicates motif rank. Motif analysis in lower panels of a and b - by HOMER software. (c) Intersection of peaks between UTX-bound and open chromatin sites. (d) Intersection of closed chromatin sites and loss of H3K4me1. (e) Immunoblot showing UTX protein level in 416B-Cas9 cells edited with Utx gRNA or empty gRNA control. Actin was used as loading control (repeated in n = 3 experiments). Uncropped images are shown in Supplementary Fig.12 (f) ChIP for SMARCA4, CHD4, UTX followed by qPCR for Aff1 and (g) Lrrc8c loci shown as fold enrichment over control loci (GD_chr5, gene desert on chromosome 5) in 416B-Cas9 cells with edited Utx vs Empty-gRNA control. Genomic snapshots show chromatin co-occupacy of UTX, SMARCA4 and CHD4 at studied regions. The mean ± s.e.m is shown; n = 3-5 independent cell cultures; P by two-sided t-test. In f (Utx_ex3 gRNA vs Empty-gRNA) for SMARCA4 t = 2.371; df = 9; for CHD4 t = 2.793, df = 7; for UTX t = 2.671, df = 5. In g (Utx_ex3 gRNA vs Empty-gRNA) for SMARCA4 t = 4.723; df = 8; for CHD4 t = 2.818, df = 7; for UTX t = 6.009, df = 6. In a, c, and d, P by Fisher's exact test; in b, P by hypergeometric test. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype for H3K27ac and UTX; n = 3 mice per genotype for ATAC-seq.
Supplementary Figure 8 Functional redundancy between UTX and SMARCA4 loss for chromatin accessibility on GATA sites.
(a) Schematic representation of experimental strategy: Cas9 expressing Utx−/− and Utx+/+ HSPCs were transduced with lentiviral vector expressing gRNA for Smarca4 and Chd4 and empty gRNA as a control. Six days post transduction we analysed chromatin accessibility by ATAC-seq. (b) Differential peaks between empty gRNA and Smarca4 gRNA in Utx+/+ cells (FDR<0.05; FC< −1.25) were compared with differential peaks lost upon Utx deletion (empty gRNA in Utx+/+ was compared to empty gRNA in Utx−/−; FDR<0.01; FC< −1.5) followed by motif analysis of the overlap. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype, P for peak comparison by Fisher's exact test. Motif and statistical analysis in lower panel of b was determined by HOMER software. (c) Genomic snapshot of ATAC-seq at Kif5a locus. Note that Smarca4 editing but not Chd4 knockout phenocopy Utx loss at indicated in blue region.
Supplementary Figure 9 Correlation of open chromatin sites with gain of H3K27ac, H3K4me1 and gene expression.
(a) Intersection of peaks between differentially opened chromatin and gained H3K27ac and (b) gained H3K4me1 sites. (c) Comparison of upregulated genes to opened chromatin regions (2175 genes) in Utx−/− followed by motif analysis of the overlap, number indicates motif rank. P in a and b, by Fisher's exact test; P in c by hypergeometric test. Motif and statistical analysis was determined by HOMER software. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype for H3K27ac and H3K4me1; n = 3 mice per genotype for ATAC-seq. (d) MONO-MAC6 proliferation upon editing of TCF3 and TCF12. BFP-positive fraction was compared with the non-transduced population and normalized to day 4 (d4) for each gRNA. The mean ± s.d. is shown; n = independent cell cultures; P by one-way ANOVA with Bonferroni correction; P shown for edited gene on day 19 vs control gRNA (EMPTY) d19; for TCF12, t = 18.81, df = 6; for TCF3, t = 14.22, df=6. d – day in culture.
Previously reported interactions were obtained from STRING database, Uniprot annotations and literature searches. The graph was drawn with Cytoscape using the organic layout, which was modified manually to allow better visualization of the connections. Node size represents abundance of the protein. Grey edges represent novel interactions identified by UTX IP-MS, light blue edges represent interactions reported in the literature, and black edges represent previously reported interactions. Note that Esr1 and Banp were not identified in the UTX IP-MS experiment. The protein were included in the network to illustrate their interactions with the newly identified UTX-binding proteins.
(a) In the presence of UTX or UTY, the oncogenic ETS transcriptional program is suppressed by tight regulation of ETS TF expression levels and through coordinated recruitment of chromatin remodelers such as SMARCA4 and the COMPASS complex to open chromatin and lay enhancer marks for important tumour suppressor TF such as GATA2. (b) However, when UTX/UTY are initially lost (in the pre-leukemic phase of disease) an increased expression and binding of ETS TFs occur across the genome, leading to novel enhancer generation with immediate effects upon gene expression at some loci (full arrow). For a larger number of regions ETS TFs bind to closed and compacted chromatin (dashed arrows). In addition, loss of UTX/UTY leads to a lack of coordinated binding and activity of SMARCA4 and the COMPASS complex closing off chromatin accessibility and leading to a loss of enhancer function at GATA binding sites, switching off the GATA program. In addition, the loss of H3K4me1 further leads to a failure to recruit and activate SMARCA4. (c) Subsequently and potentially related to the effects of cooperating mutations, the pioneering effects of ETS TFs lead to gene activation and this evolution of the leukemic transcriptional programs leads to the development of overt AML.
Uncropped western blot images presented in the main and supplementary figures.
