Literature DB >> 31897485

BET inhibition prevents aberrant RUNX1 and ERG transcription in STAG2 mutant leukaemia cells.

Jisha Antony1,2, Gregory Gimenez1, Terry Taylor3, Umaima Khatoon1, Robert Day4, Ian M Morison1, Julia A Horsfield1,2.   

Abstract

Entities:  

Keywords:  CRISPR-Cas9; ERG; RUNX1; STAG2; chromatin; cohesin; enhancer; inducible; megakaryocyte

Year:  2020        PMID: 31897485      PMCID: PMC7288737          DOI: 10.1093/jmcb/mjz114

Source DB:  PubMed          Journal:  J Mol Cell Biol        ISSN: 1759-4685            Impact factor:   6.216


× No keyword cloud information.
Dear Editor, Cohesin is a multiprotein complex that not only is essential for cell division but also has key roles in genome organization that underpin its gene regulatory function. Recurrent mutations of genes encoding cohesin subunits occur in myeloid malignancies at 10%–12% (Kon et al., 2013), and the frequency of cohesin mutation in Down syndrome-associated megakaryoblastic leukaemia is even higher (~50%) (Yoshida et al., 2013). Cohesin insufficiency reinforces stem cell programmes and impairs differentiation in haematopoietic stem cells (Mazumdar et al., 2015; Mullenders et al., 2015; Viny et al., 2015). The STAG2 subunit of cohesin is the most frequently mutated in myeloid malignancies (Kon et al., 2013). In contrast to other cohesin subunits, complete loss of STAG2 is tolerated due to partial compensation by STAG1. STAG2 and STAG1 have redundant roles in cell division (Benedetti et al., 2017; van der Lelij et al., 2017). However, cohesin-STAG1 and cohesin-STAG2 have non-redundant roles in facilitating 3D genome organization to delineate tissue-specific gene expression (Kojic et al., 2018). Cohesin depletion was previously shown to alter chromatin accessibility and transcription of the RUNX1 and ERG genes (Mazumdar et al., 2015), which encode transcription factors that regulate haematopoietic differentiation. Here we used CRISPR-Cas9 to edit K562 erythroleukaemia cells to contain a patient-specific STAG2 R614* mutation (Mullenders et al., 2015) and found that RUNX1 and ERG are precociously transcribed in response to phorbol 12-myristate 13-acetate (PMA)-induced megakaryocytic differentiation. We characterized two K562 edited lines with homozygous STAG2 R614* mutation (STAG2-null and STAG2-null) (Figure 1A; Supplementary Figures S1 and S2, Data S1, and Material). Both STAG2-null lines showed complete loss of STAG2 (Figure 1B). STAG2-null K562 cells exhibited occasional adherent characteristics (Figure 1C) and slower cell cycle progression (Supplementary Figure S3). Array CGH showed that both STAG2-null lines had varying minor gains and losses of genetic material relative to the parental line (Supplementary Figure S4 and Data S2). Nevertheless, both STAG2-null transcriptomes clustered together and were distinct from the parental line (Supplementary Figure S5). Consistent with potential compensation by STAG1, both STAG2-null lines showed 1.6-fold upregulation in STAG1 (Supplementary Figure S6). Several transcription factors, kinases, chemokines, cytokines, and lineage markers that were lowly expressed in parental cells were significantly upregulated in one or both STAG2-null clones (Supplementary Figure S7). Gene set enrichment analyses revealed loss of the typical K562 associated chronic myelogenous transcription profile (Supplementary Figure S8). STAG2-null cells upregulated extracellular matrix genes reflecting their adherent phenotype and gained a stem cell-like expression signature (Figure 1D; Supplementary Figure S8). These results show that STAG2 depletion leads to profound morphological and transcriptional changes.
Figure 1

