The lysine methyltransferase 2a (KMT2A) (which is also known and hereafter referred to as mixed-lineage leukemia [MLL], trithorax [Drosophila] homolog gene) plays a pivotal role in embryogenesis and hematopoiesis. Recurrent, balanced translocations involving the MLL gene [t(v;11q23)] are heterogeneous, and more than 75 different fusion partners have been described as important drivers in acute myeloid leukemia (AML) leukemogenesis. 1,2 Beside chromosomal aberrations, a unique gene rearrangement in MLL known as partial tandem duplication (PTD) can be found in approximately 5-11% of cytogenetically normal AML (CN-AML) patients. This mutation is associated with poor prognosis.3-8 Although both t(v;11q23) and the MLL-PTD result in increased HOMEOBOX (HOX) gene expression in leukemic blasts, t(v;11q23) have been shown to be genetically and functionally distinct from the MLL-PTD.9 While almost all t(v;11q23) lose their C-terminal transactivation and methyltransferase domains, these C-terminal domains are retained in the MLL-PTD.9
The transcription factor BRD4 is a member of the bromodomain and extra terminal (BET) family of proteins. Aberrant BRD4 binding and gene activation has been shown to be important for t(v;11q23)-mediated leukemogenesis. 10 JQ1 is one of the best-characterized, small molecule bromodomain inhibitors.11 However, the potential use of JQ1 in MLL-PTD AML has not been extensively studied yet. Therefore, we examined whether MLL-PTD AML blasts are sensitive to JQ1 treatment and if BRD4 inhibition results in an altered binding of the transcription factor to DNA.12
First, we tested whether JQ1 treatment has an impact on cell proliferation and survival in a MLL-PTD+ AML cell line (i.e., EOL-1) and in a MLL wild-type cell line (i.e., K562).13 Both cell lines were treated with JQ1 or dimethyl sulfoxide (DMSO) vehicle control for 24 hours (h) at different concentrations and cell growth was assessed by WST-1 assay. We found a significant decrease in cell proliferation in EOL1 cells (IC50 = 321 nM) but not in K562 cells (Figure 1A). Concomitantly, we found a significant and dose dependent increase in the number of apoptotic EOL-1 cells (Figure 1B) but not in the K562 cells (Online Supplementary Figure S1A). We also analyzed the effect of JQ1 treatment on primary blast cell growth from three AML patients that harbor a MLL-PTD compared to normal hematopoietic stem and progenitor cells (HSPC; CD34+ cord blood) controls. We found JQ1 treatment significantly reduced blast cell growth assessed by a decrease in the number of colony-forming cells (CFC) in JQ1-treated MLL-PTD AML samples, with no significant decreases of CFC in normal HSPC (Figure 1C) or MLL wild-type (wt) primary patient samples (Online Supplementary Figure S1B).
Next, we tested the effect of JQ1 in a murine AML mouse model. For these experiments we used our well established MllPTD/WT Flt3ITD/WT double knockin AML mouse model14,15 that develops lethal CN-AML with ~100% penetrance. In secondary bone marrow transplantation, it leads to death within 6 to 12 weeks.14,15 Of note, MLL-PTD is predominantly found in CN-AML in humans. First, we wanted to determine whether JQ1 also induced apoptosis in the MllPTD/WT Flt3ITD/WT mouse AML blasts, similar to what we observed in human AML blasts. We found that JQ1 induced a significant increase in apoptosis assessed by Annexin V staining in the MllPTD/WT Flt3ITD/WT blasts (Figure 1D) with essentially no toxicity to normal murine bone marrow cells (Online Supplementary Figure S1C). Based on these promising in vitro results, we then wanted to test, whether targeting BRD4 in vivo would result in prolonged survival of mice with Mll-PTD+ leukemia. In order to test the antileukemic activity of JQ1 in a murine AML model, we used our previously established MllPTD/WT Flt3ITD/WT mouse model.14-16 We observed a significant increase in survival of JQ1 treated MllPTD/WT Flt3ITD/WT mice compared to mice treated with vehicle control (Figure 1E). Moreover, the mice that eventually succumbed to disease and were treated with JQ1 had significant lower spleen weight, indicating a lower leukemic burden (Figure 1F). Interestingly, we also found that the leukemic bone marrow cells from JQ1-treated mice had a significant lower engraftment potential after re-transplantation than cells from mice treated with vehicle control (Online Supplementary Figure S1D). These data suggested that JQ1 might also have an impact on leukemic cell self-renewal and consequently leukemia stem cells (LSC) in Mll-PTD AML, however further experiments are needed to fully address effects on LSC by JQ1 in Mll-PTD leukemia.