Supplementary Figures 1–12
UTX mutant cancer cell lines with affected UTY, from COSMIC database
Differentially expressed genes (adj. P-value<-0.5 and log2FC >0.5) between Utx-/- and Utx+/+ Lin- BM from preleukemic female mice, n = 2 mice per genotype; fold change and P was generated using DESeq2 as described in Methods section.
Differentially expressed genes (adj. P-value<0.05) between Utx-/Y and Utx+/Y Lin- BM from pre-leukemic male mice; n = 2 mice per genotype; fold change and P was generated using DESeq2.
Differentially expressed genes (adj. P-value<0.05, log2FC <-0.5 and log2FC >0.5) in Utx-/- with removed overlapping genes in Utx-/Y. RNA-Seq was performed in Lin- BM from pre-leukemic mice.
Differentially expressed genes (adj P-value<0.05, log2FC <-0.5 and log2FC >0.5) between Utx-/- AML (n = 3 mice) and Utx+/+ Lin- BM from pre-leukemic females (n = 2 mice). Fold change and P was generated using DESeq2.
UTX bound peaks in WT Lin- BM pre-leukemic female mice (n = 2 mice). Unspecific peaks found in IgG control ChIP (from n = 2 mice) were subtracted from UTX-bound peaks.
Downregulated (a) or upregulated (b) genes overlapping UTX bound peaks (adj P-value<0.05 and log2FC <-0.5 and log2FC >0.5) in Utx-/- Lin- BM.
Differentially bound peaks for H3K27me3 (FDR <0.01, FC <-1.5 and FC >1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).
Differentially bound, downregulated peaks for H3K27ac (FDR <0.01, FC <-1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).
Differentially bound, upregulated peaks for H3K27ac (FDR <0.01, FC > 1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).
Overlapping gene loci associated with UTX bound peaks and all differentially bound H3K27ac peaks (FDR<0.01, FC <-1.5 and FC >1.5) in Utx-/- Lin- BM (n = 2 mice per genotype).
Differentially bound peaks for H3K4me1 (FDR <0.01, FC <-1.5 and FC >1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).
Differentially bound peaks for PU.1 ChIP-seq (FDR <0.01, FC <-1.5 and FC >1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 3 mice per genotype).
Overlapping gene loci associated with UTX bound peaks and differentially downregulated H3K27ac peaks (FDR<0.01, FC <-1.5) in Utx-/- Lin- BM (n = 2 mice per genotype).
Mass spectrometry results of UTX interactors in 416b cells.
Mass spectrometry results of UTX interactors in 416b cells.
ATAC-seq. Differentially closed peaks in Utx-/- Lin- BM (FDR<0.01, FC <-1.5) in comparison to Utx+/+ Lin- BM, n = 3 mice per genotype.
ATAC-seq. Differentially open sites in Utx-/- Lin- BM (FDR<0.01, FC <-1.5) compared to Utx+/+ Lin- BM (n = 3 mice per genotype).
Overlapping downregulated gens with closed chromatin sites (ATAC-seq) in Utx-/- Lin- BM (FDR<0.01, FC <-1.5).
ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx+/+ Lin- BM (FDR<0.05, FC ≤ -1.25 and ≥ 1.25) upon knockout of SMARCA4 (Smarca4 gRNA) in comparison to control (Empty gRNA). Cells isolated from n = 2 mice per genotype.
ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx-/- Lin- BM (FDR<0.01, FC ≤ -1.5 and ≥ 1.5) expressing Empty gRNA in comparison to Cas9, Utx+/+ Lin- BM expressing Empty gRNA control. Cells isolated from n = 2 mice per genotype.
ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx-/- Lin- BM (FDR<0.05, FC ≤ -1.2 and ≥1.25) upon knockout of SMARCA4 (Smarca4 gRNA) in comparison to control (Empty gRNA).
ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx+/+ Lin- BM (FDR<0.01, FC ≤ -1.5 and ≥1.5) upon knockout of Chd4 (Chd4 gRNA) in comparison to control (Empty gRNA). Cells isolated from n = 2 mice per genotype.
Overlapping upregulated gens with open chromatin sites (ATAC-seq) in Utx-/- Lin- BM (FDR<0.01, FC >1.5).
Differentially expressed genes (adj P-value<0.05, log2FC <-0.5 and log2FC >0.5) between Utx-/- Lin- BM from pre-leukemic females (n = 2 mice) and Utx-/- AML (n = 3 mice).
Genes overexpressed in Utx-/- AML (but not in pre-leukaemic setting) and bound by PU.1 in closed in pre-leukaemic Utx-/- Lin- BM; (FDR<0.01, FC >1.5). duplicated names were removed.
Primer sequences used for qRT-PCR and ChIP-qPCR
Primer sequences used for Gibson cloning
Motif analysis presented in the study, output tables were obtained with Homer software. Statistical analysis was determined by HOMER software; n = 2 mice per genotype for RNA-seq, ChIP-seq and ATAC-seq in vitro; n = 3 mice per genotype for ATAC-seq in Lin-ve BM.
RNA-seq raw and process file description.
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Gozdecka, M., Meduri, E., Mazan, M. et al. UTX-mediated enhancer and chromatin remodeling suppresses myeloid leukemogenesis through noncatalytic inverse regulation of ETS and GATA programs. Nat Genet 50, 883–894 (2018). https://doi.org/10.1038/s41588-018-0114-z
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