STAG2 mutation alters chromatin accessibility and response to cell signaling. (A) Schematic of STAG2 protein showing the position of STAG2 R614* (C>T) mutation. Shown also is the Sanger sequencing plot for CRISPR-Cas9-edited K562 line containing homozygous STAG2 R614* mutation (STAG2-null). A silent mutation was introduced at PAM site in STAG2-null cells. (B) Immunoblot analyses of STAG2 protein levels in parental (WT) and STAG2-null cells. Bar graphs show STAG2 protein normalized to γ-tubulin from three biological replicates. Significance was determined by unpaired t-test. L, protein ladder. (C) Images of WT and STAG2-null K562 cells in culture. (D) Gene set enrichment analyses showing upregulation of extracellular matrix (Naba core matrisome) and haematopoietic stem cell genes in STAG2-null Shown are the normalized enrichment score (NES) and FDR q-value. (E) Volcano plot of differential chromatin accessibility in STAG2-null compared to WT K562 cells. Significant peaks at adjusted P-value ≤ 0.05 are shown in red (52452 sites showing differential accessibility, 29432 differentially increased and 23020 differentially decreased). Lines indicate log2 fold change cut-off: 2. (F) Enrichment of differentially increased and decreased accessible sites identified in STAG2-null at SEs (defined in K562, CD34+ cord blood cells, and CD14+ monocytes). (G) Integrative genome browser view of normalized ATAC-sequencing signals from STAG2-null and WT cells at ERG and RUNX1. Significant (P ≤ 0.05) accessible sites at RUNX1-P2 promoter and ERG +85 kb enhancer are boxed. ChromHMM data for K562 (derived from ENCODE) is shown at the top of each plot, and additional tracks are BRD4 binding in K562 following treatment with dimethyl sulfoxide (DMSO) or 6 h of JQ1 (Liu et al., 2017). (H and I) ERG (H) and RUNX1-P2 (I) expression levels examined over a time-course treatment with PMA, JQ1, or a combination of PMA and JQ1. Graphs depict average relative mRNA levels from three biological replicates normalized to two reference genes. Black asterisks denote significant difference between WT and STAG2-null lines following PMA-only treatment. Green asterisks denote significant difference between PMA-only and combination of PMA and JQ1 treatment within each cell type. Significance was determined by two-way Anova. (J) Relative mean fluorescence intensity (MFI) of KIT and CD15 following treatment with control DMSO or JQ1 for 24 h. Relative MFI for each cell type and condition was determined as a ratio of MFI in stained/unstained. Graphs represent the average of three biological replicates. Significance was determined by two-way Anova. Black asterisks denote significant difference between WT and STAG2-null cells for the same condition. Red asterisks denote significant difference between DMSO and JQ1 treatment within each cell type. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