After identifying the ability of JQ1 to decrease MLL-PTD+ AML blast growth in vitro and in vivo, we wanted to determine whether alterations in BRD4 binding accounts for MLL-PTD blast sensitivity to BRD4-inhibition. BRD4 has been shown to be a positive regulator of gene transcription and aberrant BRD4-binding in cancer induces alterations in gene expression. Thus, we hypothesize that MLL-PTD leukemogenesis is driven by dysregulation of gene expression patterns resulting from aberrant BRD4 binding. Furthermore, we wanted to determine whether normal BRD4 binding could be restored by treatment with JQ1. In order to address this question, we performed total RNA sequencing (RNA-seq) on primary MLL-PTD AML blasts and normal HSPC treated with JQ1 or vehicle control (n=3 for each group, pooled) before and after JQ1 treatment and analyzed as previously described.18 In addition, we performed chromatin immunoprecipitation sequencing (ChIP-seq) using a BRD4 antibody. Cells from three healthy cord blood donors (CB) and primary leukemic cells from three patients with MLL-PTD were treated with either JQ1 (10 nM) or vehicle (DMSO) for 24 hours (h) and ChIP was performed as previously described.18 The 75-basepair sequence reads were generated using an llumina sequencing platform (NextSeq 500) and then mapped to the human reference genome (GRCh37/hg19) using the BWA algorithm with default settings.19 Aligned reads were normalized and genomic regions with local enrichments against corresponding input sample, peaks, were defined using MACS algorithm with a cutoff P-value of 1e-7.20 Consensus peaks were defined by merging overlapping peak coordinates and peak scores were calculated. The resulting matrix was annotated with gene information by calculating distances from RefSeq gene starts and ends to the center of the consensus peak regions and applying an annotation cutoff of 5 kb. Similar to what has previously been described for t(v;11q23)-AML that BRD4 has an aberrant binding profile, we found three times more and stronger genomic interactions of BRD4 in the MLL-PTD patient sample compared to normal HSPC, and only 22% of the BRD4 peaks in MLL-PTD overlapped with normal HSPC in ChIP-seq (Figure 2A). When we treated the MLL-PTD sample with JQ1, both the number of peaks and their intensity decreased, whereas JQ1 treatment did not affect BRD4 binding in HSPC (Figure 2B). Next, by integrating the RNA-seq and ChIPseq data, we wanted to determine which genes had alterations in BRD4 binding, leading to mRNA changes in the AML patient cells compared to normal CD34+ cells. For these analyses, the data obtained from RNA-seq counts, and ChIP-seq using BRD4, were merged by gene id. Our strategy to detect different patterns of changes in peak scores and gene expression consisted in the conversion of the values into quartiles in way to define MLL-PTD specific response to JQ1 treatment.