STAG2 mutation alters chromatin accessibility and response to cell signaling. (A) Schematic of STAG2 protein showing the position of STAG2 R614* (C>T) mutation. Shown also is the Sanger sequencing plot for CRISPR-Cas9-edited K562 line containing homozygous STAG2 R614* mutation (STAG2-null). A silent mutation was introduced at PAM site in STAG2-null cells. (B) Immunoblot analyses of STAG2 protein levels in parental (WT) and STAG2-null cells. Bar graphs show STAG2 protein normalized to γ-tubulin from three biological replicates. Significance was determined by unpaired t-test. L, protein ladder. (C) Images of WT and STAG2-null K562 cells in culture. (D) Gene set enrichment analyses showing upregulation of extracellular matrix (Naba core matrisome) and haematopoietic stem cell genes in STAG2-null Shown are the normalized enrichment score (NES) and FDR q-value. (E) Volcano plot of differential chromatin accessibility in STAG2-null compared to WT K562 cells. Significant peaks at adjusted P-value ≤ 0.05 are shown in red (52452 sites showing differential accessibility, 29432 differentially increased and 23020 differentially decreased). Lines indicate log2 fold change cut-off: 2. (F) Enrichment of differentially increased and decreased accessible sites identified in STAG2-null at SEs (defined in K562, CD34+ cord blood cells, and CD14+ monocytes). (G) Integrative genome browser view of normalized ATAC-sequencing signals from STAG2-null and WT cells at ERG and RUNX1. Significant (P ≤ 0.05) accessible sites at RUNX1-P2 promoter and ERG +85 kb enhancer are boxed. ChromHMM data for K562 (derived from ENCODE) is shown at the top of each plot, and additional tracks are BRD4 binding in K562 following treatment with dimethyl sulfoxide (DMSO) or 6 h of JQ1 (Liu et al., 2017). (H and I) ERG (H) and RUNX1-P2 (I) expression levels examined over a time-course treatment with PMA, JQ1, or a combination of PMA and JQ1. Graphs depict average relative mRNA levels from three biological replicates normalized to two reference genes. Black asterisks denote significant difference between WT and STAG2-null lines following PMA-only treatment. Green asterisks denote significant difference between PMA-only and combination of PMA and JQ1 treatment within each cell type. Significance was determined by two-way Anova. (J) Relative mean fluorescence intensity (MFI) of KIT and CD15 following treatment with control DMSO or JQ1 for 24 h. Relative MFI for each cell type and condition was determined as a ratio of MFI in stained/unstained. Graphs represent the average of three biological replicates. Significance was determined by two-way Anova. Black asterisks denote significant difference between WT and STAG2-null cells for the same condition. Red asterisks denote significant difference between DMSO and JQ1 treatment within each cell type. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. ATAC-sequencing showed that chromatin accessibility was differentially altered at ~50000 sites in STAG2-null cells (Figure 1E; Supplementary Data S3). Motif analyses of differentially accessible sites identified strong enrichment for the enhancer-regulating bZIP or AP-1 factors (FRA1, FRA2, JUN-AP1) at sites of increased accessibility and for CTCF and CTCFL (BORIS) at sites of decreased accessibility (Supplementary Figure S9). In STAG2-null cells, we observed increased chromatin accessibility at super enhancers (SEs) defined for K562, CD34+ primary cord blood cells, and CD14+ monocytes (Figure 1F); 45% genes near SEs with differential accessibility also displayed altered transcript levels in STAG2-null cells. SE-proximal genes included those encoding cell lineage markers or transcription factors (Supplementary Figure S10 and Data S4). The RUNX1 and ERG loci contain SEs in CD34+ cells. SEs in proximity to RUNX1 and ERG gained accessibility in STAG2-null cells (Supplementary Figure S11). Many of the increased accessible sites were bound by a variety of AP-1 factors at RUNX1 and primarily by JUND at ERG (Supplementary Figure S11). Closer visualization revealed that the prominent ATAC sites in K562 are at the stem cell-associated ERG +85 kb enhancer and at the RUNX1-P2 promoter, and both these sites showed increased accessibility in STAG2-null (Figure 1G). To determine if STAG2 mutation affects RUNX1 and ERG expression during megakaryocyte differentiation, we stimulated cells with PMA and used quantitative PCR to measure changes over 72 h. Parental K562 cells showed gradual induction of RUNX1-P1 and ERG transcription during stimulation (Supplementary Figure S12; Figure 1H). In contrast, STAG2-null cells showed an aberrant spike of RUNX1 transcription 6–12 h post-stimulation from the proximal P2 promoter (Figure 1I; Supplementary Figure S12). A similar aberrant spike was observed in transcription of ERG (Figure 1H). By 48 h post-stimulation, RUNX1 and ERG transcription had returned to baseline in STAG2-null cells. These results imply that increased chromatin accessibility at RUNX1 and ERG in STAG2-null cells leads to unrestrained transcription in response to differentiation stimuli. K562 parental cells upregulated GATA1 and downregulated KLF1 by 48 h post-stimulation (Supplementary Figure S13), consistent with megakaryocyte differentiation. While STAG2-null cells successfully downregulated KLF1, they were not able to upregulate GATA1. BRD4 is a bromodomain-containing protein that associates with active enhancers (Bhagwat et al., 2016). Notably, BRD4 binds at the RUNX1-P2 and ERG +85 kb enhancer (Figure 1G). JQ1 is a bromodomain and extra-terminal motif (BET) inhibitor protein that reduces BRD4 binding and dampens SE-driven transcription. BRD4 can be removed from RUNX1 and ERG by the BET inhibitor, JQ1 (Figure 1G, data from Liu et al., 2017). We treated STAG2-null cells with JQ1 together with PMA and measured expression spikes in RUNX1-2 and ERG. JQ1 reduced RUNX1-P2 and ERG expression in parental cells and, strikingly, dampened the PMA-induced transcription spikes in STAG2-null cells (Figure 1H and I; Supplementary Figure S12). RUNX1-P1 transcription was completely blocked by JQ1 in both parental and STAG2-null cells (Supplementary Figure S12). STAG2-null cells have reduced expression of the differentiation marker CD15 and elevated levels of the stem cell-associated marker, KIT (CD117), which is only lowly expressed in K562 cells (Figure 1J; Supplementary Figure S14A). Following 24 h of treatment with JQ1, cell surface protein levels of KIT reduced by 2-fold in both STAG2-null clones while mRNA was reduced dramatically following 6 h of treatment (Figure 1J; Supplementary Figure S14). However, JQ1 treatment did not increase CD15 in STAG2-null cells (Figure 1J; Supplementary Figure S14A), implying that differentiation is not rescued. Collectively, the data indicate that BET inhibition can limit aberrant RUNX1/ERG transcription and reduce leukaemic stem cell-associated KIT expression in STAG2 mutant cells. Overall, our results suggest that cohesin-STAG2 depletion de-constrains the chromatin surrounding RUNX1 and ERG, which causes aberrant enhancer-amplified transcription in response to differentiation signals. We show that enhancer suppression using BET inhibitor JQ1 prevents aberrant RUNX1 and ERG signal-induced transcription in STAG2 mutant cells and reduces leukaemic stem cell characteristics of STAG2 mutants. [. and J.A.H. J.A. and J.A.H. designed the research; J.A., T.T., U.K., R.D., and I.M.M. performed experiments; J.A., G.G., and J.A.H. analysed data; and J.A., G.G., and J.A.H. wrote the paper.] Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.
  10 in total

1.  In Situ Capture of Chromatin Interactions by Biotinylated dCas9.

Authors:  Xin Liu; Yuannyu Zhang; Yong Chen; Mushan Li; Feng Zhou; Kailong Li; Hui Cao; Min Ni; Yuxuan Liu; Zhimin Gu; Kathryn E Dickerson; Shiqi Xie; Gary C Hon; Zhenyu Xuan; Michael Q Zhang; Zhen Shao; Jian Xu
Journal:  Cell       Date:  2017-08-24       Impact factor: 41.582

2.  The landscape of somatic mutations in Down syndrome-related myeloid disorders.

Authors:  Kenichi Yoshida; Tsutomu Toki; Yusuke Okuno; Rika Kanezaki; Yuichi Shiraishi; Aiko Sato-Otsubo; Masashi Sanada; Myoung-ja Park; Kiminori Terui; Hiromichi Suzuki; Ayana Kon; Yasunobu Nagata; Yusuke Sato; RuNan Wang; Norio Shiba; Kenichi Chiba; Hiroko Tanaka; Asahito Hama; Hideki Muramatsu; Daisuke Hasegawa; Kazuhiro Nakamura; Hirokazu Kanegane; Keiko Tsukamoto; Souichi Adachi; Kiyoshi Kawakami; Koji Kato; Ryosei Nishimura; Shai Izraeli; Yasuhide Hayashi; Satoru Miyano; Seiji Kojima; Etsuro Ito; Seishi Ogawa
Journal:  Nat Genet       Date:  2013-09-22       Impact factor: 38.330