Furthermore, we also wanted to determine the alterations that were reversed by BRD4-inhibiton. First, we identified BRD4 binding sites that were close by to a gene’s transcription start site (TSS), specifically bound in MLL-PTD cells but not in HSPC and could be suppressed by at least 25% through JQ1 treatment. Then, the genes close by such BRD4 binding sites and presenting the same pattern in their expression were classified as positive response to treatment, whereas the genes that present the opposite trend in their expression were classified as negative response to treatment (Figure 2C). As result, we identified genes whose expression was positively or negatively regulated by changes in BRD4 binding specific in the MLL-PTD AML sample and could be reversed by JQ1 treatment (Figure 2D). We identified 92 genes which were significantly upregulated in MLL-PTD AML cells through BRD4 binding and which were downregulated by BRD4 inhibition (Online Supplementary Table S1). As an example, Figure 2E shows the expression of ADAMDEC1 which is increased in MLL-PTD AML cells and correlates with binding of BRD4. On the other hand, 38 genes were downregulated by BRD4 in the MLL-PTD AML cells and its inhibition led to a re-expression (Online Supplementary Table S1). We also performed ingenuity pathway analysis (IPA) from the ChIP-RNA integration and identified pathways that are affected by BRD4-mediated transcriptional changes (Online Supplementary Table S2). These data suggest that the distinct gene expression profile of MLL-PTD positive AML, is at least partly driven by the transcription factor BRD4, similar to AML cells which harbor a t(v;11q23). In addition, we showed that this aberrant expression can be restored after JQ1 treatment. Because we compared only cells from one patient (treated vs. untreated) with HSPC from three pooled CB samples, next we wanted to validate the direct binding of BRD4 to two genes that were upregulated in MLL-PTD AML cells, i.e., ADAMDEC1 and SLAMF8 (Figure 3A). These genes were also shown to have a functional role in MLL-PTD cells since knockdown of either of these genes resulted in decreased leukemic cell growth (Online Supplementary Figure S1E). Using a chromatin immunoprecipitation followed by quantitative real-time polymerase chain reaction (qRT-PCR), we show that BRD4 binds to ADAMDEC1 and SLAMF8, and this binding can be repressed by JQ1 treatment. Moreover, both genes are upregulated in MLL-PTD AML patients cells compared to CB cells (Figure 3B). For both genes, JQ1 treatment led to decreased expression. Similar results were found when MLL-PTD was knocked down (Online Supplementary Figure S1F and G). We also found similar results in our in vivo mouse model. Mice treated with JQ1 had lower expression of several potential oncogenes, including Adamdec1 and Slamf8 (Online Supplementary Figure S1H to J). Finally, we showed that JQ1 treatment of MLL-PTD cells also results in the decreased expression of BCL2, CDK6, and MYC, well-established downstream targets of BRD4 (Figure 3C).1,2 We found that knocking down the MLL-PTD fusion gene using a short hairpin RNA (shRNA) also resulted in downregulation of these proteins regulated by BRD4, similar to treatment with JQ1 (Figure 3D). Previously, it has been shown that fusion proteins from t(v;11q23) can initiate aberrant gene expression profiles by recruiting BRD4.1 Our data suggest that in MLL-PTD cells utilize a similar mechanism and could account for the distinct gene expression profile.
Taken together, our data shows that targeting BRD4 with the small molecule JQ1 reduces cell proliferation of MLL-PTD cells in vitro and induces apoptosis. In line, we found that JQ1 treatment decreased leukemic burden in vivo and improved survival in vivo. We show for the first time to our knowledge, that aberrant BRD4 binding in MLL-PTD cells results in a distinct deregulation of genes. By integrating the RNA-seq and ChIP-seq analysis, we identified targets relevant to the MLL-PTD subgroup of AML patients and validated in additional samples from MLL-PTD+ AML primary patient blasts and our unique AML mouse model. This novel group of genes might be associated with leukemogenesis of MLL-PTD+ CN-AML and also with the poor prognosis of this subgroup. Importantly, we were able to reverse the aberrant gene expression patterns by treatment with JQ1. Therefore, targeting BRD4 might be an effective and promising treatment option for patients harboring a MLL-PTD to improve their outcome.
- Received September 8, 2020
- Accepted April 30, 2021
Disclosures: JEB is a shareholder and executive of Novartis AG and provided JQ1 for the studies. All other authors declare no conflicts of interest.
Contributions: AMD designed the study; MB, CG, FP, BM, MK, RK, DP and GF performed the experiments; MB, CG, FP, BM, MK, RK, SK, DP, GF, RG, JB, GM, MAC and AMD contributed to the data interpretation; MB, CG, FP and AMD wrote the manuscript; HGO and XZ performed bioinformatics and statistical analyses. All authors reviewed the manuscript.
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