3.  Recurrent mutations in multiple components of the cohesin complex in myeloid neoplasms.

Authors:  Ayana Kon; Lee-Yung Shih; Masashi Minamino; Masashi Sanada; Yuichi Shiraishi; Yasunobu Nagata; Kenichi Yoshida; Yusuke Okuno; Masashige Bando; Ryuichiro Nakato; Shumpei Ishikawa; Aiko Sato-Otsubo; Genta Nagae; Aiko Nishimoto; Claudia Haferlach; Daniel Nowak; Yusuke Sato; Tamara Alpermann; Masao Nagasaki; Teppei Shimamura; Hiroko Tanaka; Kenichi Chiba; Ryo Yamamoto; Tomoyuki Yamaguchi; Makoto Otsu; Naoshi Obara; Mamiko Sakata-Yanagimoto; Tsuyoshi Nakamaki; Ken Ishiyama; Florian Nolte; Wolf-Karsten Hofmann; Shuichi Miyawaki; Shigeru Chiba; Hiraku Mori; Hiromitsu Nakauchi; H Phillip Koeffler; Hiroyuki Aburatani; Torsten Haferlach; Katsuhiko Shirahige; Satoru Miyano; Seishi Ogawa
Journal:  Nat Genet       Date:  2013-08-18       Impact factor: 38.330

4.  BET Bromodomain Inhibition Releases the Mediator Complex from Select cis-Regulatory Elements.

Authors:  Anand S Bhagwat; Jae-Seok Roe; Beverly Y L Mok; Anja F Hohmann; Junwei Shi; Christopher R Vakoc
Journal:  Cell Rep       Date:  2016-04-07       Impact factor: 9.423

5.  Leukemia-Associated Cohesin Mutants Dominantly Enforce Stem Cell Programs and Impair Human Hematopoietic Progenitor Differentiation.

Authors:  Claire Mazumdar; Ying Shen; Seethu Xavy; Feifei Zhao; Andreas Reinisch; Rui Li; M Ryan Corces; Ryan A Flynn; Jason D Buenrostro; Steven M Chan; Daniel Thomas; Julie L Koenig; Wan-Jen Hong; Howard Y Chang; Ravindra Majeti
Journal:  Cell Stem Cell       Date:  2015-10-22       Impact factor: 24.633

6.  Cohesin loss alters adult hematopoietic stem cell homeostasis, leading to myeloproliferative neoplasms.

Authors:  Jasper Mullenders; Beatriz Aranda-Orgilles; Priscillia Lhoumaud; Matthew Keller; Juhee Pae; Kun Wang; Clarisse Kayembe; Pedro P Rocha; Ramya Raviram; Yixiao Gong; Prem K Premsrirut; Aristotelis Tsirigos; Richard Bonneau; Jane A Skok; Luisa Cimmino; Daniela Hoehn; Iannis Aifantis
Journal:  J Exp Med       Date:  2015-10-05       Impact factor: 14.307

7.  Dose-dependent role of the cohesin complex in normal and malignant hematopoiesis.

Authors:  Aaron D Viny; Christopher J Ott; Barbara Spitzer; Martin Rivas; Cem Meydan; Efthymia Papalexi; Dana Yelin; Kaitlyn Shank; Jaime Reyes; April Chiu; Yevgeniy Romin; Vitaly Boyko; Swapna Thota; Jaroslaw P Maciejewski; Ari Melnick; James E Bradner; Ross L Levine
Journal:  J Exp Med       Date:  2015-10-05       Impact factor: 14.307

8.  Synthetic lethality between the cohesin subunits STAG1 and STAG2 in diverse cancer contexts.

Authors:  Petra van der Lelij; Simone Lieb; Julian Jude; Gordana Wutz; Catarina P Santos; Katrina Falkenberg; Andreas Schlattl; Jozef Ban; Raphaela Schwentner; Thomas Hoffmann; Heinrich Kovar; Francisco X Real; Todd Waldman; Mark A Pearson; Norbert Kraut; Jan-Michael Peters; Johannes Zuber; Mark Petronczki
Journal:  Elife       Date:  2017-07-10       Impact factor: 8.140

9.  Synthetic lethal interaction between the tumour suppressor STAG2 and its paralog STAG1.

Authors:  Lorena Benedetti; Matteo Cereda; LeeAnn Monteverde; Nikita Desai; Francesca D Ciccarelli
Journal:  Oncotarget       Date:  2017-06-06

10.  Distinct roles of cohesin-SA1 and cohesin-SA2 in 3D chromosome organization.

Authors:  Aleksandar Kojic; Ana Cuadrado; Magali De Koninck; Daniel Giménez-Llorente; Miriam Rodríguez-Corsino; Gonzalo Gómez-López; François Le Dily; Marc A Marti-Renom; Ana Losada
Journal:  Nat Struct Mol Biol       Date:  2018-06-04       Impact factor: 15.369

  10 in total
  8 in total

1.  Transcriptional Regulation of RUNX1: An Informatics Analysis.

Authors:  Amarni L Thomas; Judith Marsman; Jisha Antony; William Schierding; Justin M O'Sullivan; Julia A Horsfield
Journal:  Genes (Basel)       Date:  2021-07-29       Impact factor: 4.096

2.  Cohesin mutations are synthetic lethal with stimulation of WNT signaling.

Authors:  Chue Vin Chin; Jisha Antony; Sarada Ketharnathan; Anastasia Labudina; Gregory Gimenez; Kate M Parsons; Jinshu He; Amee J George; Maria Michela Pallotta; Antonio Musio; Antony Braithwaite; Parry Guilford; Ross D Hannan; Julia A Horsfield
Journal:  Elife       Date:  2020-12-07       Impact factor: 8.140

3.  Cohesin Components Stag1 and Stag2 Differentially Influence Haematopoietic Mesoderm Development in Zebrafish Embryos.

Authors:  Sarada Ketharnathan; Anastasia Labudina; Julia A Horsfield
Journal:  Front Cell Dev Biol       Date:  2020-12-07

4.  Dynamic Runx1 chromatin boundaries affect gene expression in hematopoietic development.

Authors:  Dominic D G Owens; Giorgio Anselmi; A Marieke Oudelaar; Damien J Downes; Alessandro Cavallo; Joe R Harman; Ron Schwessinger; Akin Bucakci; Lucas Greder; Sara de Ornellas; Danuta Jeziorska; Jelena Telenius; Jim R Hughes; Marella F T R de Bruijn
Journal:  Nat Commun       Date:  2022-02-09       Impact factor: 17.694

Review 5.  Cohesin Mutations in Cancer: Emerging Therapeutic Targets.

Authors:  Jisha Antony; Chue Vin Chin; Julia A Horsfield
Journal:  Int J Mol Sci       Date:  2021-06-24       Impact factor: 5.923

Review 6.  Cohesin mutations in myeloid malignancies.

Authors:  Johann-Christoph Jann; Zuzana Tothova
Journal:  Blood       Date:  2021-08-26       Impact factor: 25.476

Review 7.  A cohesive look at leukemogenesis: The cohesin complex and other driving mutations in AML.

Authors:  Katelyn E Heimbruch; Alison E Meyer; Puja Agrawal; Aaron D Viny; Sridhar Rao
Journal:  Neoplasia       Date:  2021-02-20       Impact factor: 5.715

8.  Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways.

Authors:  William Schierding; Julia A Horsfield; Justin M O'Sullivan
Journal:  J Med Genet       Date:  2020-09-11       Impact factor: 6.318

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.